Plant phenotyping methods.

A C-repeat binding factor-salicylic acid (CBF-SA) module links wound-induced evaporative cooling to tissue repair in plants. →

Repairing damaged tissues is essential for the survival of all organisms. In plants, tissue injury rapidly triggers defense and repair programs. However, the molecular mechanisms linking early injury cues to the later stage of wound repair remain unclear. Here, we show that wounding of Arabidopsis leaves induces localized low temperature at the injury site, likely caused by evaporative cooling, which is accompanied by an activation of cold-responsive genes. Using thermal imaging combined with computer vision and deep learning, we developed a workflow to monitor the dynamics of wound healing in a quantitative, non-invasive, and real-time manner. Mechanistically, we show that C-repeat Binding Factor (CBF) transcription factors are required for the activation of the injury-associated cold response and downstream salicylic acid (SA) signaling. Our findings suggest that the CBF-SA pathway acts coordinately to promote lignin and callose deposition, thereby facilitating wound repair. Together, these findings reveal a link between a wound-induced biophysical cue and the tissue repair program.

Why it matches plant phenotyping methods熱画像とコンピュータビジョン・深層学習を組み合わせ、植物の創傷治癒を定量的・非侵襲的・リアルタイムに測定するワークフローを開発しており、表現型取得法が研究の中心である。

abstractUsing thermal imaging combined with computer vision and deep learning, we developed a workflow to monitor the dynamics of wound healing in a quantitative, non-invasive, and real-time manner.

Prediction models for Larix species via near infrared spectroscopy as a high-throughput phenotyping approach →

Phenotyping extensive populations remains a major constraint in tree breeding programmes, particularly due to the time-consuming and labour-intensive nature of conventional methods. Near infrared (NIR) spectroscopy, which is a high-throughput phenotyping method, offers an alternative solution, providing a rapid and cost-effective approach for assessing growth- and function-based traits on large numbers of trees. This study aimed to evaluate the potential of NIR spectroscopy-based models for predicting such traits in Larch. Specifically, delta carbon-13 ( δ 13 C), carbon (C), nitrogen (N), specific leaf area (SLA), leaf dry matter content (LDM), and phenolics on needles; the branch hydraulic trait (P 50 ), and lignin and hydroxyphenyl/guaiacyl (H/G) ratio on wood cores from an experimental study on Larix species were predicted using multivariate modelling, specifically, partial least squares regression. Reliable models were obtained for N content (R 2 training = 0.95, r 2 testing = 0.94), lignin (R 2 training = 0.95, r 2 testing = 0.94), and H/G ratio (R 2 training = 0.88, r 2 testing = 0.89), while moderate predictive performance was observed for C content (R 2 training = 0.79, r 2 testing = 0.79) and δ 13 C (R 2 training = 0.76, r 2 testing = 0.69). This methodological approach and its results encourage the transition from traditional laboratory methods to efficient, large-scale-based trait evaluation techniques in forestry.

Why it matches plant phenotyping methodsNIR分光とPLS回帰を用いて樹木の複数形質を大規模推定する手法を評価しており、表現型取得・推定法が研究の中心である。

abstractNear infrared (NIR) spectroscopy, which is a high-throughput phenotyping method, offers an alternative solution, providing a rapid and cost-effective approach for assessing growth- and function-based traits on large numbers of trees.

Video-rate label-free molecular mapping in living plant tissue with a deployable optical encoder →

Abstract Living tissues contain dynamic biochemical information that is difficult to capture with conventional hyperspectral microscopes because sequential spectral acquisition is poorly matched to in vivo molecular processes that evolve during measurement. Here we introduce a task-specific optical encoding framework for video-rate molecular inference in living plant tissue. The system integrates a passive spectral encoder, implemented here as a low-angle scattering LDPE layer, into a 22-mm miniaturized probe and learns a supervised mapping from ultraviolet-excited autofluorescence measurements to biomolecular abundance maps. Unlike conventional pipelines that first reconstruct hyperspectral datacubes and then perform spectral unmixing, the deployed system directly estimates endogenous molecular contrast associated primarily with lignin and chlorophyll in poplar tissue, with additional suberin-associated contrast evaluated in suberin-rich tissue. This reframing makes the measurement task biomolecular inference rather than spectral reconstruction, enabling biochemical mapping under low-photon autofluorescence conditions while reducing data burden and computational latency. In living poplar stems, the platform captures autofluorescence-derived videos of embolism propagation and wound-induced biochemical remodeling, dynamic processes for which sequential spectral acquisition can introduce temporal mixing because the molecular contrast evolves during the scan itself. The system also resolves genotype-dependent reductions in lignin-associated autofluorescence in engineered poplar lines. Direct molecular inference improves biomolecular estimation relative to a reconstruction-based pipeline, while probabilistic decoding provides uncertainty estimates. These results show that compact passive spectral encoding, when optimized for biological inference rather than datacube recovery, enables deployable, label-free molecular videography of living plant tissue dynamics after task-specific calibration.

Why it matches plant phenotyping methods生体植物組織の生化学的状態を動画取得・推定する光学センシング手法を開発し、校正、比較評価、不確実性推定まで行っており、表現型取得法が中心である。

abstractHere we introduce a task-specific optical encoding framework for video-rate molecular inference in living plant tissue.

Quantification of microplastic uptake and phytotoxicity in submerged aquatic plants using fluorescence spectroscopy. →

Microplastics (MPs) are persistent and ubiquitous contaminants in aquatic ecosystems, yet their interactions with submerged aquatic plants remain poorly understood. While MP-induced phytotoxicity has been extensively investigated in terrestrial plants, quantitative evidence for MP uptake and internal accumulation in submerged species is still limited. In this study, we investigated the phytotoxicity and accumulation patterns of fluorescent microplastics (FMPs) in two submerged aquatic plants, Bacopa lanigera and Rotala indica, using fluorescence spectroscopy. Plants were exposed to FMPs of two particle sizes (50 nm and 1 µm) across three exposure concentrations (0.001%, 0.01%, and 0.05%). Plant growth, chlorophyll content, fluorescence emission, and FMP accumulation were systematically evaluated. Our results demonstrated clear size- and concentration-dependent responses. Smaller particles (50 nm) showed significantly higher uptake and induced stronger phytotoxic effects than 1 µm particles, with pronounced growth inhibition and chlorophyll reduction observed at the highest concentration (0.05%). Fluorescence-based analysis enabled quantitative estimation of both surface-associated and internalized FMPs within plant tissues. Maximum surface accumulation reached 207 ppm, while internal (cross-sectional) accumulation reached up to 75 ppm, regardless of plant species. Under the respective experimental conditions, B. lanigera exhibited higher estimated FMP accumulation, whereas R. indica showed greater growth inhibition. These findings provide quantitative evidence of microplastic uptake and internal accumulation in submerged aquatic plants and highlight particle size as a critical determinant of phytotoxicity. Moreover, this study establishes a fluorescence-based methodological framework for estimating microplastic concentrations in aquatic plant tissues, contributing to improved ecological risk assessment of microplastics in freshwater ecosystems.

Why it matches plant phenotyping methods蛍光分光法による植物組織内マイクロプラスチック蓄積の定量が中心的な技術貢献であり、植物の蓄積状態と毒性関連表現型を評価している。

abstractusing fluorescence spectroscopy

An optimised FISH-based approach for tissue and subcellular localisation of apple scar skin viroid in cucumber. →

Fluorescence in situ hybridisation (FISH) is a valuable technique for visualising RNA molecules in their native cellular context. Still, its application in plant tissues is often limited by tissue autofluorescence and the lack of optimised protocols. Here, we developed and validated a simple, reproducible FISH workflow to detect Apple scar skin viroid (ASSVd) in cucumber. Systematic optimisation of probe chemistry, tissue selection, and sampling stage significantly improved assay sensitivity and reproducibility. The AZDye594-labelled antisense riboprobe produced higher signal-to-background ratios and lower background fluorescence than fluorescein-labelled probes, enabling reliable detection of ASSVd in vascular-associated tissues. The optimised workflow consistently detected ASSVd in both leaves and stems. High-resolution confocal imaging further revealed predominant nuclear accumulation of ASSVd RNA in infected cells. Together, this study establishes a sensitive and accessible FISH workflow for localisation of ASSVd in cucumber and provides a practical platform for investigating the spatial distribution of viroid and other plant RNA pathogens.

Why it matches plant phenotyping methods植物組織内の病原体RNAの空間局在を可視化・定量可能にするFISHワークフローを開発・検証しており、植物状態の画像取得法が研究の中心である。

abstractHere, we developed and validated a simple, reproducible FISH workflow to detect Apple scar skin viroid (ASSVd) in cucumber.

Optimizing cell segmentation and downstream processing for plant probe-based spatial transcriptomics →

Abstract Probe-based spatial transcriptomics platforms use predefined oligonucleotide panels to detect selected RNAs in tissue sections while preserving transcript spatial coordinates. Accurate cell segmentation is required for reliable transcript-to-cell assignments. This analytical process is affected in plant tissues by cell walls, large vacuoles, and strong autofluorescence, which often reduce boundary contrast and elevate background. Nucleus-only segmentation with fixed-distance expansion can be an alternative approach, but it underestimates cellular area and morphology and reduces the number of assignable transcripts per cell. Here, we present a practical workflow for segmentation and downstream processing in plant probe-based spatial transcriptomics. Using the soybean nodule, soybean seed, rice root, and wheat inflorescence, we demonstrate the applicability of our workflow across species, tissues, and technological platforms. In brief, candidate cell masks are generated from available fluorescence signals and then selected and corrected using two napari plugins. Transcript-informed refinement with Baysor is included as an optional step. Upon benchmarking our approach using a collection of metrics (assignment yield, background/negative controls, and per-cell transcript/gene distributions) and linked segmentation choices to expression-matrix quality and downstream clustering, we demonstrate the potential of our workflow to support the analysis of plant probe-based spatial transcriptomics.

Why it matches plant phenotyping methods植物組織の細胞セグメンテーションとトランスクリプト割当てを改善する実用ワークフローを開発し、複数種・組織でベンチマークしている。植物形態そのものの測定ではないが、細胞レベルの空間状態を抽出する解析手法が中心である。

abstractHere, we present a practical workflow for segmentation and downstream processing in plant probe-based spatial transcriptomics.

In-situ visualisation of the micromechanical deformation of apple tissue using 4D X-ray computed tomography with digital volume correlation. →

Continuous X-ray computed tomography (XCT) combined with digital volume correlation (DVC) is presented to quantify internal three-dimensional strain and failure dynamics in apple cortex tissue during compression, revealing how the cellular microstructure governs its mechanical response. We introduce a dimensionless number Mi that is a function of the average interfacial contact area of cells, cell wall thickness, the average cell volume and tissue porosity, to describe tissue microstructure over different development stages. Mechanical softening during maturation aligned strongly with decreasing Mi, linking microstructure to effective Young's modulus, peak stress, and toughness. DVC revealed distinctive strain-distribution signatures: in young, low-porosity tissue, strain was initially diffuse with early-onset localization indicating progressive failure, whereas mature, high-porosity tissue exhibited sharply peaked strain distributions and highly localized fracture planes indicative of brittle collapse. These findings demonstrate how pore evolution, anisotropy, and cell packing jointly determine macroscopic deformation, establishing XCT-DVC as a powerful framework for connecting plant tissue architecture to mechanical function.

Why it matches plant phenotyping methods4D XCTとDVCを用いてリンゴ組織の内部三次元ひずみ、微細構造、破壊状態を定量化する手法が研究の中心であり、植物組織の構造・力学的状態を抽出しているため。

abstractContinuous X-ray computed tomography (XCT) combined with digital volume correlation (DVC) is presented to quantify internal three-dimensional strain and failure dynamics in apple cortex tissue during compression

RADIX: a deep learning framework that maps root barriers across species and reveals genetic and environmental contributions →

Root anatomical barriers, including the suberized and lignified walls of the endodermis and exodermis, and cortical aerenchyma, regulate water and nutrient transport, gas exchange, and rhizosphere interaction. Their adaptive function places them as an important target for breeding environmentally resilient plant species. Quantifying these structures at high resolution is a manual bottleneck that limits experimental scale. We present RADIX (Root Anatomy Deep- learning Image segmentation across species and platforms), a framework that adapts a large self-supervised vision-transformer foundation encoder (DINOv3), pre-trained on billions of natural images, to root anatomy by fine-tuning its encoder with a dense-prediction-transformer decoder. Transferring these general-purpose vision encoders to a specialized biological domain with a high-quality annotated dataset is what allows RADIX to generalize across species and imaging platforms. We train and evaluate it on the first expert-annotated benchmark of root anatomical structures at scale, comprising 1,695 high-quality fluorescence images spanning 17 monocot and dicot species, six anatomical structures, and three imaging platforms. RADIX segments all six structures at inter-annotator-level accuracy and generalizes to unseen species, genotypes, growth conditions, and an imaging platform from an independent laboratory. A single unified model surpasses monocot- and dicot-specialist models without sacrificing in-group accuracy. Predicted masks yield aerenchyma and suberin/lignin measurements matching expert annotation at ∼1.2 s per image with a single GPU, reducing weeks of manual analysis to minutes. Applying RADIX across genotypes, microbial treatments, and growth systems, we show that these cell type features form a coordinated, multidimensional, and context-dependent system shaped by genetic and environmental factors.

Why it matches plant phenotyping methods根の解剖学的構造を画像から自動抽出・定量する深層学習フレームワークを開発し、注釈付きベンチマークで検証しているため、植物フェノタイピング手法が中心である。

abstractQuantifying these structures at high resolution is a manual bottleneck that limits experimental scale.

Tracking Nano- and Microplastics in Plants: Uptake Pathways, Tissue Distribution, and Analytical Strategies from Microscopy to Spectroscopy. →

Nano- and microplastics (NMPs) are now widely detected across agroecosystems and can act as physiological stressors in plants. Exposure occurs through contaminated soil, irrigation water, or airborne deposition, bringing particles into direct contact with roots and above-ground tissues. Reported entry routes include apoplastic transport, cracks formed at lateral root emergence, leaf stomata, and endocytosis once particles have crossed the cell wall. Once internalized, particles may translocate through the xylem and, in some cases, the phloem, accumulating in roots, stems, and leaves depending on particle size, surface charge, and plant structural characteristics. NMPs have been associated with oxidative stress, disrupted photosynthesis, and altered metabolic pathways. Detecting NMPs within heterogeneous, hydrated plant tissues remains challenging, as particles often show low contrast against biological structures and can be mistaken for cellular components. This review examines how microscopy techniques reveal NMPs size, surface attachment, tissue distribution, and cellular-level interactions, while noting that these approaches primarily provide morphological or localization information rather than confirming polymer identity. Complementary spectroscopic and mass-based analytical methods are discussed for their role in chemical confirmation and quantification. This review supports informed selection among imaging, spectroscopic, and quantitative techniques for studying plant-plastic interactions, while highlighting current analytical challenges facing the field.

Why it matches plant phenotyping methods植物組織内の粒子サイズ・付着・分布・細胞相互作用を測定する顕微鏡、分光、質量分析手法を中心にレビューしており、植物状態の観測手法が主題である。

abstractThis review examines how microscopy techniques reveal NMPs size, surface attachment, tissue distribution, and cellular-level interactions

AI-enabled simultaneous phenotyping of leaf vein and stomatal traits uncovers independent genetic control in maize →

Abstract Background Leaves maintain hydraulic homeostasis during photosynthesis through the coordinated action of stomata, which regulate gas exchange and transpiration, and veins, which supply water to the leaf lamina. While functional links between stomatal and vascular traits are known in dicots, their potential genetic coordination in C4 crops remains poorly understood. We investigated the genetic architecture of these traits in maize using a Multi-parent Advanced Generation Inter-Cross (MAGIC) population and a low-cost, high-throughput phenotyping platform integrating leaf clearing, digital microscopy, artificial intelligence, and image analysis Results We phenotyped 285 recombinant inbred lines and the MAGIC founder lines, generating 8,072 images from 2,026 leaf samples taken from seedlings grown in controlled conditions. A YOLOv8-based model automatically detected stomata, while a custom and efficient image-processing pipeline quantified vein traits and stomatal spatial distribution patterns along cell bundles. This enabled simultaneous characterization of stomatal density, size, and distribution together with vein density, thickness, and bundle-associated spatial patterning. Substantial phenotypic variation was observed among genotypes, with strong correlations between abaxial and adaxial traits but no significant correlations between stomatal and vein traits. QTL mapping identified 37 genomic regions associated with stomatal and vein traits, including loci containing known developmental regulators such as stomatal density and distribution1 and stomagen1 , as well as novel loci controlling stomatal spatial patterns, divergence between leaf surfaces and veins traits. Conclusions These results support independent genetic control of stomata and veins and decoupled contribution to water-use efficiency, providing a novel genetic framework to independently optimize leaf hydraulic capacity and gas exchange in target environments.

Why it matches plant phenotyping methods葉の気孔・葉脈形質を自動画像解析で同時定量する高スループット表現型解析プラットフォームが研究の中心であり、形質抽出手法も具体的に記述されている。

abstractusing a Multi-parent Advanced Generation Inter-Cross (MAGIC) population and a low-cost, high-throughput phenotyping platform integrating leaf clearing, digital microscopy, artificial intelligence, and image analysis

Identifying and engineering the molecular origins of lignin color for predictive staining of plant tissues →

Lignins in plant biomass are carbon-negative aromatic biopolymers which hold tremendous potential as multipurpose resources for sustainable bioeconomy, limited only by their chemical heterogeneity. Plant lignified tissues, such as sapwood and seed coats, vary in colors within and between species, indicating that specific lignin topochemistries determine the different colors. Yet, the responsible lignin chromogen(s) are unknown. We developed chemical imaging using UV-Vis microspectroscopy to link lignin color to topochemistry in isolates and plant samples. Using synthetic and technical lignins, we identified the different stable chromogens as homomeric lignin substructures varying in size, unit chemistry and interunit linkages. We controlled the accumulation of specific lignin chromogens using genetic engineering to similarly stain lignified tissues from different plant species. We established plant tissue engineering to cast plant tissues with pre-determined color by adjusting lignin topochemistries. We proved that biotechnological manipulation of the identified lignin chromogens predictably and stably stains lignified plant tissues.

Why it matches plant phenotyping methodsUV-Visマイクロ分光法による化学イメージングを開発し、植物組織のリグニン由来色をトポケミーと関連付けて予測・操作する手法が研究の中心である。

abstractWe developed chemical imaging using UV-Vis microspectroscopy to link lignin color to topochemistry in isolates and plant samples.

Pixel-registered multimodal synchrotron XRF and FTIR microscopies reveal salinity stress response mechanisms in pistachio. →

Background Salinity is a major abiotic stress that negatively affects nearly all plant species at all stages of growth. Drought and poor-quality irrigation cause high soil salinity and salt accumulation via evaporation, reducing crop productivity. Despite its critical importance, the spatial localization of salt ions and associated biochemical changes within plants experiencing high salinity remains largely unknown. In this study, we developed a multimodal imaging pipeline to understand the impact of salinity on the pistachio rootstock UCB-1 (Pistacia atlantica x Pistacia integerrima). We directly link biochemical fingerprints in stem tissue architecture with salt ion localization to provide insights into the strategies pistachio uses to tolerate salinity. Results We observed that Pistacia spp. exposed to high salt conditions accumulated Ca, Si, Cl, Al and Mg as hotspots within the pith, compared to the control (of which only Ca and Al co-locate). In contrast, there was a decrease in K between the control and salinity treatment. Hotspots of amide I and II were present in the cortex and pith of the salinity treated sample. Additionally, the salinity treatment resulted in an increased abundance of pectin and carbohydrates within the pith compared to the control, and the abundance of esters/carboxylic acid was greater in the salinity treatment. Conclusions We determined that Cl and K, S and P, and biochemical components polysaccharide and pectin, esters and carboxylic acid, amide I and cellulose are the strongest drivers of salinity-treatment induced variability. In the cortex and phloem/xylem, a negative K-Ca correlation decreases in the salinity treatment. Several hotspots of elements and amide I (proteins) appear under salinity treatment, particularly in the cortex, suggesting an increase in the production of stress-related proteins (in response to high Cl) and/or structural proteins (i.e. Ca). Together, these results indicate that pistachio responds to salinity through ion compartmentalization coupled with a targeted biochemical adjustment, rather than a broadscale tissue-wide response. Overall, these novel, spatially resolved pixel-registered multimodal imaging data provide an enabling platform to understand the mechanisms of salinity tolerance in Pistacia spp and can be broadly applied to studying stress-related phenotype response in various plant tissues.

Why it matches plant phenotyping methods植物組織の元素・生化学状態を空間的に取得するピクセル登録型マルチモーダル画像パイプラインを開発し、植物ストレス表現型解析への汎用的プラットフォームとして提示しているため。

abstractwe developed a multimodal imaging pipeline to understand the impact of salinity on the pistachio rootstock UCB-1

Nano-flow liquid chromatography-mass spectrometry for highly sensitive quantification of indole-3-acetic acid from small tissue sections prepared by laser micro dissection. →

Plant hormones play critical roles in many aspects of plant life cycles including development, growth, reproduction and responses to environmental stimuli. These processes are often associated with changes in endogenous plant hormone levels and locations. Therefore, to understand the modes of action of plant hormones, it is important to accurately quantify these chemical compounds in a high-definition tissue map. In this study, we developed a system to quantify indole-3-acetic acid (IAA), the major endogenous auxin, from small tissue samples using laser microdissection (LMD) coupled with nano-flow liquid chromatography (nano-LC)-mass spectrometry (MS), which improved detection limits, allowing quantification of IAA from a single 10 μm cryosection of maize coleoptile. Our results reveal that IAA is actively synthesized in the apical 400 μm region of the coleoptiles and is preferentially accumulated in vascular tissues. This technique can provide a precise view of the spatiotemporal distribution of plant hormones and their significance in regulating physiological responses at tissue or cellular levels.

Why it matches plant phenotyping methods植物組織中のIAAの空間分布を高感度に定量するLMD-nano-LC-MS法そのものを開発しており、植物の生理状態を組織・細胞レベルで取得する技術が研究の中心である。

abstractIn this study, we developed a system to quantify indole-3-acetic acid (IAA), the major endogenous auxin, from small tissue samples using laser microdissection (LMD) coupled with nano-flow liquid chromatography (nano-LC)-mass spectrometry (MS)

Three-dimensional reconstruction reveals distinct endodermal network topology associated with root ion transport characteristics in balsa →

The endodermis plays a critical role in root function by regulating the movement of water and nutrients. Because endodermal function emerges from coordinated interactions among neighboring cells, the three-dimensional (3D) organization of cellular networks may influence how transport pathways are spatially arranged within root tissues. However, the 3D cellular network topology of the endodermis and its potential functional significance in woody plants remain poorly understood. Here, we combined light-sheet fluorescence microscopy (LSFM), 3D reconstruction, and network topology analysis to compare the endodermal cellular networks of two tree species, balsa (Ochroma pyramidale) and Eucalyptus robusta. We found that the balsa endodermis exhibits a distinct network topology characterized by higher local connectivity, lower closeness centrality, and lower edge betweenness centrality than that of Eucalyptus. Confocal Raman spectroscopy revealed broadly similar lignin and suberin signatures in the Casparian strip of the two species. Physiological measurements further showed that balsa roots exhibited significantly higher K + influx than Eucalyptus roots. Together, these observations indicate an association between variation in endodermal network organization and differences in root ion transport characteristics. This study highlights the value of integrating three-dimensional cellular reconstruction with network analysis to investigate structure-function relationships in plant tissues.

Why it matches plant phenotyping methodsLSFMによる3D細胞再構築とネットワーク解析が、根内皮の形態・構造特性を定量化する中心的手法として用いられているため、植物フェノタイピング手法の実質的応用に該当する。

abstractHere, we combined light-sheet fluorescence microscopy (LSFM), 3D reconstruction, and network topology analysis to compare the endodermal cellular networks of two tree species, balsa (Ochroma pyramidale) and Eucalyptus robusta.

Estimating Crop Nitrogen Uptake from UAV-Based Imagery Using Machine Learning Techniques →

Unmanned Aerial Vehicle (UAV)-based remote sensing using high-throughput spectral imaging has emerged as an effective non-destructive alternative for large-scale agricultural monitoring. This study evaluates the performance of UAV-based multispectral (MSI) and hyperspectral (HSI) imaging combined with machine learning for estimating in-season nitrogen uptake in spring wheat and canola. Field trials were conducted at irrigated and non-irrigated sites in southern and central Alberta, Canada, respectively, over three growing seasons (2023–2025). Coincident with ground-truth tissue sampling, aerial imagery was collected and processed to train and validate six machine learning models, using ~520 matchups per crop. All models successfully estimated nitrogen uptake across years and locations, although performance varied by sensor and data types. For canola, ANN produced the highest MSI-based accuracy (R2 = 0.83, RMSE = 0.5%), whereas HSI data improved prediction performance, with SVR achieving the best results (R2 = 0.90, RMSE = 0.40%). In wheat, ANN yielded the highest accuracy for both MSI and HSI data (R2 = 0.77, RMSE = 0.54% for MSI; R2 = 0.8, RMSE = 0.48% for HSI). These findings demonstrate that UAV-based spectral imaging combined with machine learning provides a reliable and scalable approach for non-destructive nitrogen uptake estimation. Although MSI sensors produced strong predictive performance, the enhanced spectral resolution of HSI data consistently improved estimation accuracy for both crops across varied growing conditions.

Why it matches plant phenotyping methodsUAVマルチスペクトル・ハイパースペクトル画像と機械学習により、作物の窒素吸収量という植物形質を推定し、複数モデル・センサーの性能を評価しているため、フェノタイピング手法が中心である。

abstractThis study evaluates the performance of UAV-based multispectral (MSI) and hyperspectral (HSI) imaging combined with machine learning for estimating in-season nitrogen uptake in spring wheat and canola.

Hijacked hydraulics: Verticillium dahliae-induced xylem dysfunction in pepper stems revealed by integrated hydraulic, imaging, and molecular analyses. →

Xylem tissue enables efficient long-distance water transport but is a primary target for vascular pathogens. This study investigates how systemic invasion by Verticillium dahliae impairs the hydraulic function of pepper (Capsicum annuum) plants, focussing on xylem colonisation and its anatomical and physiological effects. Real-time sap flow was continuously monitored with custom-built ExoBeat sensors, while periodic stem water potential measurements allowed calculation of changes in stem hydraulic conductance as an additional indicator of xylem performance. Fungal colonisation was assessed by quantitative polymerase chain reaction, and vessel occlusions and embolised conduits were visualised using scanning electron microscopy and micro-computed tomography, complemented by direct hydraulic conductivity measurements. By 14 d post inoculation, V. dahliae had progressed from roots to aboveground tissues, coinciding with a marked decrease in sap flow, water potential, and soil-to-stem hydraulic conductance, alongside the onset of dwarfing. Direct fungal blockage and anatomical changes were the primary contributors to hydraulic dysfunction. Vessel occlusion by tyloses, gels, and air embolisms played a negligible role. This study reveals how V. dahliae progressively impairs pepper hydraulics through systemic xylem colonisation, highlighting the value of real-time sap flow monitoring. Our integrative, multidisciplinary approach offers a powerful framework to unravel the complexity of dynamic plant-fungal vascular interactions.

Why it matches plant phenotyping methodsカスタムセンサーによるリアルタイム・サップフロー測定を中心に、植物の水理機能・病原体による機能低下を定量化しており、単なる生物学的測定にとどまらない実質的なフェノタイピング手法の適用である。

abstractReal-time sap flow was continuously monitored with custom-built ExoBeat sensors

Integrating UAV-based dynamic phenotyping and GWAS to decipher the genetic basis of cotton defoliation →

Upland cotton (Gossypium hirsutum L.) is a critical economic crop, yet the efficiency of mechanized harvesting is heavily contingent upon effective pre-harvest defoliation. Traditional manual assessment of defoliation is labor-intensive and subjective, posing a significant bottleneck for large-scale genetic dissection of this dynamic trait. In this study, we established an integrated “high-throughput phenotyping-to-gene discovery” framework by utilizing UAV-based multispectral imaging to monitor 306 cotton cultivars across 4 environments. A Partial Least Squares Regression (PLSR) model was optimized to accurately estimate Leaf Area Index (LAI), and Gaussian curve fitting was employed to standardize LAI time series (ΔLAI) into a comparable dynamic phenotypic dataset. Genome-wide association studies (GWAS) based on these dynamic phenotypes identified 472 significant SNPs and 39 candidate genes. By integrating GWAS signals with transcriptome profiling of the petiole abscission zone and haplotype analysis, we identified 3 core regulatory genes: Ghi_A01G08401 (GhPIN3a), Ghi_D08G10716, and Ghi_D11G03091. Functional validation via virus-induced gene silencing (VIGS) and qRT-PCR demonstrated that Ghi_D08G10716 (encoding oxalyl-CoA synthetase) and Ghi_D11G03091 (encoding a VQ motif-containing protein) act as negative regulators in the defoliation process. These results provide a scalable technical paradigm and critical genetic resources for the precision breeding of cotton cultivars optimized for mechanized harvesting.

Why it matches plant phenotyping methodsUAVマルチスペクトル画像からLAIを推定し、時系列を動的表現型データへ変換する高スループット表現型解析手法が研究の中心であり、GWASへの実質的適用も行っている。

abstractwe established an integrated “high-throughput phenotyping-to-gene discovery” framework by utilizing UAV-based multispectral imaging to monitor 306 cotton cultivars across 4 environments.

Hyperspectral Imaging for Crop Disease Detection: A Systematic Literature Review and Research Gap Analysis →

Crop diseases cause 20-40% of food losses every year and cause economic damage of more than USD 220 billion per year on a global scale. The basic problems in precision agriculture remain the same as early and accurate disease detection. Hyperspectral imaging (HSI) is a type of imaging technique that captures hundreds of contiguous wavelengths of the electromagnetic spectrum spanning from 400 to 2500 nm that has been found to be a useful non-destructive diagnostic tool that can detect the subtle biochemical differences that occur in plant tissue before symptoms are visible. The paper critically summarizes and reviews the literature from 2000 to 2024, especially focusing on the application of AI and machine learning (ML) for HSI-based crop disease detection. A total of 48 primary studies are reviewed and grouped into five thematic categories: (1) spectral vegetation index methods, (2) classic machine learning classifiers, (3) deep learning architectures, (4) attention and transformer mechanisms and (5) disease severity quantification. Based on this review, four gaps in the literature are identified: (1) lack of comparison of classical and deep learning models on the same splits of the same datasets, (2) underutilisation of the SWIR-2 spectral range (>2000 nm) for the discrimination of diseases, (3) lack of integrated spatial mapping of the disease severity from spectral index fusion, and (4) lack of lightweight deep learning spectral-only architectures for field deployment in resource-constrained environments. These gaps together form a promising research program based on this AI approach to automated crop disease detection, and the experimental research work reported in our companion paper is fueled by these gaps.

Why it matches plant phenotyping methods植物病害の症状・重症度をハイパースペクトル画像とAIで推定する手法を対象とした体系的レビューであり、植物フェノタイピング手法のレビューが中心。

abstractHyperspectral imaging (HSI) is a type of imaging technique that captures hundreds of contiguous wavelengths of the electromagnetic spectrum spanning from 400 to 2500 nm that has been found to be a useful non-destructive diagnostic tool that can detect the subtle biochemical differences that occur in plant tissue before symptoms are visible.

Quantitative light element profiling in plant tissues with monochromatic X-ray fluorescence analysis: a new frontier for abiotic stress studies. →

Determining elemental concentrations in plant tissues is essential for physiological studies on abiotic stress. However, high-throughput routine analysis of light elements (sodium to calcium) in plants is challenging due to the need for complete sample dissolution and expensive and time-consuming inductively coupled plasma-mass-spectrometry (ICP-MS). Ion chromatography and ion-selective electrodes are low-cost methods but suffer from major drawbacks, including limited throughput and time-consuming sample preparation. This study reports on a new methodology for quantitative analysis of light elements in plants using monochromatic X-ray fluorescence (MXRF) analysis. We quantitatively assessed sodium and potassium uptake in Arabidopsis thaliana, Oryza sativa and Lactuca sativa in salinity treatments. The new method provides reliable results from samples as small as 1 mg, making it suitable for analysis at the seedling stage. This is enabled by the high sensitivity of the system and optimized sample preparation that ensures sufficient signal even at low sample masses. We tested the accuracy and precision of the technique for other light elements to demonstrate its broad applicability. The results show that the method delivers rapid, non-destructive, and extraction-free light element analysis on small samples highly correlating with ICP-MS. The monochromatic XRF method provides accurate measurements and reproducible results for studying salinity tolerance ideally suited for investigating elemental composition of early plant developmental stages, offering new possibilities for research into early stimuli responses.

Why it matches plant phenotyping methods植物組織中の元素濃度という生理形質を測定するMXRF法の開発と、ICP-MSとの相関、精度・再現性評価が研究の中心であるため。

abstractThis study reports on a new methodology for quantitative analysis of light elements in plants using monochromatic X-ray fluorescence (MXRF) analysis.

Advancing the pneumatic method to assess xylem vulnerability to embolism among distinct growth forms. →

Drought-driven plant mortality is closely linked to xylem embolism. Building useful, reliable datasets of xylem vulnerability to embolism requires methods that are practical, fast, accurate, widely accessible and robust across growth forms. We tested and advanced the pneumatic method for constructing xylem vulnerability curves (VCs) across contrasting growth forms to improve inference of drought resilience. Using an automated pneumatron, VCs were constructed for three species representing a small woody shrub (Erica monsoniana), a large woody shrub (Protea repens), and a reed-like graminoid (Cannomois congesta). For graminoid culms, we compared three approaches for estimating xylem water potential (Ψ) and developed a non-invasive method that couples repeated relative water content (RWC) measurements with Ψ-RWC models to obtain high-temporal Ψ estimates. Percent air discharged (PAD)-Ψ relationships were well captured by sigmoid functions. Cannomois congesta showed the steepest curves and the least negative thresholds overall (P 50 = -2.91 ± 0.09 MPa), indicating early, rapid embolism progression, whereas Erica monsoniana was most resistant (P 12 = -5.91 ± 0.74 MPa; P 50 = -6.78 ± 0.76 MPa) with higher variability; Protea repens was intermediate. P 50 estimates were the most comparable with prior optical, pneumatic and centrifuge estimates, whereas P 12 and P 88 showed greater divergence. Ψ TLP was less variable between species, but ranked similarly (-1.49 ± 0.03, -1.53 ± 0.03, -1.59 ± 0.02 MPa for C. congesta, P. repens, and E. monsoniana, respectively). Such variation yielded systematically wider hydraulic safety margins for the three species. By demonstrating that the pneumatic method can generate reliable vulnerability curves across small and large woody shrubs and graminoids, this study broadens the comparative evaluation of xylem vulnerability across growth forms with contrasting anatomy. A practical advance is the use of repeated RWC measurements paired with Ψ-RWC relationships to improve Ψ resolution in graminoid culms while minimizing disturbance.

Why it matches plant phenotyping methods植物の木部キャビテーション脆弱性を測定する空気圧法を改良・比較検証し、反復RWC測定による非侵襲的な水ポテンシャル推定も開発しているため、植物生理形質の取得法が研究の中心です。

abstractWe tested and advanced the pneumatic method for constructing xylem vulnerability curves (VCs) across contrasting growth forms to improve inference of drought resilience.

Drought adaptation in spring wheat seedlings relies on coordinated deep root architecture and cortical tissue allocation. →

Introduction: Root anatomical traits and spatial architecture play a critical role in crop water acquisition and utilization, directly impacting drought tolerance. However, comprehensive studies examining the synergistic effects of deep root configuration and cortical tissue organization under drought stress during the seedling stage remain scarce. Additionally, the underlying physiological mechanisms are not yet well understood. Methods: In this study, we utilized a high-throughput, paper-based phenotyping platform to simulate drought stress using 10% PEG. An efficient, multi-trait evaluation framework was employed to classify the 28 tested genotypes into five drought tolerance categories. Results: This approach enabled the identification of drought-tolerant cultivars "Ruichun 1," "Ningchun 11," and "Ningchun 57," as well as the drought-sensitive cultivar "Dingxi 48." Root traits, including maximum depth, convex hull area, and plant height, demonstrated strong explanatory power and could serve as valuable phenotypic indicators for seedling stage screening. Our findings suggest that drought adaptation in spring wheat involves a strategic coupling in which specific cortical configurations facilitate the development of deep root architecture. While previous studies have often focused on individual parameters, we show that drought-tolerant genotypes optimize root growth in deeper segments of the growth medium by adjusting cortical tissue proportions, potentially minimizing metabolic costs. Discussion: This integrated perspective offers a detailed physiological framework for understanding drought resilience and moves toward a mechanism-based interpretation of resource reallocation. However, it is important to note that these results were obtained using a paper-based phenotyping platform under PEG-induced osmotic stress, reflecting the genotypic potential at the seedling stage rather than actual field drought tolerance. In conclusion, combining the paper-based high-throughput phenotyping platform with a multi-trait evaluation framework allows for the accurate classification of drought tolerance types and the efficient identification of representative spring wheat cultivars. The findings emphasize the importance of deep root configuration and optimized cortical allocation as fundamental components of the root structural basis for drought adaptation in spring wheat. These results provide clear phenotypic targets for early-stage screening, which should be further validated at later developmental stages and under field conditions before being applied in breeding programs.

Why it matches plant phenotyping methods紙ベースのハイスループット表現型解析プラットフォームと多形質評価フレームワークが、根形態を用いた耐乾性分類の中心的手法として明示されているため。

abstractwe utilized a high-throughput, paper-based phenotyping platform

One-year-old wood morphology and colorimetric indicators of cold hardiness in 'Frontenac' and 'Prairie Star' grapevines. →

Cold hardiness is a critical trait for grapevine survival and productivity in cold climates. This study examined the relationships among cane morphological characteristics, shoot color parameters, and cold hardiness in two grapevine cultivars ('Prairie Star' and 'Frontenac') across four dormant-season sampling times (ST 1-ST 4) and three internode diameter classes (small, normal, and large). Morphological traits, including internode length, shoot diameter, and cross-sectional area, did not show a consistent temporal trend across sampling periods, suggesting that the observed variation was primarily associated with sampling time and cane class rather than progressive structural change during dormancy. In contrast, colorimetric traits showed a clear seasonal pattern, with shoots becoming darker and redder from ST 1 to ST 4, consistent with advancing lignification and cane maturation. Cold hardiness, assessed using low-temperature exotherms of bud, phloem, and xylem tissues, increased substantially from early to mid-dormancy, with xylem tissues reaching the greatest freezing tolerance by ST 3-ST 4. 'Prairie Star' showed slightly greater xylem cold hardiness than 'Frontenac', while bud survival remained consistently high across all treatments. Strong associations between shoot color and LTE values indicate that color traits, particularly at the fifth internode, may serve as reliable non-destructive indicators of cold hardiness status. Sampling time was the primary source of multivariate variation, with cultivar and internode class contributing secondary effects. These findings demonstrate that observable cane traits, especially shoot color, reflect the progression of seasonal cold acclimation and may support the evaluation and selection of cold-hardy grapevine germplasm.

Why it matches plant phenotyping methods枝の色・形態を用いてブドウの耐寒性を非破壊推定する指標として評価しており、単なる生物学的測定ではなく表現型取得法の妥当性評価が中心です。

abstractStrong associations between shoot color and LTE values indicate that color traits, particularly at the fifth internode, may serve as reliable non-destructive indicators of cold hardiness status.

3D Reconstruction of Mature Arabidopsis Ovules Using FIB-SEM to Study Filiform Apparatus Morphology →

Volume electron microscopy based on serial sectioning allows for three-dimensional (3D) visualization and analysis of the internal structures of tissues, cells, and organelles. One such technique, focused ion beam (FIB) scanning electron microscopy (SEM), has the advantages of nanoscale sectioning and high z-resolution, but the disadvantage of limited volume processing. Because of this limitation, targeting localized objects by FIB-SEM is difficult. Here, we developed a FIB-SEM observation workflow that enables the analysis of the filiform apparatus of synergid cells enclosed in the Arabidopsis ovule. In this protocol, plant samples are stained, embedded, trimmed, and carbon-coated while maintaining their orientation within the tissue. Then, sequential observations are performed using Cut & See function of FIB-SEM, followed by image processing for 3D reconstruction. Utilization of multi-scanning and image cropping from high-resolution data helps to identify localized targets within plant tissue. The filiform apparatus, which is an invaginated cell wall structure of the synergid cells, shows distinct contrast in each image, allowing for segmentation using brightness-based binarization. Such segmentation avoids the need to manually trace complex structures and facilitates 3D reconstruction by volume electron microscopy. Key features • Sampling and trimming of the resin block enable directionally loading in FIB-SEM. • Multi-scanning by FIB-SEM and target extraction by image processing software enable 3D reconstruction of local areas within the sample block. • Binarization using distinctive brightness of cellular structures enables segmentation without manual tracing of complex structures such as the filiform apparatus cell wall.

Why it matches plant phenotyping methods植物組織内の構造をFIB-SEMと画像処理で3D再構成・セグメンテーションするワークフローを開発しており、フィリフォーム装置形態という植物器官形質の取得が中心である。

abstractHere, we developed a FIB-SEM observation workflow that enables the analysis of the filiform apparatus of synergid cells enclosed in the Arabidopsis ovule.

An ESIPT-AIE nanosensor for ONOO - imaging: decoding heavy metal stress and ferroptosis in living plants. →

Peroxynitrite (ONOO - ) serves as a critical redox signaling molecule in plant stress responses and ferroptosis, yet real time monitoring within complex plant matrices remains challenging. To address this, we synthesized a ratiometric nanosensor (DA) through molecular self-assembly. The DA particles (258 nm in diameter) exhibited enhanced sensitivity driven by an excited-state intramolecular proton transfer (ESIPT)-triggered restricted intramolecular motion mechanism, resulting in distinctive aggregation-induced emission (AIE) behavior. This nanoscale configuration improved tissue penetration and eliminated the aggregation-caused quenching (ACQ) effect commonly observed in traditional rhodamine derivatives. Meanwhile, the DA probe featured a large Stokes shift of 167 nm and an ultra-low limit of detection (LOD) of 6.4 nM. Leveraging these optical advantages, the nanosensor enabled real-time visualization of ONOO - dynamics in plant tissues and quantitative assessment of ONOO - accumulation under cadmium (Cd 2+ ), sodium chloride (NaCl), and erastin induced stress. This work represents the first application of an ESIPT-AIE hybrid probe for ONOO - detection in plants, providing a powerful analytical platform for elucidating oxidative stress mechanisms and advancing strategies to enhance crop resilience.

Why it matches plant phenotyping methods植物組織内の酸化ストレス状態を可視化・定量する新規ナノセンサーを開発し、植物ストレス下で検証しており、表現型状態の取得法が中心である。

abstractwe synthesized a ratiometric nanosensor (DA) through molecular self-assembly.

Predictive models for phenotyping and classification of wheat cultivar viability. →

Given the global importance of wheat cultivation in the agricultural landscape, the practicality of the tetrazolium test in post-harvest management of seed lots, and the significant increase in the use of technologies in agriculture, this work aimed to evaluate predictive models for high-efficiency phenotyping and classification of the viability of different commercial wheat cultivars using the tetrazolium test. The predictive models proved accurate in estimating the viability of the 50 seed lots, reaching over 90% viable seeds, depending on the wheat cultivar. The recommended tetrazolium salt solution concentrations were 0.125% for the BRS 264 cultivar, 0.1% for MGS Brilhante and BRS 404, and 0.075% for TBIO DUQUE and BRS 394, with a pre-conditioning period of 9 h, regardless of the cultivar. Correlations between the percentage of viable seeds obtained by the tetrazolium test and physiological vigor variables were statistically significant, serving to validate each chosen predictive model, as well as to rank the seed lots by cultivar. Through computational phenotyping of over 10,000 seed images, and subsequently, individual digital analyses of the respective embryonic tissues, the cultivars BRS 264, TBIO DUQUE, and BRS 404 were classified into four viability classes, and MGS Brilhante and BRS 394 into three classes. Therefore, predictive models, specific to each cultivar, associated with the tetrazolium test and image analysis resources, represent significant advances for decision-making regarding the implementation or post-harvest management of wheat crops, especially cultivars planted under different climates and regions.

Why it matches plant phenotyping methods小麦種子画像とテトラゾリウム試験を用いて、生存性を推定・分類する予測モデルを開発し、相関で検証しており、植物表現型取得・抽出法が研究の中心である。

abstractthis work aimed to evaluate predictive models for high-efficiency phenotyping and classification of the viability of different commercial wheat cultivars using the tetrazolium test.

Phase-contrast microtomography unveils mechanisms of root colonization by a vascular fungal pathogen →

Soil-borne vascular pathogens pose serious threats to agriculture with complex invasion strategies that remain poorly characterized compared to foliar pathogens. While foliar pathogens like Magnaporthe oryzae employ specialized appressoria to penetrate plant surfaces through a combination of mechanical force and enzymatic degradation, the invasion mechanisms of vascular pathogens that lack classical appressoria have remained largely theoretical. The nanoscale processes governing root penetration and colonization by these pathogens are particularly challenging to visualize due to technical limitations of conventional microscopy. Here we show, using phase-contrast X-ray computed microtomography and advanced microscopy, that Fusarium oxysporum (Fo) employs distinct mitogen-activated protein kinase (MAPK) cascades to orchestrate root invasion through unprecedented morphological plasticity. We identify previously undocumented appressoria-like structures that facilitate physical penetration, while demonstrating that Fo exhibits remarkable cellular adaptability, reducing hyphal diameter by more than 20-fold (from 5 μm to 220 nm) to navigate confined plant spaces, a dramatic morphological transition previously thought impossible. By using cellulase-deficient mutants, we demonstrate that cellulolytic activity is dispensable for surface breach and submicrometric hyphal colonization, establishing that mechanical force generation rather than enzymatic degradation is the primary determinant of successful host penetration. Three-dimensional reconstruction reveals a quantitative correlation between fungal proliferation and progressive embolism formation, with distinct MAPK pathways differentially regulating penetration force generation (Fmk1), osmotic adaptation during apoplastic colonization (Hog1), and directional growth toward vascular tissues (Mpk1). These findings provide a mechanistic framework for vascular wilt pathogenesis and reveal potential targets for controlling these economically devastating plant diseases.

Why it matches plant phenotyping methods位相コントラストX線マイクロトモグラフィーと3次元再構成を中核に、根の侵入・菌糸形態・塞栓形成という植物の病態と形態を定量化しており、病理学的機構研究であるものの表現型取得法の適用が実質的です。

titlePhase-contrast microtomography unveils mechanisms of root colonization by a vascular fungal pathogen

Machine learning-enabled implantable plant biomarker sensor for early detection and classification of acid and salt stress. →

Abiotic stresses, particularly acid and salt stress, severely limit plant productivity. Conventional detection is often hindered by physiological lags and phenotypic latency. Here, we develop a machine learning-enabled implantable plant biomarker sensor (MLIPBS) for early stress diagnosis. Featuring a foldable design, MLIPBS enables conformal integration into plant tissues for continuous monitoring of H 2 O 2 , K + , and pH. We confirm the robust sensing capabilities and favorable biocompatibility of MLIPBS through cross-species validation in lettuce, tomato, and Aloe vera. Additionally, leveraging the LightGBM architecture, we demonstrate that MLIPBS successfully classifies combined stress conditions and varying intensity levels of acid and salt stress, achieving an average accuracy of 90.5%. We further show that the system identifies stress types and intensities within 8 hours of onset, providing an early-warning window at least 48 hours before symptom manifestation. Our study provides reliable wearable tools for stress-resistant crop screening and precision management in smart agriculture.

Why it matches plant phenotyping methods植物組織内の生体指標を連続測定し、ストレスの種類・強度を分類するセンサーと機械学習システムの開発・検証が中心であり、植物ストレス状態のフェノタイピング手法に該当する。

abstractHere, we develop a machine learning-enabled implantable plant biomarker sensor (MLIPBS) for early stress diagnosis.

Detection and Quantification of Dysprosium in Plant Tissues. →

The growing demand for rare-earth elements (REEs), particularly dysprosium (Dy), underscores the need for sustainable extraction methods. Recovery of Dy, particularly from geographically distributed waste sources, is challenging. This gap positions phytomining, a technique using plants to accumulate metals, as a promising alternative. However, plant species differ in their ability to accumulate metals in high concentrations, necessitating efficient screening methods. In this study, we developed a high-throughput fluorescence-based assay to detect and quantify Dy uptake in plant tissues. The Dy detection method described in the present work exploits Dy's unique spectroscopic properties for sensitive and efficient analysis, enabling the detection of concentrations as low as 0.07 μM, with a detection limit of 0.2 μM in a plant matrix. By incorporating sodium tungstate (Na 2 WO 4 ) as a fluorescence enhancer, we achieved robust emission intensities at 480 and 580 nm, facilitating Dy quantification in complex plant matrices. Additionally, the use of time-resolved fluorescence techniques reduces background autofluorescence from plant tissues, enhancing signal specificity. Validation of the fluorescence method with inductively coupled plasma mass spectrometry (ICP-MS) demonstrated a strong correlation in Dy levels. Greenhouse trials confirmed the method's utility for screening Dy accumulation in living plants and highlighted the potential for rapid stand-off detection. This fluorescence-based approach offers a scalable, efficient tool for identifying Dy-accumulating plants and advances phytomining as a sustainable strategy for REE recovery.

Why it matches plant phenotyping methods植物組織中のDy蓄積という植物状態を蛍光センサーで定量する高スループット手法を開発し、ICP-MSで検証しており、表現型取得法が中心である。

abstractIn this study, we developed a high-throughput fluorescence-based assay to detect and quantify Dy uptake in plant tissues.

How stochastic cell fate and endoreduplication yield non-random epidermal patterns. →

Pavement cells in the Arabidopsis thaliana epidermis span a wide range of sizes and ploidy levels, but rules that generate this heterogeneity across an organ remain unclear. Clark et al. identify a shared genetic pathway that promotes large, polyploid pavement cells in both sepals and leaves, then ask whether the familiar "scattered" distribution of giant cells is truly random. By combining whole-tissue imaging with two independent computational randomization approaches that regenerate tissues from segmented images while preserving cell size distributions and key boundary constraints, together with a stochastic cell-autonomous model, the authors show how an initially random pattern can later appear clustered relative to a changing random baseline as tissues grow and subdivide. The study provides a quantitative framework for testing spatial organization in cellular mosaics where point-based methods fail, and it shows how proliferation history can convert early stochastic fate decisions into a statistically non-random mature pattern.

Why it matches plant phenotyping methods全組織イメージングと、セグメンテーション画像を用いた独立な計算的ランダム化・確率モデルを組み合わせ、植物組織の細胞サイズ・倍数性・空間パターンを定量解析する枠組みが研究の中心である。

abstractBy combining whole-tissue imaging with two independent computational randomization approaches that regenerate tissues from segmented images while preserving cell size distributions and key boundary constraints, together with a stochastic cell-autonomous model

LipoTag: A minimal motif for live and functional imaging of plant cell membranes →

The plant plasma membrane is a highly dynamic structure that is crucial for cell compartmentalization, the maintenance of (bio)chemical gradients, signaling and cell growth and responses to stress. In plants, plasma membranes are tightly connected to the cell walls that encase them. These cell walls can act as diffusion barriers and prevent the use of a wide range of synthetic fluorescent probes that have been developed to study animal cell membranes, which lack a cell wall, with live functional imaging. Here, we introduce LipoTag, a minimal chemical motif that, upon chemical conjugation, transforms hydrophobic fluorophores into water-soluble, membrane-targeted probes that can permeate plant cell walls to reach their intended location. LipoTag uses a localized positive charge in combination with a short aliphatic spacer to direct cargo to the plasma membrane. We used LipoTag to develop a suite of membrane-specific fluorescent probes that work in walled organisms beyond the plant kingdom. In addition, we used LipoTag to develop functional reporters for the quantitative imaging of membrane density, lipid order and membrane oxidation in living plant tissues. LipoTag forms a modular platform for exploring the plant plasma membrane with a suite of contemporary imaging modalities.

Why it matches plant phenotyping methods植物細胞膜を対象とした蛍光プローブと機能レポーターを開発し、生体植物組織で膜密度・脂質秩序・膜酸化を定量画像化する方法を提示しており、表現型取得法が中心である。

abstractHere, we introduce LipoTag, a minimal chemical motif that, upon chemical conjugation, transforms hydrophobic fluorophores into water-soluble, membrane-targeted probes that can permeate plant cell walls to reach their intended location.

Systematic Investigation of Microstructural and Spectral Characteristics in Citrus Midrib for Huanglongbing Detection. →

Citrus Huanglongbing (HLB) disease is a devastating disease faced by the global citrus industry, for which there is currently no effective cure. This study systematically investigated the anatomical characteristics and infrared spectral properties of different microstructures (phloem, xylem, pith, and cortical tissues) in the midribs of healthy and HLB-infected citrus leaves. Scanning electron microscopy observations revealed obvious phloem breakage and massive starch granule accumulation in various tissues of HLB-infected samples. Using micro-Fourier transform infrared spectroscopy, the spectral acquisition parameters were optimized (slice thickness: 10 μm, spectral resolution: 8 cm -1 , spatial resolution: 10 μm × 10 μm, number of scans: 256), and in-situ spectral information from different tissues were obtained. The results showed significant changes in the intensity and position of absorption peaks in the fingerprint region (1,800 to 675 cm -1 ) of all tissues after HLB infection, particularly enhanced carbohydrate absorption at bands such as 1,099, 1,060, and 1,033 cm -1 , indicating that abnormal carbohydrate accumulation is a typical symptom of HLB. A principal component analysis score plot based on spectral data from the phloem demonstrates a clear spatial separation trend between healthy and HLB-infected samples, providing a theoretical basis and methodological support for the fast, early, nondestructive detection of citrus HLB disease.

Why it matches plant phenotyping methodsミクロFTIRの取得条件を最適化し、健全・HLB感染葉の組織スペクトルから病害状態を識別する手法を検討しており、植物病徴の非破壊フェノタイピングが中心である。

abstractUsing micro-Fourier transform infrared spectroscopy, the spectral acquisition parameters were optimized (slice thickness: 10 μm, spectral resolution: 8 cm -1 , spatial resolution: 10 μm × 10 μm, number of scans: 256), and in-situ spectral information from different tissues were obtained.

In situ detection of methyl jasmonate using plant-wearable sensors to quantify genotype-dependent herbivory resistance. →

Methyl jasmonate (MeJA) is a key phytohormone regulating plant responses to herbivory and environmental stress. While conventional analytical techniques, such as liquid chromatography-mass spectrometry, provide high accuracy, their application is often limited by labor-intensive workflows, high costs, and complex sample preparation requirements. In this study, we present a wearable electrochemical sensor for the in situ monitoring of MeJA in maize (Zea mays L.) under fall armyworm (FAW; Spodoptera frugiperda [J.E. Smith]) herbivory. The sensor employs an array of microneedles functionalized with a MeJA-specific molecularly imprinted polymer (MIP). This work presents the in situ monitoring of MeJA levels within intact plant tissues using a MeJA-specific MIP integrated with a microneedle-based sensor, and demonstrates, for the first time, the use of a plant-wearable sensor to quantify genotype-dependent herbivory resistance. The sensor exhibited considerable sensitivity and selectivity, with a detection limit of 0.18 μM. Sensor performance was validated in four maize genotypes with varying levels of resistance to FAW (Mp708, BS39:0043, Tx601, GEMN0131). Time-course measurements revealed that resistant genotypes exhibited earlier and stronger MeJA induction following infestation, whereas susceptible genotypes showed delayed and attenuated responses. Sensor measurements demonstrated a strong correlation with conventional measurement data. Statistical analysis using a randomized complete block design confirmed that genotype, detection methodology, and infestation status significantly influence MeJA variability. These findings highlight the potential of the present wearable sensor as a powerful tool for studying plant defense mechanisms and advancing precision agriculture through direct monitoring of phytohormonal signaling.

Why it matches plant phenotyping methods植物体内のホルモン状態を測定するウェアラブル電気化学センサーを開発し、複数遺伝子型で性能検証・従来法との相関評価を行っており、表現型取得手法が研究の中心である。

abstractwe present a wearable electrochemical sensor for the in situ monitoring of MeJA in maize (Zea mays L.) under fall armyworm (FAW; Spodoptera frugiperda [J.E. Smith]) herbivory.

In-situ measurements of dissolved gases in tree xylem sap as tracers for plant physiology →

Common hydrogeological methods make use of natural gases as tracers to better understand the spatial and temporal evolution of groundwater flow, to constrain water residence time, and to reconstruct environmental conditions at recharge [1-3]. Noble gases can be used as complement of the stable water isotope tracers for understanding complex hydrological systems [4,5,6].We adapted these methods to in-situ measurements of gases in tree xylem sap to better understand the plant-mediated water and gas flux between the hydrosphere, the biosphere, and the atmosphere. Using a “miniRuedi” portable mass-spectrometer [7] and tailored semi-permeable membrane probes, the partial pressures of He, Ar, Kr, N2, O2, CO2, and CH4 were continuously monitored in-situ in the soil, the tree, and the atmosphere. Diurnal variations of CO2 and O2 were observed that reflected the tree physiological activities [8]. Since transpiration by plants is a major component of the hydrological cycle, such measurement techniques offer new opportunities to better understand plant water and CO₂ dynamics, within the soil-plant-atmosphere continuum.[1] Kipfer et al. (2002), Reviews in Mineralogy and Geochemistry, 47, 615–700; [2] Brennwald et al. (2013), Advances in Isotope Geochemistry – The Noble Gases as Geochemical Tracers, 123-153; [3] Brennwald et al. (2022), Frontiers in Water, 4, 107-115; [4] Althaus et al. (2009), Journal of Hydrology, 370, 64-72. [5] Schilling et al. (2019), Reviews of Geophysics, 57, 146-182. [6] Xu et al. (2017). Hydrogeology Journal, 25(7), 2015–2029; [7] Brennwald et al. (2016), ES&T, 50, 13455-1346; [8] Marion et al. (2024), Tree Physiology, tpae062.

Why it matches plant phenotyping methods植物の木部樹液中ガスを測定する携帯型質量分析計と膜プローブを適応し、植物生理活動や水・CO₂動態を連続的に取得する測定法が研究の中心である。

abstractWe adapted these methods to in-situ measurements of gases in tree xylem sap to better understand the plant-mediated water and gas flux between the hydrosphere, the biosphere, and the atmosphere.

Simulation and prediction of post-harvest ripening processes for tomatoes with different ripeness levels based on electrical characteristics. →

Detecting postharvest tomato ripeness is essential for quality control. To reveal the evolution of complex conductivity σ ∗ and complex permittivityε ∗ during tomato ripening, this study integrates bioimpedance spectroscopy (BIS) and finite element method (FEM) to predict postharvest tomato maturity. Based on the Maxwell-Wagner equation, σ ∗ and ε ∗ were derived from the measured impedance and conductance data. BIS measurements were conducted on whole tomatoes at four ripening periods and their components (pericarp, chamber, core, cavity). A finite element model was implemented in COMSOL to simulate electrical field distribution and quantify tissue-specific differences. Continuous monitoring of white ripening period tomatoes was used to validate the model, yielding an average accuracy of 85.16%, peaking at 92.86% in red ripening period and dipping to 80.30% in color change period, elucidate the dynamic changes in electrical properties during tomato ripening and provide a basis for nondestructive maturity assessment.

Why it matches plant phenotyping methodsトマトの成熟状態を電気特性から非破壊推定するBIS・FEM手法を開発・検証しており、植物状態の取得・推定が研究の中心である。

abstractthis study integrates bioimpedance spectroscopy (BIS) and finite element method (FEM) to predict postharvest tomato maturity.

CryoFluorSEM – A new approach for fluorescence and EM imaging of cryofractured plant samples →

Abstract Cryo‐scanning electron microscopy (CryoSEM) permits the preparation and detailed imaging of bulky samples while keeping them in a hydrated state. For plant biology, cryofractures give information on cell ultrastructure and tissue organisation within a much larger context that is the whole organ or organism. To date, a method to locate fluorescence reporters on the cryofracture has not been reported. Our approach uses a stereofluorescence microscope with an 80 mm working distance and a high‐zoom ratio to image the fracture through a viewing port of the cryopreparation chamber while the sample is still frozen and under vacuum. We have applied this method to look at fluorescent reporters of auxin transport and signalling in plant shoot apices and seedlings, the expression of a poorly characterised gene in the young floral pedicel and nitrogen‐fixing rhizobial bacteria, expressing GFP, in root nodules. This method is applicable to any cryopreserved bulky sample that has a fluorescent output and paves the way for correlative light‐electron microscopy for cryoSEM‐based imaging.

Why it matches plant phenotyping methods植物試料の蛍光レポーターを凍結破断面上で位置特定・画像化する新規CryoFluorSEM法の開発であり、植物の構造・組織状態を取得する方法が中心である。

abstractTo date, a method to locate fluorescence reporters on the cryofracture has not been reported.

A non-destructive plant screening method for improving sample uniformity in horticultural crops based on a hydrogen peroxide fluorescent probe →

Introduction Hydrogen peroxide (H 2 O 2 ) functions as a key signaling molecule in plants responding to stress. Although numerous detection methods have been developed, simple and non-destructive techniques for the semi-quantitative monitoring of H 2 O 2 in plant tissues remain scarce. Methods In this study, we developed a "turn-on" fluorescent probe specifically designed to detect endogenous H 2 O 2 in plant tissues, and conducted spectroscopic and in vivo toxicity tests. Furthermore, under experimentally controlled stress conditions, we utilized this probe to detect H 2 O 2 levels in four distinct plant types exposed to salt, waterlogging, cadmium, and drought stresses. Additionally, H 2 O 2 was detected in a grafting model under non-experimentally controlled stress conditions. Results The results showed that the probe demonstrated excellent selectivity, a strong linear correlation (R2 = 0.9849), and a low detection limit of 0.6450 μmol/L. Importantly, it exhibits good biocompatibility with plant tissues and effectively minimizes detection errors caused by transient H 2 O 2 fluctuations induced by environmental changes. Consequently, it provides more accurate and stress-reflective H 2 O 2 measurements. Under experimentally controlled stress conditions, the changes in relative fluorescence intensity conformed to the typical response patterns observed when plants experience graded levels of stress. Notably, even under complex grafting conditions without imposed stress gradients, applying the probe to bottle gourd (Lagenaria siceraria) rootstocks with different graft compatibility produced fluorescence dynamics consistent with the typical H 2 O 2 responses of compatible and incompatible rootstocks, and the distribution of relative fluorescence intensity within the population underscored the importance of prescreening plants for biological studies. Pearson correlation and Bland-Altman analyses confirmed good agreement between our method and the commercial assay kit. Discussion These results demonstrate that the LWS probe enables H 2 O 2 detection and, in combination with the IVIS in vivo imaging system, can screen individual plants differing in stress responses more effectively than other sensors. This non-destructive approach preserves the structural integrity of plant samples, enabling follow-up physiological, biochemical, and genomic analyses on the same specimens. This method provides a reliable prescreening platform for investigating plant stress responses at the biological level.

Why it matches plant phenotyping methods植物組織中のH2O2を非破壊的・半定量的に検出する蛍光プローブとIVIS画像化を開発し、性能検証およびストレス応答個体のスクリーニングに応用しており、植物状態の取得手法が中心である。

abstractwe developed a "turn-on" fluorescent probe specifically designed to detect endogenous H 2 O 2 in plant tissues

A high-throughput fluorescence-based microplate reader assay to quantify total flavonol levels in plant tissues. →

Background Flavonols are plant specialized metabolites that regulate plant growth, development, and stress responses. Due to their antioxidant activity, they also confer nutritional benefits to human health. Quantification of flavonols in plant tissues typically relies on chromatographic methods such as HPLC or LC-MS, or on microscopy-based approaches using diphenylboric acid 2-aminoethyl ester (DPBA) staining to visualize flavonols in plant tissues. These methods are time-consuming and resource intensive. Here, we present a rapid, high-throughput, fluorescence-based microplate reader assay for flavonol quantification, in which the flavonol-specific dye DPBA is added to plant extracts to form fluorescent complexes. Results The assay was optimized for extraction efficiency and validated for sensitivity, accuracy, and reproducibility. It also shows consistency with HPLC measurements. We demonstrate its utility by quantifying flavonol levels in different tomato tissues, across different cultivars, and even between plant species. Our assay showed that reproductive tissue in tomato plants has higher flavonol levels than vegetative tissue. Also, we found variation in flavonol levels in tomato fruit skin across different laboratory and commercial cultivars, suggesting that our approach shows promise for use in genome-wide association studies to identify genetic factors underlying variation in flavonol levels. Lastly, we measured flavonol levels in dry leaves of different plants used for brewed beverages. Conclusion In conclusion, the assay represents a simple, robust, and scalable flavonol screening tool for studies in plant metabolism, environmental physiology, breeding, and metabolic engineering.

Why it matches plant phenotyping methods植物組織中のフラボノール量を定量する高スループット測定法を開発し、感度・精度・再現性およびHPLCとの一致を検証している。単なる代謝測定ではなく、植物育種・代謝研究向けのスクリーニングツールとして方法自体が中心である。

abstractHere, we present a rapid, high-throughput, fluorescence-based microplate reader assay for flavonol quantification

A high-performance biocompatible biomass-based fish gelatin organohydrogel strain sensor for long-term accurate plant growth monitoring →

Organohydrogel-based plant strain sensors hold significant potential for enabling accurate and real-time monitoring of plant growth processes. However, existing strain sensors typically face challenges such as inferior biocompatibility, trade-off between sensing performance and mechanical properties, as well as poor long-term stability, leading to inaccurate monitoring and plant tissue damage and thus hindering their practical applications. Herein, we propose a synergistic metal ion and multiple hydrogen bond dual crosslinking strategy to develop a biomass-based fish gelatin organohydrogel as a strain sensing material. The resultant organohydrogel simultaneously exhibits excellent mechanical properties (Young's modulus of 99.9 kPa and strong adhesiveness of 60 kPa), high sensing performance (GF = 2.13, stable response across a wide temperature range from -80 °C to 25 °C), outstanding plant tissue and human cell biocompatibility, and long-term stability (over 5000 loading-unloading cycles under 100% strain), demonstrating superior overall performance to most existing organohydrogels. To harness these unique material performances, we fabricate a sandwich-structured plant strain sensor for long-term monitoring of plant growth. The fabricated strain sensor enables successful real-time monitoring of the growth dynamics of lotus stems and pomelo fruits with high accuracy and long-term stability up to three weeks. Our novel design strategy of high-performance organohydrogels enables high-fidelity plant growth monitoring, unlocking new potentials for advancing data-driven smart and precision farming practices.

Why it matches plant phenotyping methods植物成長を長期・リアルタイムに測定するひずみセンサーの材料設計、性能評価、植物での検証が研究の中心であり、植物フェノタイピング手法に該当する。

abstractwe propose a synergistic metal ion and multiple hydrogen bond dual crosslinking strategy to develop a biomass-based fish gelatin organohydrogel as a strain sensing material

The ultrastructure of the mature wheat grain after resin embedding, as observed using atomic force microscopy →

This study examines the ultrastructure of the outer layers of hexaploid wheat (Triticum aestivum L.) seeds using atomic force microscopy (AFM) in air tapping mode. The specimens were resin-embedded after hydration. A standardised protocol for preparing specimens specifically for AFM investigations is presented, focusing on revealing the ultrastructure while minimising artefacts and optimising the resolution of the structural morphology. AFM provides a comprehensive histological description of the hydrated mature wheat seed, encompassing each layer from the outer pericarp to the starchy endosperm. This study highlights the ultrastructural details of the tissues in their hydrated state, particularly with regard to morphology and size. Thus, AFM shows great potential for revealing intricate details of plant tissues structure and ultrastructure.

Why it matches plant phenotyping methods成熟コムギ種子の組織形態・超微細構造をAFMで取得するための標準化試料調製プロトコルを提示しており、植物形態の観察手法が中心である。

abstractA standardised protocol for preparing specimens specifically for AFM investigations is presented, focusing on revealing the ultrastructure while minimising artefacts and optimising the resolution of the structural morphology.

Low-Cost Custom-Built Flow Meters for Plant Hydraulic Conductance: Validation of Accuracy, Precision, and Reproducibility. →

Measurement of xylem hydraulic conductance provides access to xylem hydraulic conductivity and vulnerability to cavitation, two key traits for assessing plant sensitivity to environmental stressors. We evaluated the performance of custom-built low-cost pressure drop flow meters through nearly 1200 measurements across devices, laboratories, reservoir heights (10, 25 and 45 cm, used to induce pressure head and drive water flux) and PEEK tubing of hydraulic contrasting resistances. Flow meters were interchangeable, with mean differences generally < 3.5% and never exceeding 5%, with 88.9% of comparative tests showing no significant difference. Under recommended conditions (25-45 cm pressure head, downstream-to-upstream pressure ratio ≈0.5), precision reached 1%-7% coefficient of variation. Accuracy, assessed against reference values obtained by water displacement, was also strong, with 68% of measurements deviating by < 5% from reference values and over 78% when measured at {greater than or equal to}25 cm. At 10 cm, performance declined because sensor deviations represented a larger fraction of pressure differential, and low-resistance PEEK tubing increased absolute but not relative error. Validated flow meters proved portable, affordable (≈2500 CAD), and reliable. Their low cost, open-source interface, and publicly available construction protocol make them accessible to laboratories with limited resources, enabling reproducible multi-laboratory studies of plant hydraulics and fostering international collaborations.

Why it matches plant phenotyping methods植物の木部油圧コンダクタンスという生理形質を測定する低コスト流量計を開発・検証し、精度・再現性・多施設間性能を評価しているため、植物フェノタイピング手法が研究の中心である。

abstractWe evaluated the performance of custom-built low-cost pressure drop flow meters through nearly 1200 measurements across devices, laboratories, reservoir heights (10, 25 and 45 cm, used to induce pressure head and drive water flux) and PEEK tubing of hydraulic contrasting resistances.

Three-dimensional nano-imaging reveals subtle changes in xylem structure in CAD-deficient sorghum →

Lignin plays a central role in the formation and function of secondary cell walls in vascular plants. However, the structural consequences of lignin modification for cell wall properties and cellular function in grasses remain poorly understood. Here, we investigated how cinnamyl alcohol dehydrogenase (CAD) deficiency alters vascular cell architecture in Sorghum bicolor, using the brown midrib-6 (bmr6) mutant as a model system. Biochemical and histochemical analyses confirmed altered lignin chemistry in bmr6, including increased incorporation of hydroxycinnamaldehyde residues and reduced tricin levels. We applied ptychographic X-ray computed tomography (PXCT) to quantify the cell wall geometry, in three dimensions, at nanometer-scale resolution. PXCT enabled measurements of wall thickness distribution and lumen shape along tracheary elements. Analyses revealed no significant differences in wall thickness between wild-type and bmr6 plants. However, three-dimensional morphometric descriptors indicated reduced lumen convexity in bmr6, suggesting localized modifications not detectable by conventional two-dimensional imaging. Water flow numerical simulations through PXCT-derived images indicated reduced vessel permeability and simulated hydraulic conductivity in bmr6, suggesting that subtle geometric changes may influence performance. These findings highlight the value of three-dimensional imaging for resolving cell wall organization and provide new insight into the architectural resilience of grass xylem in response to targeted lignin modification. HighlightThree-dimensional X-ray nano-imaging reveals alterations in the cell wall architecture that affect simulated hydraulic performance under reduced CAD activity in sorghum.

Why it matches plant phenotyping methods植物の木部細胞壁形状をナノスケール3D画像から定量化するPXCT手法が研究の中心であり、壁厚・内腔形状・形態記述子を抽出しているため、植物表現型計測の実質的な適用に該当する。

abstractWe applied ptychographic X-ray computed tomography (PXCT) to quantify the cell wall geometry, in three dimensions, at nanometer-scale resolution.

Plant Microtechnique with Resin: Towards Plant Histolomics →

Plant microtechnique involves a sequence of skill-intensive histological procedures that often yield poorly reproducible images and limited quantitative information. Nevertheless, it provides an essential cellular and tissue context needed to understand biological functions. In this work, we present an optimized resin-based microtechnique that replaces paraffin embedding, incorporates a chemically activated adhesive treatment for glass slides, and develop a trichrome stain for resin sections. All these improvements enhanced section stability and image reproducibility, enabled a broader color palette with sharp contrast of tissues, cells and organelles, and selected ultrastructural features using light microscopy. Based on these preparations, a quantitative micrograph analysis workflow was developed based on image segmentation and feature extraction using MATLAB (R2024a) and Adobe Photoshop (CS6). This approach enables the measurement of a wide range of morphometric and compositional features, generating structured histological datasets that we refer to as plant histolomes. As an illustrative application, this workflow was applied to leaves from several model plants species and integrated multiple anatomical traits into a composite feature, the “C4 Kranz-anatomy level”, enabling quantitative comparison along the C3-C4 anatomical transition. The resin-based microtechnique and the histolomics framework developed in this work provide a robust and reproducible basis for the quantitative plant histology, bridging classical microscopy with a data-driven tissue analysis.

Why it matches plant phenotyping methods樹脂包埋・染色による植物組織画像の再現性向上と、画像セグメンテーション／特徴抽出による形態・組成形質の定量化が研究の中心であり、植物フェノタイピング手法の開発・検証・適用に該当する。

abstractIn this work, we present an optimized resin-based microtechnique

Integrated sensing and communication for lettuce water-status monitoring →

With the rapid development of smart agriculture, the agricultural Internet of Things (Ag-IoT) has gradually established a monitoring system centered on distributed sensing, low-power communication, and intelligent control. However, current solutions underexplore the perceptible characteristics of communication signals, and therefore do not fully utilize their latent potential in environmental perception. This paper targets the demand for crop water monitoring and introduces an integrated sensing and communication (ISAC) approach. This method can achieve non-contact and continuous perception of crop water status by reusing the communication link without altering the existing hardware architecture and frequency band configuration. Taking leafy vegetables such as lettuce as the research object, a prototype system based on a 3 GHz communication link was built. A quantitative mapping model between the water content of plant tissues and the amplitude and phase disturbances they cause to electromagnetic waves was established. A joint optimization mechanism that considers both communication performance and sensing accuracy was proposed to achieve a coordinated configuration between communication quality (BER < 10⁻⁴, SNR ≈ 20 dB, EVM < 8 %) and sensing accuracy (MAE = 2.51 %, R² = 0.92). Experiments were conducted in controlled environments and production-like scenarios, demonstrating that the method can stably identify the water status of lettuce while ensuring communication quality of service (QoS). The proposed ISAC method is potentially compatible with existing Ag-IoT frequency bands and physical-layer infrastructures, assuming access to pilot/CSI and airtime control. Protocol-level integration with LoRa, Wi-Fi, and NB-IoT is defined as future work It provides a low-cost, high-integration, and easily scalable communication-driven solution for water monitoring in smart agriculture.

Why it matches plant phenotyping methodsレタスの水分状態という植物生理形質を、通信信号を再利用した非接触センシングで推定する方法を開発し、プロトタイプと精度検証を行っており、フェノタイピング手法が中心である。

abstractThis method can achieve non-contact and continuous perception of crop water status by reusing the communication link

The ultrastructure of the mature wheat grain tissue in its native state, as observed using atomic force microscopy →

This study presents a novel application of atomic force microscopy (AFM) for characterising the ultrastructure of dry (15 % moisture) native and mature wheat grains (Triticum aestivum L.). A key contribution is the standardisation of a meticulous sample preparation protocol that minimises artefacts. This protocol involves dry-cutting the grains using a device that enables precise surface smoothing via ultramicrotomy, ensuring perfect alignment for AFM scanning without the need for resin-embedding. The research provides a comprehensive histological description ranging from the outer pericarp to the starchy endosperm. The outer layers (pericarp, seed coat, and nucellar epidermis) appear as compact, continuous structures in the dry state, with stronger inter-layer adhesion. The study also discovered a previously undescribed left-handed helical twist in the tube cells of the inner pericarp, a feature that is hypothesised to be lost in conventional resin-embedding techniques. AFM is demonstrated to be a powerful tool for revealing intricate, hydration-dependent ultrastructural adaptations in plant tissues.

Why it matches plant phenotyping methods成熟コムギ粒の組織微細構造という植物形質を対象に、AFM imaging とアーティファクトを低減する試料調製法を中心的に開発・実証しているため、植物フェノタイピング手法として採用する。

abstractThis study presents a novel application of atomic force microscopy (AFM) for characterising the ultrastructure of dry (15 % moisture) native and mature wheat grains (Triticum aestivum L.).

Resolving subcellular sucrose concentrations in plant tissues →

Abstract Sucrose is the central unit of carbon and energy in plants. As the product of photosynthesis, it is transported from source–to–sink tissues across both short and long distances. Subcellular sucrose concentrations strongly influence rates of transport within cells, tissues, and organs. Moreover, as a central metabolite, its concentration influences the rates of many enzymatic reactions. Measuring sucrose concentration with subcellular resolution remains challenging, especially for the cytosol, which hosts many critical enzymatic reactions and, in many cells, occupies only a thin layer between the vacuole and the plasma membrane. Here, we review the methods that have been utilized to measure subcellular sucrose concentrations in plant cells. The approaches covered include microautoradiography, non-aqueous fractionation, Fourier transform infrared (FTIR) microspectroscopy, Raman microspectroscopy, mass spectrometry imaging, Förster resonance energy transfer (FRET) nanosensors, direct sampling, and theoretical modelling. We provide perspectives on the use cases for these methods and discuss developments towards resolving subcellular sugar concentrations in live tissues.

Why it matches plant phenotyping methods植物組織内の細胞内ショ糖濃度という生理形質を測定する手法群をレビューし、各手法の利用場面と発展を論じているため、植物フェノタイピング手法レビューに該当する。

abstractHere, we review the methods that have been utilized to measure subcellular sucrose concentrations in plant cells.

Electrical impedance spectroscopy in plant cold resistance: a review →

Low-temperature stress compromises the integrity of plant cell membranes, leading to lipid phase transitions and increased membrane permeability, which subsequently induce physiological damage. However, conventional methods for assessing cold resistance, such as relative electrolyte leakage measurement, growth recovery tests, and LT50 determination, are limited by their highly destructive nature, time-consuming procedures, or insufficient sensitivity. Electrical impedance spectroscopy (EIS), a non-destructive and efficient electrophysiological technique, has emerged as a valuable tool for evaluating cold resistance and screening cold-tolerant plant varieties. By applying multi-frequency alternating current to plant tissues and measuring the resulting impedance responses, EIS enables the extraction of key parameters such as extracellular resistance, intracellular resistance, and cell membrane capacitance. These parameters collectively reflect the structural integrity and physiological condition of cells from multiple perspectives. Notably, under low-temperature stress, plant genotypes with varying degrees of cold resistance exhibit distinct impedance spectral characteristics, allowing EIS to efficiently discriminate cold tolerance among different varieties or treatments. This review summarizes recent advances in EIS-based research on plant cold resistance, covering its underlying electrical principles, equivalent circuit models, and biophysical mechanisms. It also outlines practical applications, including the screening of cold-tolerant woody and herbaceous plants, as well as integration with traditional assessment methods, while highlighting the advantages of EIS in terms of accuracy, universality, and real-time monitoring. Furthermore, the review addresses key challenges such as species specificity, model standardization, and data analysis, and proposes future research directions, including integration with artificial intelligence, development of portable devices, and establishment of standardized stress resistance databases.

Why it matches plant phenotyping methods植物の低温耐性をEISで非破壊評価・識別する方法を中心に、原理、モデル、検証課題、実用化をレビューしており、植物フェノタイピング手法のレビューに該当する。

abstractElectrical impedance spectroscopy (EIS), a non-destructive and efficient electrophysiological technique, has emerged as a valuable tool for evaluating cold resistance and screening cold-tolerant plant varieties.

Integration of X-Ray CT, Sensor Fusion, and Machine Learning for Advanced Modeling of Preharvest Apple Growth Dynamics. →

Understanding the complex interplay between environmental factors and fruit quality development requires sophisticated analytical approaches linking cellular architecture to environmental conditions. This study introduces a novel application of dual-resolution X-ray computed tomography (CT) for the non-destructive characterization of apple internal tissue architecture in relation to fruit growth, thereby advancing beyond traditional methods that are primarily focused on postharvest analysis. By extracting detailed three-dimensional structural parameters, we reveal tissue porosity and heterogeneity influenced by crop load, maturity timing and canopy position, offering insights into internal quality attributes. Employing correlation analysis, Principal Component Analysis, Canonical Correlation Analysis, and Structural Equation Modeling, we identify temperature as the primary environmental driver, particularly during early developmental stages (45 Days After Full Bloom, DAFB), and uncover nonlinear, hierarchical effects of preharvest environmental factors such as vapor pressure deficit, relative humidity, and light on quality traits. Machine learning models (Multiple Linear Regression, Random Forest, XGBoost) achieve high predictive accuracy (R 2 > 0.99 for Multiple Linear Regression), with temperature as the key predictor. These baseline results represent findings from a single growing season and require validation across multiple seasons and cultivars before operational application. Temporal analysis highlights the importance of early-stage environmental conditions. Integrating structural and environmental data through innovative visualization tools, such as anatomy-based radar charts, facilitates comprehensive interpretation of complex interactions. This multidisciplinary framework enhances predictive precision and provides a baseline methodology to support precision orchard management under typical agricultural variability.

Why it matches plant phenotyping methodsリンゴ果実の内部組織構造をX線CTで非破壊・三次元計測し、構造パラメータを抽出する手法が研究の中心であり、環境データとの統合や機械学習による形質推定も行っているため。

abstractThis study introduces a novel application of dual-resolution X-ray computed tomography (CT) for the non-destructive characterization of apple internal tissue architecture in relation to fruit growth

Measuring Phloem Transport Velocity on a Tissue-Level Using a Phloem-Mobile Dye. →

Here, we describe an in vivo dye-tracking method for measuring phloem transport velocity in seedlings, leaves, and petioles and potentially other translucent plant tissues. The method requires measurement of the fluorescent signal of a phloem-mobile dye using sensitive photo-sensors placed externally to the plant. Following dye application, velocity is determined by either following a dye pulse or using laser fluorescence bleaching. Velocity is estimated by dividing the distance traveled by the dye by the time it takes to travel. This method can be used to measure phloem transport velocity on intact plants with minimal disturbance and has the potential to be used under a variety of growth conditions. Because there are large differences among species in their anatomy, this method should be optimized for individual plants and tissue types.

Why it matches plant phenotyping methods植物体内の師部輸送速度という生理形質を、色素追跡と外部光センサーで測定する方法を開発・記述しており、表現型取得法が研究の中心である。

abstractHere, we describe an in vivo dye-tracking method for measuring phloem transport velocity in seedlings, leaves, and petioles and potentially other translucent plant tissues.

Quantification of Callose Deposition in the Phloem of Woody Stems Using Supervised Machine Learning-Driven Automated Image Analysis with the IlastiKlean R Package. →

Callose deposition in the phloem is an innate part of plant development and a response to biotic and abiotic stress, aiding in stress mitigation but potentially also compromising phloem functionality. Measuring callose using aniline blue staining is widely employed, but accurate quantification is hindered by image qualities such as texture and fluorescent artifacts. Here, we describe a method to quantify callose levels in the phloem of woody plants using aniline blue staining, confocal microscopy, and automated supervised machine learning-driven image analysis supported by the IlastiKlean R package. Bark peel samples from woody plants are collected from shoots, stained, and imaged to assess callose deposition. The microscopy images are preprocessed and analyzed using Fiji, Ilastik, and the IlastiKlean R package, which allows accurate quantification of the number, size, and distribution of callose deposits. This quantitative measure can be used to study, screen, and engineer plants that are better adapted to biotic or abiotic stresses, and it serves as an important tool for basic and foundational studies of callose deposition in the phloem.

Why it matches plant phenotyping methods木本植物の師部におけるカロース沈着を、画像解析とRパッケージで定量する手法の開発・記述が中心であり、植物の形態・生理状態を表す形質を抽出する。

abstractHere, we describe a method to quantify callose levels in the phloem of woody plants using aniline blue staining, confocal microscopy, and automated supervised machine learning-driven image analysis supported by the IlastiKlean R package.

A Dual-Reporter System for the Analysis of Phloem Structural and Signaling Responses In Vivo. →

Plants have evolved an effective defense mechanism in the phloem to prevent the spread of pathogens and minimize the loss of phloem sap following injury. Specific structural phloem proteins known as P-proteins rapidly seal affected sieve elements by plugging the sieve plates, a phenomenon defined as sieve element occlusion. This chapter describes a live cell imaging method for the analysis of P-protein responses and signal propagation in vivo without tissue sectioning or mechanical manipulation. It is based on an Arabidopsis thaliana dual-reporter line where P-proteins are labeled with fluorescent tags in a complementation background, allowing real-time visualization of the parietal protein network during sieve element occlusion. The calcium sensor Yellow Cameleon 3.6 is specifically expressed and anchored in the sieve elements, enabling the detection of calcium waves and their effects on P-protein structure over longer distances in vivo. Using this protocol, a wide range of external triggers-including chemical treatments, buffers, and wounding-can be applied with precision, allowing the analysis of P-protein functions and long-distance signaling in the phloem. The method is readily adaptable to other genetically encoded sensors and can be used to investigate P-protein-independent processes as well as the diverse signaling and structural responses of additional sieve element components.

Why it matches plant phenotyping methods植物の師部におけるタンパク質構造とカルシウムシグナルを生体内で可視化・解析するライブセルイメージング法が中心であり、植物状態の取得手法を具体的に提示している。

abstractThis chapter describes a live cell imaging method for the analysis of P-protein responses and signal propagation in vivo without tissue sectioning or mechanical manipulation.

Measuring Esculin Export from Leaves as Proxy for Sucrose Loading Rates in the Phloem. →

Phloem loading of sucrose and the transport from source leaves to sink tissues is vital for plant growth and carbon allocation. Traditional methods to measure phloem loading are often time-consuming or require specialized equipment. Here, we introduce a rapid, cost-effective esculin-based fluorometric assay as a reliable proxy for sucrose loading. Esculin, a fluorescent coumarin glucoside, is specifically transported by sucrose transporters in plants with active apoplastic phloem loading. After application to source leaves, esculin fluorescence is measured in the extracted leaf sap, providing a sensitive and relatively high-throughput method for analyzing phloem loading dynamics. Validated against established techniques, the assay is accessible to nonspecialized laboratories and enables investigations into environmental and developmental regulation of phloem loading, offering insights into plant growth and stress responses.

Why it matches plant phenotyping methods葉へのエスクリン輸送を蛍光測定し、師部のショ糖ローディング速度を推定する植物生理表現型測定法を開発・検証しており、方法が研究の中心です。

abstractHere, we introduce a rapid, cost-effective esculin-based fluorometric assay as a reliable proxy for sucrose loading.

Characterization of Viruses in Phloem by Correlative X-Ray Microtomography (μCT)-Volume Electron Microscopy (vEM) Imaging. →

Studying virus-infected phloem is of significant importance, as it not only enhances our understanding of viral pathogenesis but also leverages viruses as tools to expand knowledge about plant phloem physiology. The uneven distribution pattern of phloem-infecting viruses poses methodological challenges for such studies-requiring both large field of view (FOV) and high-resolution imaging. A comprehensive anatomical analysis of the phloem necessitates global visualization, while resolving viral structures demands local high-resolution observation. This chapter describes a method, the X-ray microtomography (μCT)-volume electron microscopy (vEM) correlative imaging technique, which effectively addresses these methodological requirements, where μCT provides the large FOV for identification of regions of interest, followed by vEM acquisition of high-resolution images. It is a six-step protocol, including: (1) sample preparation, (2) flaw detection, (3) overview imaging by μCT, (4) identifying viral infection regions, (5) high-resolution imaging by vEM, and (6) image processing and analysis. In this workflow, the steps of sample preparation and identification of viral infection regions are critical. This protocol was originally established for investigating Southern rice black-streaked dwarf virus (SRBSDV) infection in rice phloem, with parameters optimized for plant reoviruses. We provide advice on how to adapt the approach for studying other viral infections.

Why it matches plant phenotyping methods植物のウイルス感染部位と師部構造をμCT・vEM相関イメージングで取得・解析する6段階プロトコルが中心であり、植物状態の画像ベース計測法に該当する。

abstractThis chapter describes a method, the X-ray microtomography (μCT)-volume electron microscopy (vEM) correlative imaging technique

Infrared Microimaging of Sucrose Distribution in Plant Vascular Tissues. →

Sucrose is the primary transport sugar in plants, serving as an essential energy source and signaling molecule. Detection, visualization, and quantification of sucrose in various plant tissues are essential for understanding the metabolic and physiological processes that sustain plant life. Traditional metabolite-mapping techniques have struggled to visualize the quantitative distribution of sucrose at sufficient resolution to distinguish vascular bundles from surrounding tissues. Here, we present a Fourier-transform infrared (FTIR) imaging approach that can visualize sucrose in plant tissues quantitatively at a microscopic resolution (~12 µm). This IR-based, label-free method can be used with both model plants and agriculturally important crops. The assay has a detection range of 20-1000 mM and can map sucrose distribution within complex organs such as stems, leaves, and seeds. Notably, it enables the precise quantification of sucrose levels in vascular tissues. This is a trait of great interest in many current breeding and plant biotechnology approaches aimed at increasing crop yield.

Why it matches plant phenotyping methods植物組織内のスクロース分布を定量化するFTIR画像法を開発・提示しており、植物の生理状態（糖分布）を取得する方法が研究の中心である。

abstractHere, we present a Fourier-transform infrared (FTIR) imaging approach that can visualize sucrose in plant tissues quantitatively at a microscopic resolution (~12 µm).

Analysis of Gametophytic Apomixis Using Confocal Microscopy. →

Apomixis is an asexual reproductive mechanism that takes place deeply inside the female reproductive organs of the plant, in ovules and seeds. In gametophytic apomixis, an unreduced female gametophyte is produced by a modified meiosis of the megaspore mother cell (dipolspory) or from a somatic initial cell (apospory). The unreduced, nonrecombined egg cell develops subsequently into an embryo by parthenogenesis. The cyto-embryological study of apomixis is challenging because of the inaccessibility of these structures. Consequently, images of apomeiosis and parthenogenesis with high definition are limited to a few species. In this chapter, we show the application of a Feulgen staining protocol combined with confocal microscopy for the study of nonreductional megasporogenesis and autonomous embryo formation in diplosporous apomictic Taraxacum officinale and aposporous apomictic Pilosella piloselloides var. praealta. Using a rapid and technically simple method, performed on whole-mount ovaries, we have obtained high-resolution images of the female reproductive cells. Furthermore, we highlight the application of this protocol for the study of loss-of-diplospory and loss-of-parthenogenesis mutants in the same species.

Why it matches plant phenotyping methods全載卵巣にFeulgen染色と共焦点顕微鏡を組み合わせ、雌性生殖細胞・胚形成を高解像度で可視化する技術を提示・適用しており、植物の生殖状態を取得する方法が中心である。

abstractUsing a rapid and technically simple method, performed on whole-mount ovaries, we have obtained high-resolution images of the female reproductive cells.

Preparation of Tissue Sections for Light-Microscopic Analysis of Phloem Anatomy. →

Accurate analysis and description of plant tissues often rely on the preparation of high-quality anatomical slides, a task that becomes particularly challenging when dealing with heterogeneous tissues such as phloem, which contains both soft and rigid components. This chapter provides a comprehensive protocol outlining key techniques for the optimal preparation of phloem tissue samples for light microscopy. The protocol encompasses essential steps such as fixation, softening, embedding, sectioning, staining, and mounting, and is adaptable for examining phloem and adjacent tissues in both woody and herbaceous stems and roots. Studying phloem anatomy is crucial for understanding nutrient transport, plant development, and responses to environmental stress, offering insights into both fundamental plant biology and practical applications in agriculture and forestry.

Why it matches plant phenotyping methods植物の師部解剖形態を観察・解析するための組織切片作製プロトコルが主題であり、植物形質取得の技術的方法が中心である。

abstractThis chapter provides a comprehensive protocol outlining key techniques for the optimal preparation of phloem tissue samples for light microscopy.

Evaluating rapid plant tissue analysis method for nitrogen diagnostics in corn (Zea mays L.) production →

Abstract Background Accurate assessment of plant nitrogen status is essential for optimizing fertilizer inputs, increasing productivity, and ensuring environmental quality. This study compared three nitrogen status assessment in corn ( Zea mays L.): visual assessment method, a novel real-time nutrient estimation using the Picketa LENS™ system, and the conventional laboratory tissue analysis as a reference method. To evaluate the accuracy of the Picketa LENS™ system, a field experiment with four nitrogen treatments (0% nitrogen (control), 80% nitrogen, 100% nitrogen, and 100% nitrogen + stabilizer) and four replications was conducted in York County, Nebraska. Results Visual assessment detected treatment differences, with the 0% nitrogen plots showing severe chlorosis and a progressive decline (63.4% reduction) in healthy leaves below the ear over five weeks, whereas 100% nitrogen maintained consistently higher healthy leaf counts (only a 7.4% reduction). However, visual assessment showed limited ability to distinguish between 80% nitrogen and 100% nitrogen + stabilizer treatments until weeks four and five. Both quantitative methods did not detect treatment differences due to the sampled leaf position. The Picketa system (2024 corn model) reported higher absolute nitrogen concentrations (approximately 4.4–4.6%) than laboratory analysis (2.9–3.2%) across all treatments and did not detect significant treatment effects. Conventional laboratory analysis detected only a modest increase in the 100% nitrogen treatment compared with the 0% control. For macronutrients, the Picketa system measured concentrations higher than conventional tissue sampling for phosphorus, potassium, and calcium, with potassium showing approximately 40% higher values and calcium showing 40–50% higher values, while magnesium and sulfur showed close agreement between methods. Micronutrient analysis revealed that the Picketa system consistently reported higher concentrations than conventional tissue sampling for iron (45% higher), manganese (approximately 4-fold higher), copper (90% higher), and zinc (33% higher), but reported significantly lower boron concentrations (67% lower). Despite these absolute value differences, both methods demonstrated similar patterns of detection across treatments. Conclusions Visual assessment effectively detected treatment differences, while the Picketa System and the conventional method did not, but maintained similar patterns. These findings highlight the promise of Picketa LENS and the importance of matching sample positions and timing to diagnostic objectives. Integrating real-time sensing with conventional methods can improve nitrogen management decisions.

Why it matches plant phenotyping methodsトウモロコシの窒素状態を測定するリアルタイムセンサー法を従来法と比較し、精度や処理差の検出性能を評価しているため、植物形質測定法の技術検証が中心である。

abstractThis study compared three nitrogen status assessment in corn ( Zea mays L.): visual assessment method, a novel real-time nutrient estimation using the Picketa LENS™ system, and the conventional laboratory tissue analysis as a reference method.

A Breathable, Low-Cost, and Highly Stretchable Medical-Textile Strain Sensor for Human Motion and Plant Growth Monitoring →

Flexible strain sensors capable of conformal integration with living organisms are essential for advanced wearable electronics, human–machine interaction, and plant health. However, many existing sensors require complex fabrication or rely on non-breathable elastomer substrates that interfere with the physiological microenvironment of skin or plant tissues. Here, we present a low-cost, breathable, and highly stretchable strain sensor constructed from biomedical materials, in which a double-layer medical elastic bandage serves as the porous substrate and an intermediate conductive medical elastic tape impregnated with carbon nanotubes (CNTs) ink acts as the sensing layer. Owing to the hierarchical textile porosity and the deformable CNTs percolation network, the sensor achieves a wide strain range of 100%, a gauge factor of up to 2.72, and excellent nonlinear second-order fitting (R2 = 0.997). The bandage substrate provides superior air permeability, allowing long-term attachment without obstructing moisture and gas exchange, which is particularly important for maintaining skin comfort and preventing disturbances to plant epidermal physiology. Demonstrations in human joint-motion monitoring and real-time plant growth detection highlight the device’s versatility and biological compatibility. This work offers a simple, low-cost yet effective alternative to sophisticated strain sensors designed for human monitoring and plant growth monitoring, providing a scalable route toward multifunctional wearable sensing platforms.

Why it matches plant phenotyping methods植物の成長をリアルタイム検出する伸縮センサーを開発し、植物への適用を実証しており、表現型取得が中心的な技術貢献である。

abstractHere, we present a low-cost, breathable, and highly stretchable strain sensor constructed from biomedical materials

High-resolution microCT reveals relationships between stomata and interior leaf anatomy in Sorghum →

Stomata are pores in the leaf epidermis that regulate the trade-off between CO2 uptake for photosynthesis and water vapor loss to the atmosphere. Stomatal patterning therefore influences water use efficiency and is a target for engineering to avoid drought stress. However, there is limited understanding of how internal leaf anatomy is coordinated with stomatal development, in part due to the technical challenges of assessing three-dimensional anatomy with sufficient resolution. C4 grasses are understudied, and this is a significant knowledge gap given their file-like stomatal distribution and unique mesophyll organization. In this study, wild-type sorghum and a low-stomatal density transgenic line expressing a synthetic Epidermal Patterning Factor (EPFsyn) were studied. High-resolution microCT was paired with machine learning to characterize three-dimensional traits of mesophyll, epidermis, and airspace, which together determine gias. Sorghum internal leaf airspace is an arrangement of large sub-stomatal airspaces with thin air passageways. Adaxial and abaxial surfaces differed in stomatal patterning relative to mesophyll structures, sub-stomatal crypts and airspace CO2 conductance (gias). Surprisingly, adaxial stomata were consistently located above rather than between vascular bundles. Unexpectedly, gias was not significantly different in wild-type versus EPFsyn. EPFsyn plants had larger crypts and shifts in internal leaf anatomy, indicating a potential compensation mechanism for predicted impacts of reduced stomatal density on gias. These findings provide a new understanding of the interplay between leaf surface specific anatomy and internal structural patterning of the mesophyll in a C4 species, and provides knowledge relevant to engineering water use efficiency in crop species.

Why it matches plant phenotyping methods高解像度microCTと機械学習を組み合わせ、葉の三次元形態・気腔などの植物形質を抽出する手法が研究の主要部分であり、単なる生物学的測定ではない。

abstractHigh-resolution microCT was paired with machine learning to characterize three-dimensional traits of mesophyll, epidermis, and airspace

Modeling and temporal analysis of electrical impedance spectroscopy responses of Rosa chinensis under powdery mildew stress →

Under the intensifying impact of global climate change, the frequency of plant disease outbreaks is steadily increasing, posing significant challenges to healthy cultivation and precision management. To enable early diagnosis of plant disease stress, this study used two rose (Rosa chinensis) varieties, ’Red Cap’ and ’Carefree Wonder’ were used to conduct powdery mildew stress experiment. Throughout the stress period, leaf electrical impedance spectroscopy (EIS), physiological parameters, and ultrastructural observations, were collected. A novel lumped equivalent circuit model was proposed, incorporating plant cell electrophysiological properties. The model developed for both rose varieties-featuring Constant Phase Elements (CPE) and Warburg elements (W), successfully characterized the resistive properties of the leaf tissue, including the extracellular resistance (R₁), cell membrane resistance (R₂), intracellular resistance (R₃), and vacuole interior resistance (R₄). Model parameters R₁ and R₃ were significantly correlated with the above physiological indicators, and showed significant differences 3 to 11 days earlier than traditional physiological parameters, demonstrating strong potential for early detection of cellular damage. Overall, this study demonstrates that EIS technology can dynamically reflect electrical property changes in plant tissues under biotic stress, effectively overcoming the lag limitations of conventional physiological measurements, providing a promising tool for early disease diagnosis and resistance screening.

Why it matches plant phenotyping methodsバラ葉の病害ストレス状態を電気インピーダンス分光法で測定し、等価回路モデルを開発・検証して早期診断性能を評価しているため、植物フェノタイピング手法が中心である。

abstractA novel lumped equivalent circuit model was proposed, incorporating plant cell electrophysiological properties.

Chemical imaging of lignocellulosic biomass: Mapping plant chemistry →

Lignocellulosic biomass (LB), which encompasses various plant samples, requires thorough characterization to optimize its use as a carbon resource. Chemical imaging simultaneously provides chemical and spatial information, offering significant benefits for LB analysis. This review presents an overview of the most advanced techniques for achieving this goal. By combining spectrometry and microscopy, microspectroscopy enables chemical imaging using various irradiation sources (IR, Raman, fluorescence, among others), allowing for the quantitative mapping of key LB components such as lignins, cellulose, and hemicelluloses. Mass Spectrometry Imaging (MSI) generates a mass spectrum for each spot of a sample thereby creating a chemical image pixel-by-pixel. MSI techniques like Matrix-Assisted Laser Desorption/Ionization (MALDI), down to 2-5 μm spatial resolution, and Secondary Ion Mass Spectrometry (SIMS), down to 300 nm for molecular analysis, effectively map small molecules in LB. In contrast, Desorption ElectroSpray Ionization (DESI) has been applied to plant extracts but remains largely unexplored for LB applications. Nuclear Magnetic Resonance (NMR) provides insight into various LB properties too. Solid-state NMR (ssNMR) and Dynamic Nuclear Polarization (DNP) help elucidate the structure of LB, sometimes aided by 3D atomistic modeling, whereas micro-Magnetic Resonance Imaging (micro-MRI) and Time-Domain (TD-NMR) probe the impact of water on LB properties.

Why it matches plant phenotyping methods植物バイオマスの化学成分を空間的に定量・マッピングする化学イメージング手法のレビューであり、植物試料の観察・形質抽出法が中心である。

abstractThis review presents an overview of the most advanced techniques for achieving this goal.

Lighting up the underground: enhancing growth-ring detection in grassland subshrubs using autofluorescence and histochemistry →

Growth rings in woody plants form in response to seasonal variation in the environment and are fundamental to dendrochronological studies, but estimating plant ages—especially in underexplored growth forms such as forbs, shrubs and subshrubs from grasslands—remains challenging. Here, we address a knowledge gap in the anatomy and histochemistry of subshrubs from natural Cerrado grasslands and evaluate their potential for dendrochronological applications. We studied underground woody organs of Jacaranda decurrens, Lippia lupulina, and Mandevilla longiflora, collected at the Santa Bárbara Ecological Station (Brazil). We used autofluorescence microscopy and a suite of histochemical tests targeting structural and non-structural compounds. Autofluorescence allowed spatial assessment of wood tissues without staining, and improved growth-ring visualization. FASGA staining increased contrast between fibers and parenchyma, facilitating tissue discrimination and growth-ring delimitation, while Mäule staining highlighted differences in cell-wall composition and guaiacyl/syringyl (G/S) ratios throughout growth-ring formation. Starch was consistently detected in parenchymatic cells of all species (lowest in J. decurrens, intermediate in L. lupulina, highest in M. longiflora), and its spatial association with parenchyma aided growth-ring identification. Combining fluorescence and histochemical approaches provides complementary insights into the anatomy and chemistry of underground organs and advances dendrochronological studies in grassland ecosystems.

Why it matches plant phenotyping methods自家蛍光顕微鏡と組織化学染色を用いて地下木質器官の成長輪を可視化・判別する方法が研究の中心であり、植物の年齢・成長状態という形質の取得に直接関与する。

abstractAutofluorescence allowed spatial assessment of wood tissues without staining, and improved growth-ring visualization.

Determination of porosity and permeability correlation of leafy vegetable based on X-ray computed tomography and cell segmentation →

Porosity and permeability are critical physical parameters for accurately modelling macroscale heat and mass transfer processes during the cooling, thermal processing, and storage of leafy vegetables. However, existing estimation methods primarily rely on lumped semi-empirical approaches, which overlook the realistic 3D structural information, limiting insights into microscale water transport behaviour. This study utilised low- and high-resolution X-ray computed tomography (CT) combined with advanced cell segmentation techniques to determine the porosity-permeability correlation of spinach, a representative easily dehydrated leafy vegetable. Experiments demonstrated that the Cellpose, dilation, and erosion algorithms effectively segmented adhering cells and generated lamina and petiole slices with varying porosity gradients. Using 3D reconstruction and seepage simulation, the porosity and permeability of representative elementary volumes (REVs) in the lamina and petiole tissues were calculated, and the pressure and flow rate distributions within the intercellular spaces were visualised. The porosity-permeability relationship was fitted using the Kozeny-Carman (KC) formula as κₗ = 4.839 × 10⁻¹¹φ¹.⁷⁰/(1 - φ)⁰.⁷⁰ for lamina REVs and κₚ = 1.128 × 10⁻¹⁰φ².¹⁶/(1 - φ)¹.¹⁶ for petiole REVs. Grayscale-porosity and porosity-permeability correlations were further applied to characterise the heterogeneity of porosity (2.742%–53.30%) and permeability (4.925 × 10⁻¹⁴ - 2.829 × 10⁻¹¹ m²) of intact spinach. The study aims to provide technical and theoretical support for multiscale modelling in the quality control of leafy vegetables.

Why it matches plant phenotyping methodsX線CT、細胞セグメンテーション、3D再構成を中核として、ホウレンソウ組織の空隙率・透過率という構造的な植物形質を定量化する手法を開発・適用しているため。

abstractThis study utilised low- and high-resolution X-ray computed tomography (CT) combined with advanced cell segmentation techniques to determine the porosity-permeability correlation of spinach

Deep Learning and Machine Learning Modeling Identifies Thidiazuron as a Key Modulator of Somatic Embryogenesis and Shoot Organogenesis in Ferula assa-foetida L. →

The spice Ferula assa-foetida L., also known as asafoetida, is widely recognized for its medicinal and culinary applications. The non-native status of the plant and the prolonged dormancy of its seeds pose significant challenges for large-scale cultivation in India. In vitro organogenesis offers an effective solution to these obstacles. Establishing reliable in vitro regeneration protocols requires standardized statistical methods to evaluate univariate and multivariate data for optimizing specific traits. However, these methods have limitations when handling complex, nonlinear inputs, often producing large prediction errors that reduce the reliability of trait optimization. This study developed an in vitro regeneration system for F. assa-foetida L. and identified optimal PGRs for somatic embryogenesis and shoot organogenesis through image-based morphological analysis. Predictive models were created using DL and ML algorithms. Calli induced from leaf explants was cultured on the Murashige and Skoog medium supplemented with various combinations and concentrations of thidiazuron (TDZ), 6-benzylaminopurine (BAP), and α-naphthaleneacetic acid (NAA), as experimental variables. Seven ML approaches, namely random forest (RF), support vector machine (SVM), k-nearest neighbours (kNN), decision tree (DT), extreme gradient boosting (XG Boost), naïve bayes, and logistic regression, alongside five DL models-convolutional neural network (CNN), MobileNet, region-based convolutional neural network (RCNN), residual neural network (ResNet), and visual geometry group (VGG19)-were employed to predict the best PGRs for somatic embryogenesis and shoot organogenesis. Among them, the convolutional neural network (CNN) achieved the highest accuracy (87%), outperforming baseline ML models such as logistic regression and decision tree (82%). This pioneering study in F. assa-foetida L. presents an AI-driven, image-based framework for predicting optimal PGRs, offering a scalable approach to enhance micropropagation in endangered medicinal plants.

Why it matches plant phenotyping methods画像ベースの形態解析と深層学習・機械学習を中核に、植物組織の器官形成状態を予測して表現型最適化を行う手法開発であり、単なる培養実験ではない。

abstractidentified optimal PGRs for somatic embryogenesis and shoot organogenesis through image-based morphological analysis.

BODIPY-Rhodacycle Fluorescent Probe for In Situ Imaging of Ethylene Dynamics in Live Systems. →

Endogenous ethylene production occurs across biological kingdoms, yet its pathophysiological roles remain incompletely defined. In situ detection of ethylene is impeded by its inherent volatility and chemical inertness. Here, we report BORh, a new turn-on fluorescent probe that operates via ethylene-triggered displacement of a rhodium quencher from a BODIPY-rhodacycle scaffold, liberating the intensely fluorescent BOET. BORh exhibits high sensitivity and selectivity, broad pH tolerance, and negligible cytotoxicity. In mammalian PC12 cells, it permits real-time visualization of both exogenously supplied and in situ generated ethylene. Within photosynthetic systems, BORh overcomes cell wall barriers and chlorophyll autofluorescence, enabling in situ monitoring of ethylene dynamics in algae ( Chlamydomonas reinhardtii ) and higher plant ( Arabidopsis thaliana and Allium cepa ) tissues. Remarkably, BORh-enabled fluorescence imaging revealed synchronous upregulation of ethylene and reactive oxygen species (ROS) under plant abiotic stress. H 2 O 2 exhibited concentration-dependent biphasic regulation of ethylene biosynthesis, whereas ethylene exerted no reciprocal effect on ROS generation. These findings establish ROS as upstream regulators of ethylene biosynthesis within plant stress signaling cascades. BORh emerges as a robust chemical tool for spatiotemporal dissection of ethylene biochemistry, offering new insights into ROS-ethylene crosstalk during plant stress responses and paving the way for future investigations of ethylene function in mammalian pathophysiology.

Why it matches plant phenotyping methods植物組織内のエチレン動態を可視化・測定する蛍光プローブを開発し、植物での性能を実証しているため、植物生理状態の取得法が中心である。

abstractHere, we report BORh, a new turn-on fluorescent probe

PLANT MICROTECHNIQUE WITH RESIN - TOWARDS PLANT HISTOLOMICS →

ABSTRACT Plant microtechnique is a sequence of skill-intensive histological and microscopy procedures that often yield limited quantitative information. However, it provides the cellular context needed to uncover biomolecular functions. In this work, we developed an easier microtechnique and a novel histolomic approach for the quantitative analysis of histological features. We replaced paraffin with resin as the embedding medium, developed an adhesive treatment for glass slides, and developed a trichrome staining. These improvements provided superior tissue stability and greatly facilitated the skill-dependent steps. Unlike current stainings, our trichrome staining produced a broader color palette and sharply contrasted numerous organelles and ultrastructures in light microscopy. We leveraged these microtechnique advances through image segmentation and quantitative analysis in MATLAB and Adobe Photoshop to measure a wide range of morphometric and compositional features, thereby generating the histolome. To validate this workflow, we applied it comprehensively and systematically to several model plants and calculated their C 4 Kranz-anatomy level using a combination of characteristic histological features. The histolomes provided new insights into cellular functions and quantitative anatomical differentiation among species. The resin-based microtechnique and histolomic approach will help facilitate, standardize, and make plant histology research quantitative. GRAPHICAL ABSTRACT

Why it matches plant phenotyping methods樹脂包埋・染色・画像セグメンテーション・定量解析を統合し、植物組織の形態・構成特徴を抽出する新規ヒストロミクス手法を開発・検証しており、植物表現型取得が中心です。

abstractIn this work, we developed an easier microtechnique and a novel histolomic approach for the quantitative analysis of histological features.

Serial section videography (SSV): A low‐cost protocol for generating 3D reconstructions of internal plant structure →

Premise Analyzing structural changes along the length of an organ provides insight into its development. However, traditional histological methods are limited by intensive procedures and size restrictions. Micro-computed tomography (microCT) enables non-destructive internal imaging along the length of an organ, but high cost, technical complexity, and limited accessibility hinder widespread application. Here, we describe serial section videography (SSV), a new low-cost technique for generating three-dimensional (3D) reconstructions of internal plant anatomy using serial sectioning and open-source software. Methods and results SSV was applied to four fern rhizomes with varied gross morphology and diverse vascular architectures. Specimens were sectioned using a sliding microtome or a handheld blade, and imaged using either a digital camera or smartphone setup. Images were aligned using Fiji and segmented using 3D Slicer. The SSV method enabled continuous visualization of internal stem anatomy over several centimeters and is adaptable to both laboratory and field settings. Conclusions This protocol offers an alternative to microCT for generating 3D anatomical reconstructions, enabling researchers to examine development and structural variation across organs with minimal equipment and software. This accessible protocol reduces technical and financial barriers and is particularly well-suited for comparative studies of vascular tissues, advancing the study of plant anatomy and development.

Why it matches plant phenotyping methods植物器官内部構造を連続撮像・画像処理して3D形態を再構成する低コスト手法の開発と適用が中心であり、植物形態・解剖状態の取得法として収載対象。

abstractHere, we describe serial section videography (SSV), a new low-cost technique for generating three-dimensional (3D) reconstructions of internal plant anatomy using serial sectioning and open-source software.

Construction of a biocompatible supramolecular sensor for fluorescence imaging of Nitric oxide in plant tissues. →

Nitric oxide (NO) serves as a crucial signaling molecule regulating plant growth and stress responses, and its dynamic monitoring is crucial. This work presents a red-emitting aggregation-induced emission (AIE) supramolecular fluorescent sensor (β-CD/AIENAP) constructed through β-cyclodextrin encapsulation of organic AIE-active molecules (AIENAP). The extension of the material's conjugated structure red shifts the emission wavelength and improves the tissue penetration ability. Meanwhile, β-CD encapsulation restricts intramolecular motion, thereby enhancing fluorescence while improving biocompatibility and cell permeability. Density functional theory calculations verify both the luminescence mechanism and NO-responsive characteristics. The developed probe demonstrates rapid NO response (2 min) via specific triazole formation, exhibiting a large Stokes shift (180 nm), exceptional selectivity, and ultrahigh sensitivity (LOD = 77 nM). Through confocal imaging technology, the sensing system successfully realized the dynamic tracking of the dynamic spatial and temporal distribution of endogenous NO in plants, and systematically studied the NO response characteristics under different abiotic stresses in plants. Exogenous NO application experiments further validate stress resistance regulation. This study provides not only a novel nanosensor for plant NO detection but also an essential tool for analyzing NO signaling transduction and crop stress resistance mechanisms.

Why it matches plant phenotyping methods植物組織内の内生NOという生理状態を可視化・動態追跡する蛍光センサーを開発し、植物ストレス下で実証しており、表現型取得法が中心である。

abstractThis work presents a red-emitting aggregation-induced emission (AIE) supramolecular fluorescent sensor (β-CD/AIENAP) constructed through β-cyclodextrin encapsulation of organic AIE-active molecules (AIENAP).

Monochromatic X-ray fluorescence spectroscopy for major and trace element analysis in plant science applications →

Abstract Background and aims Determining elemental concentrations in plant tissues is crucial for any study on plant nutrition, physiology, contamination and food safety. However, existing methodologies based on acid digestion of samples coupled to inductively coupled plasma-atomic emission spectrometry (ICP-AES) or plasma-mass spectrometry (ICP-MS) are time-consuming and expensive. Methods This study introduces an innovative approach for the rapid and reliable analysis of light, transition, and heavy elements in plant samples using a novel monochromatic X-ray fluorescence (MXRF) spectrometer. Results The MXRF method was tested for the detection of 12 different elements, including light elements (K, Ca), transition metals (Mn, Fe, Co, Ni, Cu, Zn), metalloids (As, Se), and post-transition “heavy” elements (Tl, Pb), covering concentrations from 1 to 10,000 mg·kg −1 . The limits of detection and quantification ranged from 1.41 to 4.71 mg·kg −1 . The recovery rates varied from 84.74% to 89.34%, with intraday relative standard deviations (RSD) ≤ 2.31% and inter-day RSD ≤ 4.17%. A method-comparison study using 144 plant samples analysed by both MXRF and ICP-AES showed strong correlations ( R 2 > 0.87) for K, Ca, Mn, Fe, Co, Ni, Cu, Zn, As, Pb, and TI. Conclusions This study demonstrates the reliability of the MXRF technique for the quantification of K, Ca, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Pb, and Tl in plant samples. Given that MXRF can also be applied to the analysis of elemental concentrations in soil and water samples, future research will focus on refining and establishing methodologies for these sample types.

Why it matches plant phenotyping methods植物試料中の元素濃度という植物の生理・状態を測定するMXRF法を新規導入し、検出限界、再現性、回収率、ICP-AESとの比較で技術検証しているため、方法が中心的である。

abstractThis study introduces an innovative approach for the rapid and reliable analysis of light, transition, and heavy elements in plant samples using a novel monochromatic X-ray fluorescence (MXRF) spectrometer.

Development and validation of a portable X-ray fluorescence approach for quantifying silicon in plants →

Abstract Background and Aims: Portable X-ray fluorescence spectrometry (pXRF) has emerged as a robust analytical approach for elemental determination in plant tissues, enabling rapid, non-destructive, and reagent-free measurements. This study developed and validated an empirical calibration of pXRF for quantifying silicon (Si) in plants, using autoclave-induced digestion (AID) as the reference method. Methods A total of 374 samples from seven plant species (rice, maize, soybean, cowpea, sorghum, lettuce, and beet) were analyzed. Silicon concentrations obtained via AID ranged from 1.07 to 19.23 g kg − ¹ (mean = 4.48 g kg − ¹; coefficient of variation = 67%), reflecting substantial interspecific variability. Each sample was also analyzed by pXRF under optimized instrumental conditions, and a calibration model was constructed using 75% of the dataset to predict Si concentrations relative to AID values. Results The pXRF calibration exhibited a strong linear relationship with AID results (R² = 0.94; R = 0.97; p

Why it matches plant phenotyping methods植物組織中のケイ素濃度を測定するpXRF法の開発と、基準法との校正・検証が研究の中心であり、植物形質の測定法に該当する。

abstractThis study developed and validated an empirical calibration of pXRF for quantifying silicon (Si) in plants, using autoclave-induced digestion (AID) as the reference method.

Development and application of two-photon fluorescent probe for visual monitoring of isoprene in plants. →

As the main volatile organic compounds (VOCs), isoprene plays a dual role in plant stress protection and air pollution. However, its spatiotemporal dynamic monitoring in plants is insufficient, which limits environmental risk assessment. In this study, by systematically investigating the effects of the introduction of alkyne groups, maleimide groups and conjugated structures on the performance of probes, a probe (TPCM-π-M), with excellent two-photon properties was prepared. It showed good linear response in 1-240 ppm range with a detection limit of 0.2 ppm, enabling accurate detection of isoprene in various plant samples. In addition, the spatial distribution of endogenous isoprene in deep plant tissues and dynamic visual monitoring of isoprene under abiotic stress were achieved through two-photon imaging, overcoming the shortcomings of traditional single-photon imaging such as insufficient penetration depth. In particular, the dynamic regulation mechanism of plant isoprene metabolism under abiotic stress was revealed through the carotenoid/photorespiration inhibition model, and the correlation between the isoprene content in different flowers and their stress response ability was confirmed. This study provides technical support for analyzing the role of isoprene in plant metabolism and environmental adaptation, and has theoretical and applied value in plant physiology, pollution monitoring and biomedical imaging.

Why it matches plant phenotyping methods植物内イソプレンの定量・空間分布・ストレス応答を可視化する二光子蛍光プローブとイメージング法を開発し、植物試料で検証・応用しているため、表現型取得法が中心である。

abstracta probe (TPCM-π-M), with excellent two-photon properties was prepared

Automated 3D wheat tissue analysis using x-ray CT and deep learning →

Understanding wheat grain internal structures is critical for improving quality, pest resistance, and breeding efficiency. While X-ray computed tomography (CT) enables non-destructive 3D imaging, existing segmentation methods rely on manual intervention, introducing inefficiency and subjectivity. This study introduces the Residual Depthwise Separable Convolution and Vision Mamba U-Net (RDVM-UNet), an automated framework combining Depthwise Separable Convolution (DSConv) for efficient local feature extraction and Vision Mamba for global contextual modeling. Trained over 200 iterations, the model achieved a mean Intersection over Union (mIoU) of 95.4 % in segmenting wheat tissues (epidermis, embryo, endosperm). Validation across 10 varieties demonstrated robust generalizability (mIoU is 94.78 %) and rapid processing (9.65 s/grain). The framework generated 3D reconstructions, enabling precise quantification of morphological parameters (volume, surface area) critical for analyzing genetic-environmental-morphological relationships. By establishing a non-destructive, high-throughput pipeline, this work advances precision breeding, functional genomics, and trait optimization in cereal crops. RDVM-UNet bridges computational imaging and agricultural science, offering scalable solutions for crop phenotyping and quality enhancement.

Why it matches plant phenotyping methodsX線CT画像から小麦組織を自動分割・3D再構成し、形態形質を定量化する深層学習パイプラインの開発と品種横断検証が中心であり、植物表現型計測法に該当する。

abstractThis study introduces the Residual Depthwise Separable Convolution and Vision Mamba U-Net (RDVM-UNet), an automated framework combining Depthwise Separable Convolution (DSConv) for efficient local feature extraction and Vision Mamba for global contextual modeling.

Ion-selective electrodes: innovations for precision in vivo plant ion monitoring. →

Ion-selective electrodes (ISEs) are pivotal tools for real-time, non-destructive monitoring of ionic dynamics in living plants, addressing key challenges in agriculture, plant physiology, and environmental science. This review presents recent advancements in ISE-based in vivo detection technologies, with an emphasis on sensor architectures tailored for plant tissues, including screen-printed planar electrodes, flexible electrodes, microneedle electrodes, and microfluidic devices. These systems enable precise in situ quantification of essential ions and trace elements, providing valuable insights into fundamental physiological processes such as nutrient uptake, stress responses, and signal transduction. Building on current ISE fabrication techniques, the review is aimed at developing a more cohesive theoretical framework for their application in plant systems. Future directions focus on synergistic integration of wearable plant sensors to build comprehensive real-time monitoring systems, which could advance understanding of plant-environment interactions and help address global food security challenges.

Why it matches plant phenotyping methods植物体内イオン状態をリアルタイム・非破壊で測定するセンサー技術を中心に扱うレビューであり、植物生理状態のフェノタイピング手法レビューに該当する。

abstractThis review presents recent advancements in ISE-based in vivo detection technologies, with an emphasis on sensor architectures tailored for plant tissues

Label-Free Rapid Quantification of Abscisic Acid in Xylem Sap Samples Using Surface Plasmon Resonance. →

The phytohormone abscisic acid (ABA) plays a central role in organizing adaptive responses in plants to various abiotic stresses, helping the plant minimize the negative impact on growth and development. Rapid and direct detection of ABA is valuable for investigating plant responses to abiotic stress. In this work, we propose a novel label-free, non-competitive immunoassay for detecting and quantifying ABA easily and rapidly using a surface plasmon resonance (SPR) biosensor. The SPR sensor chip was functionalized with a commercial anti-ABA antibody, characterized for its affinity, binding kinetics, and specificity using the same platform. The direct assay demonstrated high specificity and sensitivity, with a calculated limit of detection of 1.36 ng/mL in buffer. The new immunosensor was applied to determine ABA concentrations directly in xylem sap samples from tomato plants subjected to abiotic stress (drought and high salinity) and was able to accurately reflect ABA levels corresponding to the applied stress. The results were comparable to the reference method, ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS), establishing this new immunosensor as a novel detection method for rapid and reliable monitoring of ABA levels associated with abiotic stress in tomato plants.

Why it matches plant phenotyping methods植物の干ばつ・高塩ストレスに関連するABA濃度を迅速測定するSPR免疫センサーを開発し、性能評価とUPLC-MS/MS比較検証を行っているため、植物の生理状態を取得する方法が中心である。

abstractwe propose a novel label-free, non-competitive immunoassay for detecting and quantifying ABA easily and rapidly using a surface plasmon resonance (SPR) biosensor.

Comparative assessment of genomic, phenomic, and metabolomic prediction models in biparental grapevine breeding populations →

Accelerating grapevine breeding for disease resistance and climate adaptation remains constrained by long generation cycles. We benchmarked genomic (SNP), phenomic (NIRS), and metabolomic (untargeted LC-MS) prediction for 24 agronomic traits in a biparental population phenotyped over three years. Seven statistical frameworks and four tissue x timepoint combinations (wood; vineyard leaves at budbreak and flowering; greenhouse leaves at flowering) were evaluated, together with feature-wise BLUPs across samples. Cross-year and cross-population analyses with two additional populations assessed temporal robustness and transferability. Genomic prediction was most accurate (up to r = 0.83), metabolomic prediction was intermediate (up to r = 0.59), and phenomic prediction was lowest (up to r = 0.39) despite its lower acquisition cost. Metabolite features were more heritable than NIR wavelengths, for which most unexplained variation remained residual under the fitted model. Multi-omics integration produced limited overall gains. These results support genomic selection as the primary approach, with metabolomic or phenomic screening considered only for traits and sampling designs that show reproducible predictive signal.

Why it matches plant phenotyping methodsブドウ育種集団の複数形質について、NIRSによるフェノミック測定を含む予測モデルを比較・検証し、交差年・集団で頑健性と転移性も評価しているため、形質推定法の技術的ベンチマークが中心である。

abstractWe benchmarked genomic (SNP), phenomic (NIRS), and metabolomic (untargeted LC-MS) prediction for 24 agronomic traits in a biparental population phenotyped over three years.

Label-free structural imaging of plant roots and microbes using third-harmonic generation microscopy →

Abstract Root biology is pivotal in addressing global challenges including sustainable agriculture and climate change. However, roots have been relatively understudied among plant organs, partly due to the difficulties in imaging root structures in their natural environment. Here we used microfabricated ecosystems (EcoFABs) to establish growing environments with optical access and employed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution. THG enabled us to observe key plant root structures including the vasculature, Casparian strips, dividing meristematic cells, and root cap cells, as well as subcellular features including nuclear envelopes, nucleoli, starch granules, and putative stress granules. THG from the cell walls of bacteria and fungi also provides label-free contrast for visualizing these microbes in the root rhizosphere. With simultaneously recorded 3PF signal, we demonstrated our ability to investigate root-microbe interactions by achieving single-bacterium tracking and subcellular imaging of fungal spores and hyphae in the rhizosphere.

Why it matches plant phenotyping methodsTHG/3PFによる根の構造を高時空間分解能でラベルフリー取得するイメージング手法を開発・実証しており、植物表現型取得が中心である。

abstractemployed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution

Monitoring the Uptake and Localization of Organic Compounds in Plant Tissues Using a Hydroponic 14C-radiolabelling Assay and Phosphor Imaging. →

Phytoremediation, the use of plants to mitigate environmental contaminants, offers a sustainable and cost-effective approach to cleaning contaminated sites. Developing methods that aid in elucidating the mechanisms behind plant uptake and metabolism of pollutants is crucial for improving phytoremediation practices. This article describes a method to assess the uptake and transformation of organic contaminants by plants using radiolabeled compounds. 14 C-labelled organic compounds, such as model 14 C-naphthenic acids, are used to trace their absorption, translocation, localization, and metabolism in plant tissues. We have previously used this method with multiple plant species, including Elymus trachycaulus and Salix interior. These observations are corroborated here with the model plant, Arabidopsis thaliana, grown hydroponically in modified Hoagland solutions. Radiolabel uptake was monitored via liquid scintillation counting and phosphor-imaging, which allows for visualization and quantification of radiolabeled compounds within plant tissues. This method details the preparation of plant materials, the use of radiolabeled compounds, and the process of analyzing the distribution and fate of contaminants within plants. The method also includes strategies for assessing compound exudation and allows for the evaluation of both plant uptake and translocation of environmental contaminants. This approach provides insight into plant-mediated remediation processes and can be applied to the study of a wide range of environmental contaminants and plant species.

Why it matches plant phenotyping methods植物組織における汚染物質の吸収・移行・局在を定量・可視化する放射標識およびホスファーイメージング法が中心で、植物の生理状態を測定する再利用可能な手法を詳述している。

abstractThis article describes a method to assess the uptake and transformation of organic contaminants by plants using radiolabeled compounds.

AnatomyArray: A high-throughput platform for anatomical phenotyping in plants →

The anatomy or the arrangement of cells often determines the organization and function of plant tissues. However, current methods in large-scale imaging and accurate quantification of anatomical traits face major limitations. To address these challenges, we introduce the AnatomyArray system, an integrated platform for multiplexed tissue sectioning and anatomical phenotyping in plants. This system includes a highly adaptable device for high-throughput paraffin sectioning and multichannel slide imaging of various plant tissues, along with AnatomyNet, a deep learning tool for analyzing tissue-scale patterns of cell arrangement and morphology. AnatomyNet delivers accurate, automated quantification of anatomical traits at both the tissue and cellular levels, outperforming existing tools in image analysis. Using the AnatomyArray system, we dissected the genetic basis of root anatomy in a diverse wheat (Triticum aestivum L.) population through anatomics-based genome-wide association studies. Among the candidate genes identified, SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 14 (TaSPL14) was associated with stele and pericycle size in roots. Analysis of Taspl14 mutants confirmed that TaSPL14 plays a critical role in regulating root growth and tissue size by influencing phytohormone pathways. The AnatomyArray platform enables high-throughput characterization of cellular-level features and provides insights into the mechanisms shaping anatomical structure in plants.

Why it matches plant phenotyping methods植物組織の高スループット画像取得と、細胞・組織形態の自動定量を中核とするプラットフォームおよび解析ツールを開発しているため。

abstractwe introduce the AnatomyArray system, an integrated platform for multiplexed tissue sectioning and anatomical phenotyping in plants.

Defining cambial activity: the limitations of indirect indicators and the need for direct cellular markers →

The vascular cambium is a key lateral meristem responsible for secondary growth in woody plants, producing secondary xylem and phloem. Understanding its activity is crucial for studies on plant phenology, carbon sequestration, and environmental responses. However, defining the precise period of cambial activity remains challenging due to reliance on indirect indicators, such as cambial zone width or the presence of undifferentiated cells adjacent to the cambium. These parameters often misrepresent the true timing of cambial cell division, conflating it with subsequent differentiation processes. This study critically examines the limitations of indirect indicators and advocates for a more precise definition of cambial activity strictly as the process of cellular division. Direct cellular markers, such as mitotic figures, phragmoplasts, and newly formed tangential walls, provide more accurate assessment of cambial activity. By distinguishing cell division from differentiation, we can refine growth periodicity analyses and improve our understanding of environmental influences on cambial function. We review the structure and activity of the vascular cambium, demonstrating how indirect indicators can misrepresent cambial activity dynamics and lead to errors in determining its onset, duration, and cessation. By integrating direct cellular markers, we propose a more accurate methodology for assessing cambial activity, improving phenological studies and providing a clearer framework for evaluating plant responses to climatic variability.

Why it matches plant phenotyping methods形成層活動（細胞分裂）の評価方法を批判的に検討し、間接指標の限界と直接的な細胞マーカーを用いる改良方法を提案するレビューであり、植物状態の測定手法が中心です。

abstractDirect cellular markers, such as mitotic figures, phragmoplasts, and newly formed tangential walls, provide more accurate assessment of cambial activity.

Chiral Hierarchies at the Nanoscale Revealed by Three-Dimensional Scanning Electron Diffraction →

Natural biocomposites such as wood and plant cell walls exhibit prominent mechanical properties largely attributed to the nanoscale organization of fibrous components, such as cellulose, which often adopt chiral arrangements. However, resolving the three-dimensional (3D) arrangement of these structures at the nanoscale remains a significant challenge, particularly in beam-sensitive materials. This study introduces a method for 3D reconstruction of orientation based on scanning electron diffraction (SED), enabling the quantitative mapping of chiral supramolecular organization with sub-100 nm spatial resolution. By acquiring low-dose SED data at multiple tilt angles and applying a symmetry-based reconstruction algorithm, we resolved the 3D orientation of cellulose fibrils in native oat husk and birch wood. Our results reveal a multilayered cell wall architecture with alternating helical handedness, providing precise measurements of 3D fibril orientation. This method reveals complex hierarchical structures at the nanoscale, enabling rapid data acquisition and analysis using widely available instrumentation. The ability to resolve such chiral organization provides insights into material properties as well as opportunities for designing bioinspired materials with tunable mechanical and functional properties that extend far beyond natural biocomposite materials.

Why it matches plant phenotyping methods植物細胞壁のセルロース微繊維配向を定量的に再構成・測定する3D SED法が研究の中心であり、植物構造形質の取得手法に該当する。

abstractThis study introduces a method for 3D reconstruction of orientation based on scanning electron diffraction (SED), enabling the quantitative mapping of chiral supramolecular organization with sub-100 nm spatial resolution.

A database of plant heat tolerances and methodological matters →

Motivation Plant heat tolerance data are increasingly valued for their potential to help increase our understanding of species’ responses to extreme temperatures, but these efforts are hindered by methodological inconsistencies and missing contextual information. To address this issue, we collated data that compiles heat tolerance estimates and documents key sources of variation attributable to taxonomy, methodology, geography, and cultivation to improve data clarity and usability. This resource is designed to catalyze more rigorous and ecologically meaningful syntheses by enabling researchers to identify, account for, and test the drivers of variation in plant heat tolerances and their consequences. Main types of variable contained Heat tolerance estimated in degrees Celsius from photosynthetic tissue Spatial location and grain Global in scope with undersaturated taxonomic sampling and underrepresented geographic regions. Time period and grain 1935-2024 Major taxa and level of measurement Primarily vascular plants encompassing >1700 taxa, >1000 genera and >200 families. Software format Comma-separated values

Why it matches plant phenotyping methods植物の熱耐性という生理形質を体系的に収集・整理したデータベースであり、方法論の不一致や変動要因も記録する再利用可能なリソースであるため、フェノタイピングデータセットとして対象に含める。

abstractwe collated data that compiles heat tolerance estimates and documents key sources of variation attributable to taxonomy, methodology, geography, and cultivation

Root Anatomy: Preparing, Imaging, and Analyzing Maize Root Cross - Sections. →

Root anatomy plays a critical structural and functional role in the maize root system, and regulates edaphic stress tolerance. The function and genetic basis of several maize root anatomical traits for stress tolerance have been demonstrated. Leveraging root anatomical traits in maize thus holds great potential for developing cultivars with greater nutrient and water efficiency. Key for such approaches is the ability to characterize the root anatomy of plants of interest. Here, we outline a systematic method for preparing, imaging, and analyzing maize root cross-sections. The protocol describes root sectioning (by hand or using a vibratome), preparation of microscope slides and toluidine blue staining, imaging under a light microscope, and both manual and semiautomated methods for anatomical feature extraction from images. The protocol enables the visualization and quantification of various anatomical tissues and traits, and its simplicity, adaptability, and accessibility make it an ideal choice for both small- and large-scale phenotyping studies in maize and other plant species. This standardized protocol provides researchers with a comprehensive methodology to accurately dissect root structures, enabling in-depth analyses that are essential for understanding plant growth, development, and adaptive value for stress tolerance.

Why it matches plant phenotyping methodsトウモロコシ根の切片作製、顕微鏡画像化、画像からの解剖学的形質抽出を体系化したプロトコルであり、植物フェノタイピング手法が中心である。

abstractHere, we outline a systematic method for preparing, imaging, and analyzing maize root cross-sections.

Near-infrared spectroscopy as a high-throughput phenotyping method for fusiform rust resistance in loblolly pine →

Fusiform rust, caused by the pathogen Cronartium quercuum (Berk.) Miyabe ex Shirai f. sp. fusiforme, is the most important disease of loblolly pine (Pinus taeda L.) in the U.S., causing millions of dollars in damage each year. Using resistant genotypes has proven a successful strategy to limit the disease, but resistance selection still relies on visual inspection for symptoms, which can lead to misclassification due to human error and the presence of ‘escaped susceptibles’ (i.e., susceptible individuals with no visible symptoms due to either an extended asymptomatic phase of the disease or the lack of adequate disease pressure to become infected). Here, we propose the use of near-infrared (NIR) spectroscopy and chemometrics to improve the accuracy of how phenotypes are rated. We collected and analyzed phloem and needle spectra from 34 non-related families replicated across eight stands in three states in the southeastern region of the U.S. using a portable, handheld NIR spectrometer. We also used a benchtop Fourier-transformed mid-infrared (FT-IR) spectrometer to analyze phloem phenolic extracts of the same samples, as this phenotyping approach has proved successful in other pathosystems. Our results show a moderate association between the phloem spectra and resistance, and models built with NIR spectra were able to classify extremes (i.e., very resistant or very susceptible) with up to 69 ​% testing accuracy. This study provides a framework for using NIR spectroscopy for phenotyping loblolly pine resistance against pathogens and advocates for using alternative technologies in forestry.

Why it matches plant phenotyping methodsNIR分光法とケモメトリクスを用いたマツの病害抵抗性表現型評価法の開発・適用が中心であり、病徴の単なる測定ではない。

titleNear-infrared spectroscopy as a high-throughput phenotyping method for fusiform rust resistance in loblolly pine

Near-infrared spectroscopy as a high-throughput phenotyping method for fusiform rust resistance in loblolly pine. →

L.) in the U.S., causing millions of dollars in damage each year. Using resistant genotypes has proven a successful strategy to limit the disease, but resistance selection still relies on visual inspection for symptoms, which can lead to misclassification due to human error and the presence of 'escaped susceptibles' (i.e., susceptible individuals with no visible symptoms due to either an extended asymptomatic phase of the disease or the lack of adequate disease pressure to become infected). Here, we propose the use of near-infrared (NIR) spectroscopy and chemometrics to improve the accuracy of how phenotypes are rated. We collected and analyzed phloem and needle spectra from 34 non-related families replicated across eight stands in three states in the southeastern region of the U.S. using a portable, handheld NIR spectrometer. We also used a benchtop Fourier-transformed mid-infrared (FT-IR) spectrometer to analyze phloem phenolic extracts of the same samples, as this phenotyping approach has proved successful in other pathosystems. Our results show a moderate association between the phloem spectra and resistance, and models built with NIR spectra were able to classify extremes (i.e., very resistant or very susceptible) with up to 69 ​% testing accuracy. This study provides a framework for using NIR spectroscopy for phenotyping loblolly pine resistance against pathogens and advocates for using alternative technologies in forestry.

Why it matches plant phenotyping methodsNIR分光法とケモメトリクスを用いてマツのさび病抵抗性表現型を高スループット評価する方法を提案・検証しており、表現型取得が研究の中心である。

abstractHere, we propose the use of near-infrared (NIR) spectroscopy and chemometrics to improve the accuracy of how phenotypes are rated.

An activatable near-infrared probe for in situ monitoring of hydrogen peroxide in plant tissues →

Biotic and abiotic stresses can disrupt plant metabolic processes. This leads to the excessive accumulation of hydrogen peroxide (H₂O₂) in plants, which in turn induces oxidative stress. Therefore, detection of H₂O₂ is critical to understanding plant growth. In this study, we developed a naphthalene-based fluorescein near-infrared fluorescent probe (NAPF-AC) for the sensitive and selective detection of H₂O₂. Upon exposure to H₂O₂, the probe undergoes disruption of its push-pull electronic structure, triggering an intramolecular charge transfer process that allows for fluorescence-based detection. NAPF-AC exhibited excellent linearity (R² = 0.998) over a wide concentration range of H₂O₂ (0.1 to 100 μM), with a limit of detection (LOD) as low as 0.05 μM. In addition, NAPF-AC was successfully used for the in-situ detection of H₂O₂ in plant tissues. This study provides a powerful tool for studying H₂O₂ dynamics in plants and offers new insights into the mechanisms regulating plant growth and stress responses.

Why it matches plant phenotyping methods植物組織内のH₂O₂という生理状態を蛍光プローブで測定するセンサーを開発し、性能評価と植物組織での実証を行っており、測定法が研究の中心である。

abstractwe developed a naphthalene-based fluorescein near-infrared fluorescent probe (NAPF-AC) for the sensitive and selective detection of H₂O₂.

Constant distance between leaf initiation sites permits non-destructive analysis of apical meristem activity during cactus shoot growth. →

Background and scope Trunks of saguaro cacti (Carnegiea gigantea) grow for many years, and during this time the shoot apical meristem (SAM) of each trunk not only grows in diameter, it also initiates new orthostichies (ribs). Several questions were examined. Is a saguaro SAM's diameter correlated with the number of orthostichies/ribs it is producing? Is SAM diameter tightly controlled, or does it vary among individuals of the same age? When saguaro trunks are ~3 m tall, their SAMs stop adding new orthostichies/ribs: do SAMs stop growing only after reaching a critical diameter, or do the SAMs vary in diameter when each stops growing? Methods Ribs were counted at various heights (corresponding to various ages) on saguaro plants in habitat. Shoot apical meristem diameter was measured by light microscopy in sectioned material. Shoot apical meristems of Echinocactus grusonii were also studied. Key results Shoot apical meristem diameter is strongly correlated with the number of ribs being maintained: the circumferential distance between newly initiated leaf primordia remains constant (145 ± 10.6 µm in C. gigantea; 193 ± 10.7 µm in E. grusonii) even as an SAM grows in diameter. An SAM's diameter and circumference can be estimated by counting the number of ribs it is maintaining. The diameter of each SAM of C. gigantea increases for many years but it eventually stabilizes; the final, stable diameter of each C. gigantea SAM varies from shoot to shoot. Conclusions Shoot apical meristem diameter in both species can be estimated non-destructively by simply counting the number of orthostichies/ribs the SAM is producing (or produced in the past). The growth rate of C. gigantea SAMs varies from plant to plant and can change with age. All C. gigantea SAMs stop increasing in diameter at some point, but that diameter varies from plant to plant.

Why it matches plant phenotyping methodsサボテンのシュート頂端分裂組織径という植物形態形質を、肋数から非破壊推定する測定法が研究の中心であり、手法の成立性と適用結果を示している。

abstractAn SAM's diameter and circumference can be estimated by counting the number of ribs it is maintaining.

Implantable Ion‐Selective Organic Electrochemical Transistors Enable Continuous, Long‐Term, and In Vivo Plant Monitoring →

The development of plant-specific biosensors holds the potential to uncover new insights into plant physiology and advance precision agriculture. Current sensing platforms mainly focus on broad plant phenotypes (e.g., elongation and hydration) and local environmental monitoring (e.g., temperature and moisture). Here, an ion-selective organic electrochemical transistor (IS-OECT) is introduced that enables real-time monitoring of variations in potassium ion concentration within the xylem of pine trees. This work demonstrates that the high sensitivity of the IS-OECT enables the detection of subtle variations in potassium ion concentrations in the xylem sap of living trees, and the high stability of the sensor allows for in vivo measurements over five weeks. Furthermore, the implantable sensors are fabricated using processes that are compatible with low-cost manufacturing (i.e., lithography-free). This sensing technology, therefore, has great potential to be a game-changer in precision forestry and could extend to precision agriculture and horticulture practices.

Why it matches plant phenotyping methods植物体内の木部カリウムイオン濃度を連続測定する埋込み型センサーを開発・実証しており、植物の生理状態取得が研究の中心である。

abstractHere, an ion-selective organic electrochemical transistor (IS-OECT) is introduced that enables real-time monitoring of variations in potassium ion concentration within the xylem of pine trees.

Spatially Resolved Plant Metabolomics →

Research and innovation in metabolomics tools to measure metabolite accumulation within plants have led to important discoveries with respect to the improvement of plant stress tolerance, development, and crop yield. Traditional metabolomics analyses have commonly utilized gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry, but these methods are often performed without regard for the spatial locations of metabolites within tissues. Methods for mass spectral imaging (MSI) have recently been developed to detect and spatially resolve metabolite accumulation and are rapidly being adopted on a wider scale. Since 2010, the number of publications incorporating mass spectral imaging has grown from approximately 80 articles to over 378 on a yearly basis, constituting an increase of at least 350% during this time frame. Spatially resolved metabolite accumulation data provides unique insights into the function and regulation of plant biochemical pathways. Mass spectral imaging is commonly paired with desorption ionization technologies, including matrix-assisted laser desorption ionization (MALDI) and desorption electrospray ionization (DESI), to generate accurate, spatially resolved metabolomics data from prepared tissue segments. Here, we describe the most recent advancements in sample preparation methods, mass spectral imaging technologies, and data processing tools that have been developed to address the limits of MSI technology. Additionally, we summarize recent applications of MSI technologies in plant metabolomics and discuss potential avenues for future research advancements within the plant biology community through the use of these technologies.

Why it matches plant phenotyping methods植物組織内の代謝物蓄積を空間的に測定する質量分析イメージング技術、試料調製、データ処理を中心にレビューしており、植物状態の取得手法が主題である。

abstractHere, we describe the most recent advancements in sample preparation methods, mass spectral imaging technologies, and data processing tools that have been developed to address the limits of MSI technology.

The mechanical properties of Arabidopsis thaliana roots adapt dynamically during development and to stress →

Mechanical properties of plant cells and tissues change dynamically, influencing plant growth, development, and interactions with the environment. Despite their central roles in plant life, current knowledge of how these properties change in vivo is very limited. Here we have combined Brillouin microscopy and molecular rotors to investigate stiffness, viscosity and porosity in living Arabidopsis thaliana seedling roots during differentiation and in response to stress and genetic manipulation. We found that mechanical properties change in a cell- and tissue-specific manner. The properties change dynamically during differentiation to support directional cell expansion. Cell-type-specific adaptations are induced within hours in response to stress or changes in cell wall metabolism. The findings form the foundation for future studies to characterize regulatory mechanisms linking biochemical signaling and mechanical properties.

Why it matches plant phenotyping methods生きた植物体での硬さ・粘性・多孔性をBrillouin顕微鏡と分子ローターにより測定する手法適用が研究の中核であり、植物の生理状態・組織特性を定量化している。

abstractHere we have combined Brillouin microscopy and molecular rotors to investigate stiffness, viscosity and porosity in living Arabidopsis thaliana seedling roots during differentiation and in response to stress and genetic manipulation.

Plant-Compatible Xenium In Situ Sequencing: Optimised Protocol for Spatial Transcriptomics in Medicago truncatula Roots and Nodules →

Elucidating the spatial and temporal regulation of gene expression during plant organogenesis is crucial for enabling precise crop improvement strategies that incorporate beneficial traits into crops while avoiding adverse effects. Root nodules, specialised organs formed in symbiosis with nitrogen-fixing bacteria, provide a valuable system to study cell-type-specific gene networks in a symbiosis-induced developmental context. However, capturing these dynamics at cellular resolution in intact plant tissues remains technically challenging. Spatial transcriptomics technologies developed for animal systems are often not directly transferable to plant tissues due to fundamental differences in tissue composition between plants and animals, including rigid and heterogeneous plant cell walls, high cell wall autofluorescence, and large vacuoles in plant cells that complicate probe access and signal detection. To address these challenges, we present an optimised protocol for applying the Xenium in situ sequencing platform to formalin-fixed paraffin-embedded (FFPE) sections of plant tissues, including Medicago truncatula roots and nodules. Key technical adaptations include customised tissue preparation, optimised section thickness, hybridisation conditions, post-Xenium staining, imaging, and downstream image analysis, all tailored specifically for plant samples. To mitigate autofluorescence and enhance detection sensitivity, we employed a strategic approach to codeword selection during probe design. Furthermore, we developed a modular probe design approach combining a custom 380-gene standalone panel with a 100-gene add-on panel. This design allows flexibility for addressing diverse research questions and includes orthologous gene sequences from two Medicago ecotypes, ensuring compatibility for downstream functional validation using mutant lines available in both genetic backgrounds. We validated the protocol across nodules at multiple developmental stages using both the 50-gene panel targeting mature nodule cell identity and the extended 480-gene panel, which includes markers across different cell types and developmental stages, as well as genes of interest identified from prior single-cell and bulk RNA-seq analyses. This optimised workflow provides a reproducible and scalable method for high-resolution spatial transcriptomics in plant tissues, establishing a robust foundation for adaptation to other plant species and developmental systems.

Why it matches plant phenotyping methods植物組織向け空間トランスクリプトミクスの技術適応・最適化と検証が研究の中心であり、植物器官の細胞状態を高解像度で取得する再現可能なワークフローを開発している。

abstractwe present an optimised protocol for applying the Xenium in situ sequencing platform to formalin-fixed paraffin-embedded (FFPE) sections of plant tissues, including Medicago truncatula roots and nodules.

Thermography reveals the potential of traditional bean varieties against common bacterial blight →

Abstract The common bean ( Phaseolus vulgaris L.) is of great socioeconomic importance in Brazil, being widely cultivated by family farmers who preserve traditional varieties adapted to regional conditions. These varieties represent a strategic source of genetic variability for breeding programs. Among the main phytosanitary obstacles to cultivation, common bacterial blight (CBB), caused by Xanthomonas phaseoli pv. phaseoli stands out as it compromises bean productivity. This study aimed to evaluate 54 traditional genotypes for resistance to CBC, using visual severity scales and infrared thermography as a complementary tool. The experiment was carried out in a greenhouse, in a randomized block design with three replicates, in two seasons (May and October 2019). Inoculation was performed by two methods (cutting with scissors at 10⁷ CFU·mL -1 and infiltration with a syringe at 10⁶ CFU·mL -1 ) with the strain Xpp ‘139-y’. The variables analyzed included area under the disease progress curve (AUDPC), incubation period (IP), and final score (FS). Thermal images were obtained up to three days after inoculation, allowing the calculation of the mean temperature difference (MTD) between healthy and infected tissues. Thermographic analysis enabled early detection of infection, before the appearance of visual symptoms, distinguishing resistant genotypes such as BAC-6 and UENF 2599. The results highlight the potential of thermography as a fast, accurate, and non-destructive method for selecting resistant genotypes, contributing to the modernization and sustainability of bean breeding programs.

Why it matches plant phenotyping methods赤外線サーモグラフィーで感染植物組織の温度差を測定し、視覚症状前の病害状態を推定する方法を、抵抗性選抜へ実質的に適用しているため含める。

abstractusing visual severity scales and infrared thermography as a complementary tool

Panoptic segmentation for complete labeling of fruit microstructure in 3D micro-CT images with deep learning. →

Metabolic processes in plant organs involving transport of water, metabolic gasses, and nutrients depend on the three-dimensional (3D) microscopic tissue morphology. However, imaging and quantifying this microstructure, including the spatial layout of parenchyma cells, pores, vascular bundles and special features such as stone cell clusters (brachysclereids), is challenging. To address this, a 3D deep learning-based panoptic segmentation model, combining semantic and instance segmentation, was developed to accelerate and improve microstructure characterization of apple and pear fruit tissue in X-ray micro-computed tomography (CT) images. In addition, various training datasets and data augmentation techniques, including synthetic data, were explored to enhance segmentation quality. The 3D panoptic segmentation achieved an Aggregated Jaccard Index of 0.89 and 0.77 for apple and pear tissue, respectively, outperforming both the previously designed 2D instance segmentation model and a marker-based watershed segmentation benchmark. The model successfully labeled vascular bundles with a Dice Similarity Coefficient (DSC) of 0.51 in apple tissue and 0.79 in pear tissue, although thin vasculature in apple remained more challenging to segment. The 3D panoptic segmentation model achieved a DSC of 0.81 and effectively segmented stone cell clusters in pear tissue. Despite evaluating different methods to enhance segmentation quality, none improved test performance beyond that of the model trained on the standard dataset. The proposed 3D panoptic segmentation model offers the most complete automated protocol to date for plant tissue labelling and morphometric quantification from native X-ray micro-CT images, without extensive sample preparation such as contrast labelling. The developed method, if not replaces, drastically accelerates conventional human-in-the-loop analysis of such images.

Why it matches plant phenotyping methods植物組織の3DマイクロCT画像から微細構造を自動セグメンテーションし、形態計測する手法の開発・比較検証が中心であるため。

abstracta 3D deep learning-based panoptic segmentation model, combining semantic and instance segmentation, was developed to accelerate and improve microstructure characterization of apple and pear fruit tissue in X-ray micro-computed tomography (CT) images.

Assessing olive tree (Olea europaea L.) responses to water shortage through radio frequency sensors →

This study presents the application of advanced radio frequency (RF) sensors for non-invasive, plant structure-specific water stress monitoring in olive trees (Olea europaea L.), focusing on the cultivars Frantoio and Leccino, known for their differing water-use strategies. The sensing system comprises circular and double-layer rectangular spiral RF sensors, optimised to maximise the quality factor (Q-factor) for enhanced sensitivity. The double-layer design, where one layer is “left-handed” and the other “right-handed,” allows for an increased magnetic field and detection reliability, especially on small branches where signal stability can be challenging. Throughout an 88-day experimental period, olive trees were subjected to full irrigation (FI) and deficit irrigation (DI) treatments. RF sensors were placed on the olive plants trunks and branches to capture plant structure-specific stress responses, with measurements recorded weekly. In the Frantoio cultivar, resonance frequency shifts were pronounced under DI, especially in the trunk and large branches, where notable physiological changes were observed. Correlations were established between resonance frequency data and morpho-physiological indicators such as trunk diameter increment (SDI) and fresh water content (FWC), validating the sensor’s sensitivity to dielectric property variations due to water stress. Anatomical analyses further revealed tissue adaptations in Frantoio under DI, including increased bark and cortex thickness and intensified sclerenchyma fibre formation, indicative of structural changes to support water transport. In contrast, the Leccino cultivar showed minimal frequency variations and lacked significant anatomical alterations, reflecting its conservative water-use strategy and limited sensitivity to stress. This research confirms RF sensors’ potential as precise tools for early water stress detection in olive trees, with an emphasis on sensor placement on main plant structures and sensitivity optimization to enhance accuracy. These findings support the use of RF sensing systems in precision agriculture for sustainable irrigation management, especially in water-limited environments and conditions.

Why it matches plant phenotyping methodsRFセンサーによるオリーブ樹の水ストレス検出法を開発・最適化し、植物構造別の測定と形態・生理指標との相関で妥当性を検証しているため、フェノタイピング手法が中心である。

abstractThis study presents the application of advanced radio frequency (RF) sensors for non-invasive, plant structure-specific water stress monitoring in olive trees (Olea europaea L.)

Expanding plant cell microscopy through artificial intelligence focusing on segmentation and virtual staining →

Fluorescence imaging has become a central tool in plant cell biology, enabling detailed analysis of cellular structures and dynamics. However, challenges such as phototoxicity, photobleaching, and the invasiveness of fluorescent labeling have driven the development of artificial intelligence (AI)-based alternatives. Among these, deep learning-based segmentation and virtual staining have shown significant promise for advancing plant cell microscopy. Compared with traditional methods reliant on manual operations or simple thresholding algorithms, segmentation powered by AI-based image transformation offers enhanced accuracy and reproducibility in quantifying cellular features. Moreover, virtual staining transforms bright-field images into synthetic fluorescence images, enabling non-invasive, high-resolution analyses while bypassing the need for physical labeling. Together, these techniques expand the analytical capabilities of plant cell microscopy, facilitating efficient and precise imaging workflows. Despite their potential, these approaches face technical challenges. Virtual staining relies heavily on high-quality bright-field images and is currently constrained when applied to three-dimensional analyses of complex plant tissues. Future efforts must focus on developing diverse training datasets and advancing AI technologies to overcome these limitations. By offering automated segmentation and virtual staining, AI is transforming plant cell microscopy into a more versatile and powerful tool, paving the way for groundbreaking discoveries and broader applications in plant cell biology.

Why it matches plant phenotyping methods植物細胞画像におけるAIセグメンテーションと仮想染色を扱うレビューで、細胞特徴の定量化と再現性向上を目的とした画像解析手法が中心である。

abstractdeep learning-based segmentation and virtual staining have shown significant promise for advancing plant cell microscopy.

Imaging of specialized plant cell walls by improved cryo-CLEM and cryo-electron tomography →

Cryo-focused ion beam scanning electron microscopy (cryo-FIBSEM) has become essential for preparing electron-transparent lamellae from cryo-plunged and high-pressure frozen specimens. However, targeting specific cellular features within large, complex organs remains challenging. Here we present a series of technical improvements significantly enhancing the efficiency and accessibility of the Serial Lift-Out and SOLIST (Serialized On-grid Lift-In Sectioning for Tomography) procedures that are revolutionizing the field. We were able to extend the cryo-FIBSEM session from 24 hours to 5 days without interruptions. In addition, we describe a modified silver-plated EasyLift TM needle that eliminates the need of the copper or gold block between the original tungsten needle and the sample. Moreover, we describe a strategy that significantly reduces curtaining effects. Finally, we report a precise routine to target a lamella with a precision of approximately 1 micrometer in X,Y and Z. Together, these modifications considerably reduce contamination risk and preparation time, making cryo-lift-out techniques more accessible for routine structural biology applications on any type of tissue. Here, we demonstrate the power of our technique by targeting several specific wall structures that are of crucial importance for root function in plants and that were previously inaccessible to cryo-electron tomography (cryo-ET). High-pressure freezing (HPF) of plant tissues presents unique challenges for cryo-electron microscopy sample preparation due to the overall sample size, the individual cells size, their rigid cell wall and finally, their large vacuoles, which contain large amounts of rather diluted water solutions compared to cytosol. The internal root structures targeted are the Casparian strip (CS), suberin lamellae (SL), as well as secondary wall of xylem vessels, requiring reaching a targeting precision of 5 micrometers in a 3 millimeters long and 80-120 micrometers thick root tip. Our technological improvements for the cryo-correlative light and electron microscopy (cryo-CLEM) workflow enabled successful, targeted cryo-ET in plant roots. We noticed that, despite ice formation in vacuoles and to some degree in the cytosol, the plasma membranes and cell walls are remarkably well preserved, providing stunning insights into the native, hydrated nano-structure of plant cell walls, previously only observable with contrasting agents and in a dehydrated state.

Why it matches plant phenotyping methods植物根の細胞壁構造を対象とするcryo-CLEM/cryo-ETワークフローの技術改良と実証が中心であり、植物組織の構造的表現型を画像取得する方法論に該当する。

abstractOur technological improvements for the cryo-correlative light and electron microscopy (cryo-CLEM) workflow enabled successful, targeted cryo-ET in plant roots.

XFruitSeg—A general plant fruit segmentation model based on CT imaging →

Identification of the phenotypes of fruits is critical for understanding complex genetic traits. Computed tomography (CT) imaging technology enables the noninvasive acquisition of three-dimensional images of fruit interiors, thus providing a robust data foundation for phenotypic analysis. Accurate segmentation of internal fruit tissues is essential, as it directly influences the accuracy and reliability of the results. Current methods are not optimized for the unique features of plant fruit images. This study introduces XFruitSeg, which is a general deep learning model for segmenting plant fruit CT images. The model uses a U-shaped encoder–decoder architecture and integrates multitask learning. A large convolutional kernel network, RepLKNet, expands the receptive field for feature extraction. Multiscale skip connections and a deep supervision mechanism improve the model's capacity to learn features of various sizes, and a contour feature learning branch specifically targets the interorganizational boundaries. An optimized composite loss function enhances the model's robustness when applied to imbalanced categories. Additionally, a dataset named XrayFruitData was established, which contains high-resolution images of twelve plant fruit varieties, with accurate annotations for orange, mangosteen, and durian fruits for model evaluation. Compared with four mainstream advanced models, XFruitSeg achieved superior segmentation performance on the orange, mangosteen, and durian datasets, with mean Dice coefficients of 95.21 ​%, 93.24 ​%, and 94.70 ​% and mean intersection over union (mIoU) scores of 91.09 ​%, 87.91 ​%, and 90.35 ​%, respectively. The results of extensive ablation experiments demonstrate the effectiveness of each component. Therefore, the proposed XFruitSeg model has been proven to be beneficial for high-precision analysis of internal fruit phenotyping traits.

Why it matches plant phenotyping methods果実CT画像から内部組織を抽出するセグメンテーション手法を開発し、データセット構築と性能比較・検証を行っており、植物表現型取得の方法が中心である。

abstractThis study introduces XFruitSeg, which is a general deep learning model for segmenting plant fruit CT images.

Methods to Observe Plant Tissue Colonization by Fusarium oxysporum. →

Fusarium oxysporum, an important soil-borne pathogen, causes vascular wilts in more than 100 plant species, leading to billions of dollars in annual yield losses. Controlling Fusarium wilt diseases is challenging due to the persistence of pathogen spores in infested fields and the growing resistance to available fungicides. Understanding the molecular interactions between F. oxysporum and its host plants is crucial for developing novel control strategies, but studying these interactions is difficult because F. oxysporum invades plant roots long before wilt symptoms can be detected in above-ground tissues. To illuminate the hidden interactions between F. oxysporum and its plant hosts, we present three confocal microscopy protocols for visualizing fungal colonization in plant tissues and the associated plant responses. The first protocol employs wheat germ agglutinin-Alexa Fluor 488 and propidium iodide to stain fungal cells and plant host tissues, respectively. The second uses sirofluor to detect deposition of callose, a (1,3)-β-glucan polymer found in plant cell walls that plays a significant role in plant defense. The third utilizes fluorescent protein-tagged fungal isolates and a stable transgenic Arabidopsis thaliana line, providing a clean and easily accessible system for visualizing early infection stages. The protocols described here will shed light on underground plant-pathogen interactions, aiding researchers in unraveling the complex dynamics between diverse F. oxysporum pathotypes and their plant hosts.© 2025 Wiley Periodicals LLC. Basic Protocol 1: Observation of F. oxysporum cells in the tomato stem vasculature Basic Protocol 2: Observation of callose deposition in F. oxysporum-colonized tomato plant roots Basic Protocol 3: Observation of fungal colonization in an F. oxysporum-A. thaliana model system.

Why it matches plant phenotyping methods植物組織内の病原菌定着、植物組織、カロース沈着および感染応答を可視化する3種の共焦点顕微鏡プロトコルが研究の中心であり、植物の病態・応答の画像取得法に該当する。

abstractwe present three confocal microscopy protocols for visualizing fungal colonization in plant tissues and the associated plant responses.

Review of plant exposure analysis and monitoring methods for chemical warfare agents →

Abstract The Organization for the Prohibition of Chemical Weapons (OPCW) enforces strict regulations on the production, storage, and use of chemical warfare agents (CWAs). However, in recent decades, terrorist incidents involving the use of CWAs have remained frequent, posing a persistent and serious threat to global security. Plants have emerged as a promising medium for detecting CWAs exposure or toxic chemical leaks due to their wide availability, straightforward sample preparation, and the absence of ethical concerns associated with animal testing. When plants are exposed to CWAs or toxic chemicals, various components within their tissues can react with these agents, generating specific biomarkers of exposure; the detection of these biomarkers enables accurate traceability of CWAs exposure. Furthermore, when plants are subjected to stress from external toxic substances, their phenotypic characteristics undergo significant changes. These changes can be non‐destructively analyzed using hyperspectral imaging (HSI) technology, offering rapid monitoring and early warning for laboratory analysis of chemical exposure or toxic chemical leaks. This article presents a comprehensive review of the detection of metabolites and adducts produced in plants exposed to sulfur mustards, nitrogen mustards, sarin (GB), soman (GD), VX, Russian VX (RVX), and chlorine, as well as the monitoring of plant phenotypic changes using HSI technology over the past decade. The review aims to inspire further discoveries of novel plant biomarkers and inform research related to plant exposure to CWAs.

Why it matches plant phenotyping methods植物曝露モニタリング手法のレビューであり、HSIによる植物表現型変化の非破壊モニタリングを明示的に扱うため、フェノタイピング手法レビューとして中心的です。

abstractThis article presents a comprehensive review of the detection of metabolites and adducts produced in plants exposed to sulfur mustards, nitrogen mustards, sarin (GB), soman (GD), VX, Russian VX (RVX), and chlorine, as well as the monitoring of plant phenotypic changes using HSI technology over the past decade.

Optimized routing algorithm with AlexNet-ShuffleNet for plant leaf disease and infectious classification in IoT →

In agriculture, utilizing images to detect plant leaf diseases is a vital area in precision farming. Typically, trained professionals physically inspect plant tissues to identify disease range. Nowadays, AI has made foremost paces in detecting and classifying plant diseases. Moreover, Internet of Things (IoT) has several applications, containing Agricultural-IoT (AIoT), which is considered to elevate agricultural yields. This paper intends to develop an approach in IoT for plant disease classification. Initially, simulation of IoT is done and the IoT nodes route sensed plant leaf images by proposed Serial Exponential Golf Optimization Algorithm (SEGOA), which is established by modifying Golf Optimization Algorithm (GOA) using Exponential Weighted Moving Average (EWMA) to the destination, where plant leaf disease detection is executed. To extract the RoI, CNN is used to discover diseased part in plant leaf. Then, plant leaves are classified as healthy and diseased subclasses by employing AlexNet-ShuffleNet. Moreover, the disease types are classified more into fungal/bacterial/viral infection using the AlexNet-ShuffleNet. Performance of adopted work is assessed by utilizing the metrics, such as energy, accuracy, sensitivity, and specificity. Overall outcome of AlexNet-ShuffleNet give a promising result, such as accuracy of 94.6%, sensitivity of 98.7% and specificity of 94%.

Why it matches plant phenotyping methods植物葉画像から病変部位を抽出し、健全・罹病状態および病原タイプを分類する画像ベースの植物病害表現型解析手法が研究の中心である。

abstractThis paper intends to develop an approach in IoT for plant disease classification.

An activatable near-infrared probe for in situ monitoring of hydrogen peroxide in plant tissues. →

Biotic and abiotic stresses can disrupt plant metabolic processes. This leads to the excessive accumulation of hydrogen peroxide (H 2 O 2 ) in plants, which in turn induces oxidative stress. Therefore, detection of H 2 O 2 is critical to understanding plant growth. In this study, we developed a naphthalene-based fluorescein near-infrared fluorescent probe (NAPF-AC) for the sensitive and selective detection of H 2 O 2 . Upon exposure to H 2 O 2 , the probe undergoes disruption of its push-pull electronic structure, triggering an intramolecular charge transfer process that allows for fluorescence-based detection. NAPF-AC exhibited excellent linearity (R 2 = 0.998) over a wide concentration range of H 2 O 2 (0.1 to 100 μM), with a limit of detection (LOD) as low as 0.05 μM. In addition, NAPF-AC was successfully used for the in-situ detection of H 2 O 2 in plant tissues. This study provides a powerful tool for studying H 2 O 2 dynamics in plants and offers new insights into the mechanisms regulating plant growth and stress responses.

Why it matches plant phenotyping methods植物組織内のH₂O₂という生理状態をin situで検出する蛍光プローブを開発し、植物での適用まで検証しており、測定法が中心的です。

abstractwe developed a naphthalene-based fluorescein near-infrared fluorescent probe (NAPF-AC) for the sensitive and selective detection of H 2 O 2

Toward routine basil (Ocimum basilicum L.) callus culture analysis using non-destructive Raman spectroscopy. →

Here we investigated whether FT-Raman spectroscopy could be used to detect biochemical changes in small-leaved basil (Ocimum basilicum L. var. minimum Alef.) callus culture (CC). To address the effect of culture conditions and elicitor treatments, CC established on 1 mg L -1 2,4-D + 0.5 mg L -1 BAP, or 2.5 mg L -1 NAA + 0.5 mg L -1 KIN was exposed to various spectral light treatments during four weeks and compared to those grown in dark. The composition of CC was analysed both using an FT-Raman spectrometer equipped with laser 1064 nm, and spectrophotometrically. The spectral composition of light had a higher influence on the chemical composition of CC grown on NAA + KIN than on 2,4-D + BAP medium. Spectrophotometrically, no differences in the content of protein or sugar were determined in relation to the plant growth regulators applied. However, significant differences in frequencies and intensities of vibrational bands associated with proteins (S-S disulfide stretching, tyrosine, cystine, and methionine at lower spectral ranges, and amide III stretching in the higher spectral range), and carbohydrates (C-O-C skeletal mode at lower spectral ranges, and C-O-H vibrations at higher spectral ranges) within the Raman spectra were estimated and discussed. The 1525 cm -1 and 1606 cm -1 peaks with high intensities of vibration bands were identified and assigned to carotenoids and phenolics. In all treatments applied the major Raman peaks were detected at 1606, 1629, and 1633 cm -1 . PCA analysis showed that CC under blue-red light and blue-red light + UVa (2,4-D + BAP) had higher content of carotenoids and ester groups, while chlorophyll a and phenolics were found in CC grown on NAA + KIN under blue-red light + UVa and blue-red light + far-red. Compared to traditional methods of analysis, which are preceded by the sample destruction before extraction and analysis, it can be concluded that the FT-Raman spectroscopy may serve as a valuable tool for the non-destructive and non-invasive identification of major biochemical changes in basil CC without any sample preparation.

Why it matches plant phenotyping methodsバジルカルスの生化学的状態を非破壊的に推定するFT-Raman法自体が研究の中心であり、従来法との比較を通じて実用性を検討しているため、植物フェノタイピング手法として含める。

abstractHere we investigated whether FT-Raman spectroscopy could be used to detect biochemical changes in small-leaved basil (Ocimum basilicum L. var. minimum Alef.) callus culture (CC).

Camelot: a computer-automated micro-extensometer with low-cost optical tracking. →

Background Plant growth and morphogenesis is a mechanical process controlled by genetic and molecular networks. Measuring mechanical properties at various scales is necessary to understand how these processes interact. However, obtaining a device to perform the measurements on plant samples of choice poses technical challenges and is often limited by high cost and availability of specialized components, the adequacy of which needs to be verified. Developing software to control and integrate the different pieces of equipment can be a complex task. Results To overcome these challenges, we have developed a computer automated micro-extensometer combined with low-cost optical tracking (Camelot) that facilitates measurements of elasticity, creep, and yield stress. It consists of three primary components: a force sensor with a sample attachment point, an actuator with a second attachment point, and a camera. To monitor force, we use a parallel beam sensor, commonly used in digital weighing scales. To stretch the sample, we use a stepper motor with a screw mechanism moving a stage along linear rail. To monitor sample deformation, a compact digital microscope or a microscope camera is used. The system is controlled by MorphoRobotX, an integrated open-source software environment for mechanical experimentation. We first tested the basic Camelot setup, equipped with a digital microscope to track landmarks on the sample surface. We demonstrate that the system has sufficient accuracy to measure the stiffness in delicate plant samples, the etiolated hypocotyls of Arabidopsis, and were able to measure stiffness differences between wild type and a xyloglucan-deficient mutant. Next, we placed Camelot on an inverted microscope and used a C-mount microscope camera to track displacement of cell junctions. We stretched onion epidermal peels in longitudinal and transverse directions and obtained results similar to those previously published. Finally, we used the setup coupled with an upright confocal microscope and measured anisotropic deformation of individual epidermal cells during stretching of an Arabidopsis leaf. Conclusions The portability and suitability of Camelot for high-resolution optical tracking under a microscope make it an ideal tool for researchers in resource-limited settings or those pursuing exploratory biomechanics work.

Why it matches plant phenotyping methods植物試料の力学的形質（弾性、クリープ、降伏応力、剛性、変形）を光学追跡で測定する装置とソフトウェアを開発しており、植物表現型の取得手法が研究の中心である。

abstractwe have developed a computer automated micro-extensometer combined with low-cost optical tracking (Camelot) that facilitates measurements of elasticity, creep, and yield stress.

Non-destructive monitoring of tissue-specific, irrigation responsive impedance signals in leaves using microneedles probes →

A non-destructive methodology for monitoring impedance changes in sorghum leaves was developed and recorded irrigation-dependent responses that differed between leaf tissues. Metal microneedles were used as impedance probes and were shown to cause minimal damage to the plant. The needles were placed on either the abaxial or adaxial side of the leaf midrib using small clamps and re-used hundreds of times with minimal signs of wear. Cross-sectional images verified the precision of microneedle placement near vascular bundles on the abaxial surface and in non-vascular hydrenchyma on the adaxial surface. Impedance measurements with microneedles displayed a significant decrease in resistance compared to planar electrodes due to bypassing the epidermal layer. A tissue-specific impedance response was seen in relation to irrigation where the non-vascular adaxial surface remained largely stable throughout a day of measurement, while impedance increased in the vascular abaxial surface during exposure to light and decreased following watering. Impedance data were also compared with simultaneous gas exchange measurements of photosynthesis and transpiration.

Why it matches plant phenotyping methodsソルガム葉の組織特異的な水分・生理応答を非破壊インピーダンス測定で取得する手法を開発し、電極比較や配置精度、再利用性も検証しているため、植物フェノタイピング手法が中心である。

abstractA non-destructive methodology for monitoring impedance changes in sorghum leaves was developed

Rapid detection and imaging of methylglyoxal in plant tissues by the near-infrared fluorescent probe SWJT-2 →

Methylglyoxal (MG) can be produced via various pathways in plants. MG is toxic for plant cells at high levels, however it acts as a signaling molecule at low levels, just as H 2 O 2 in plants. Therefore, MG detection is very important for investigating its roles in plant cells, especially in plants under environmental stresses. The near-infrared fluorescent probe SWJT-2 is a novel probe with high sensitivity for the rapid detection of MG in human HeLa cells, but at present it is not clear whether the probe can be used to determine MG levels in plant tissues. In this present research, we tried to apply the probe in plant research. Our results showed that 40 min treatment of SWJT-2 (80 μM) can be applied to the detection and imaging of MG levels in tobacco (Nicotiana benthamiana) tissues.

Why it matches plant phenotyping methods植物組織中のメチルグリオキサール濃度を近赤外蛍光プローブで検出・画像化する手法の植物への適用が中心であり、植物の生理状態を測定するフェノタイピング手法に該当する。

abstractThe near-infrared fluorescent probe SWJT-2 is a novel probe with high sensitivity for the rapid detection of MG in human HeLa cells, but at present it is not clear whether the probe can be used to determine MG levels in plant tissues.

Three-dimensional interaction between Cinnamomum camphora and a sap-sucking psyllid insect (Trioza camphorae) revealed by nano-resolution volume electron microscopy. →

Phloem-feeding insects present significant economic threats worldwide and remain challenging to understand due to their specialized feeding strategies. Significant advances in genetics, genomics, and biochemistry have greatly enriched our comprehension of phloem-insect interactions. However, existing studies relying on two-dimensional discrete images have limited our understanding of visible morphological details. In this study, we leverage volume electron microscopy (vEM) technology to unveil a nanometer-resolution interaction mode between plant and the phloem-feeding insect, Camphor psyllid (Trioza camphorae, Hemiptera: Psyllidae). The stylets penetrate each cell on the way to the feeding site (sieve tube), and new cell walls will form around the salivary sheath, ultimately fusing with the original cell walls to form remarkably thickening cell walls. Our reconstruction findings on pit gall tissues suggest that a significant decrease in cell volume and a drastic increase in cell layers are the primary processes during pit gall formation. These unique findings will set the stage for a robust discussion on the plant cellular response induced by phloem-feeding insects.

Why it matches plant phenotyping methodsvEMによるナノメートル分解能の3次元画像取得と再構築が研究の中心で、植物組織の細胞体積や細胞層数などの形態状態を定量化しているため、画像ベースの植物フェノタイピング応用に該当する。

abstractwe leverage volume electron microscopy (vEM) technology to unveil a nanometer-resolution interaction mode between plant and the phloem-feeding insect

A microneedle sensor for in-vivo sodium ion detection in plants. →

This study introduces a novel microneedle-type potentiometric sensor designed for the in-vivo detection of sodium ions (Na + ) in plant tissues. The development of this sensor is crucial for advancing our understanding of plant responses to salinity stress. The microneedle sensor employs a highly selective Na + ion carrier and integrates a solid-contact layer made of poly(3,4-ethylenedioxythiophene)-poly (sodium 4-styrenesulfonate) (PEDOT: PSS) prepared by electropolymerization. Due to its excellent conductivity and high chemical stability, PEDOT:PSS significantly reduces the surface impedance of the electrode, enhances charge transfer efficiency, and thereby improves the sensor's response sensitivity and stability. The sensor achieves a linear detection range of 1 × 10 -2 to 1 × 10 -5 M, with a slope of 56.55 ± 0.25 mV/decade and a detection limit of 1.94 × 10 -6 M. The fabrication process was optimized by refining the membrane formulation, ensuring precise control over membrane thickness, and determining the optimal conditioning time, all essential for large-scale production and agricultural applications. In addition, we evaluated the sensor's ability to detect Na + concentration changes in both artificial culture media and actual plant tissue samples. The sensor's performance was assessed through its capability to monitor Na + concentration changes in both artificial culture media and real plant tissue samples, with results benchmarked against the standard method (ICP-OES), confirming its accuracy and reliability. Moreover, application trials involving rice seedlings validated the microneedle sensor's efficacy for in vivo detection of Na + , providing a robust tool for understanding plant physiological responses to salt stress. These findings not only offer new insights into plant adaptation mechanisms but also establish a practical platform for selecting salt-tolerant cultivars and enabling rapid salt-level assessment in agricultural practices.

Why it matches plant phenotyping methods植物体内のNa⁺濃度という生理状態を測定するマイクロニードルセンサーを開発し、ICP-OESとの比較およびイネ幼苗での実証を行っており、フェノタイピング手法が研究の中心である。

abstractThis study introduces a novel microneedle-type potentiometric sensor designed for the in-vivo detection of sodium ions (Na + ) in plant tissues.

Machine learning-assisted implantable plant electrophysiology microneedle sensor for plant stress monitoring →

Plant electrical signals serve as a medium for long-distance signal transmission and are intricately linked to plant stress responses. High-fidelity acquisition and analysis of plant electrophysiological signals contribute to early stress identification, thereby enhancing agricultural production efficiency. While traditional plant electrophysiology monitoring methods like gel electrodes can capture electrical signals on plant surfaces, which face limitations due to the plant cuticle barrier, impacting signal accuracy. Moreover, the vast and intricate nature of plant electrical signal data, coupled with the absence of specialized large-scale models, impedes signal interpretation and plant physiological correlation. In light of these challenges, we engineered an implantable microneedle array using micromachining technology for monitoring and decoding plant electrical signals in a minimally invasive manner. This innovative sensor can securely adhere to plant tissue over extended periods, enabling the precise recording of electrical signals triggered by transient (mechanical injury) and long-term stresses (drought and salt stress). Based on the collected plant electrophysiological data, we utilized a machine learning model to analyze these signals for the early detection of plant stress with an accuracy of 99.29%. This sensor has great potential and is expected to revolutionize precision agricultural production and provide valuable help in managing plant stress more effectively.

Why it matches plant phenotyping methods植物の電気生理信号を取得・解析する埋込型マイクロニードルセンサーと機械学習によるストレス状態推定が研究の中心であり、植物状態の表現型計測手法に該当する。

abstractwe engineered an implantable microneedle array using micromachining technology for monitoring and decoding plant electrical signals in a minimally invasive manner.

Feasibility of near-infrared spectroscopy as a tool to estimate carotenoid content in ‘IAC Rurik’ specialty potato cultivar →

The study explores the use of NIR spectroscopy with chemometric techniques as a non-destructive method to determine carotenoids in fresh ‘IAC Rurik,’ a new yellow potato rich in these compounds. Tubers were harvested in 2022 and in 2023. Reflectance FT-NIR spectra were acquired on the periderm of 200 tubers, in two positions. Spectra were pre-processed and regression models were developed using partial least square (PLS), support vector (SVR), ridge regression, k-nearest neighbors (KNN), interval-partial least squares (iPLS), and kernel-partial least squares (kPLS) regressions. Multivariate classification was carried out by applying principal component analysis with linear discriminant analysis (PCA-LDA) and partial least squares discriminant analysis (PLS-DA). Carotenoid content prediction was better obtained using mean-centered spectra and ridge regression (RMSEP = 0.0028 g kg⁻¹, R²P = 0.90, RPD = 2.57, RER = 4.21 %). The classification of three groups (low = 0.031–0.045 g kg⁻¹; average = 0.045–0.065 g kg⁻¹; and high = 0.065–0.078 g kg⁻¹) was possible by applying PLS-DA with a correct classification of 93 %, 70 %, and 86 %, respectively for low, average, and high carotenoid content. Thus, NIR spectroscopy can be used as a non-destructive method to predict carotenoids and classify ‘IAC Rurik’ tubers based on their carotenoid content.

Why it matches plant phenotyping methodsジャガイモ塊茎のカロテノイド含量という植物形質を、NIR分光とケモメトリクスで非破壊推定・分類する手法の開発および性能評価が中心である。

abstractThe study explores the use of NIR spectroscopy with chemometric techniques as a non-destructive method to determine carotenoids in fresh ‘IAC Rurik,’ a new yellow potato rich in these compounds.

"Light-Up" Near-Infrared Fluorescent Probe for Visualization of Hydrogen Sulfide Content and Abiotic Stress Response in Plants. →

Hydrogen sulfide (H 2 S) plays a vital role in plant physiology and stress adaptation, but the detection of endogenous H 2 S remains a challenge. In this work, a near-infrared fluorescent probe (NIR-BOD-HS) was synthesized using boron-dipyrromethene (BODIPY) as the raw material, which showed a good linear relationship in the concentration range of 0.1-70 μM and a detection limit of 56 nM. The long-wavelength emission (712 nm) reduced the interference of plant autofluorescence and improved the imaging quality. The probe combined with fluorescence imaging technology nondestructively realized the spatiotemporal distribution signal of H 2 S in the deep tissues of plants. In addition, the dynamic changes of H 2 S content during seed germination and seedling growth under abiotic stress were also demonstrated through the changes in fluorescence signals. This study helps to understand the physiological response mechanism of plants under abiotic stress and provides a scientific basis for further research on plant imaging and agricultural production.

Why it matches plant phenotyping methods植物体内H₂Sの時空間分布を非破壊的に可視化・定量する近赤外蛍光プローブと画像化手法が研究の中心であり、植物の生理状態を測定するフェノタイピング手法に該当する。

abstractIn this work, a near-infrared fluorescent probe (NIR-BOD-HS) was synthesized

Systemic Uptake of Rhodamine Tracers Quantified by Fluorescence Imaging: Applications for Enhanced Crop–Weed Detection →

Systemic fluorescence tracers introduced into crop plants provide an active signal for crop–weed differentiation that can be exploited for precision weed management. Rhodamine B (RB), a widely used tracer for seeds and seedlings, possesses desirable properties; however, its application as a seed treatment has been limited due to potential phytotoxic effects on seedling growth. Therefore, investigating mitigation strategies or alternative systemic tracers is necessary to fully leverage active signaling for crop–weed differentiation. This study aimed to identify and address the phytotoxicity concerns associated with Rhodamine B and evaluate Rhodamine WT and Sulforhodamine B as potential alternatives. A custom 2D fluorescence imaging system, along with analytical methods, was developed to optimize fluorescence imaging quality and facilitate quantitative characterization of fluorescence intensity and patterns in plant seedlings, individual leaves, and leaf disc samples. Rhodamine compounds were applied as seed treatments or in-furrow (soil application). Rhodamine B phytotoxicity was mitigated by growing in a sand and perlite media due to the adsorption of RB to perlite. Additionally, in-furrow and seed treatment methods were tested for Rhodamine WT and Sulforhodamine B to evaluate their efficacy as non-phytotoxic alternatives. Experimental results demonstrated that Rhodamine B applied via seed pelleting and Rhodamine WT used as a direct seed treatment were the most effective approaches. A case study was conducted to assess fluorescence signal intensity for crop–weed differentiation at a crop–weed seed distance of 2.5 cm (1 inch). Results indicated that fluorescence from both Rhodamine B via seed pelleting and Rhodamine WT as seed treatment was clearly detected in plant tissues and was ~10× higher than that from neighboring weed plant tissues. These findings suggest that RB ap-plied via seed pelleting effectively differentiates plant seedlings from weeds with reduced phytotoxicity, while Rhodamine WT as seed treatment offers a viable, non-phytotoxic alternative. In conclusion, the combination of the developed fluorescence imaging system and RB seed pelleting presents a promising technology for crop–weed differentiation and precision weed management. Additionally, Rhodamine WT, when used as a seed treatment, provides satisfactory efficacy as a non-phytotoxic alternative, further expanding the options for fluorescence-based crop–weed differentiation in weed management.

Why it matches plant phenotyping methods幼植物・葉・葉 disc の蛍光強度とパターンを定量するカスタム画像システムと解析法の開発が中心で、植物の識別可能な蛍光状態を取得する方法論的研究である。

abstractA custom 2D fluorescence imaging system, along with analytical methods, was developed to optimize fluorescence imaging quality and facilitate quantitative characterization of fluorescence intensity and patterns in plant seedlings, individual leaves, and leaf disc samples.

Insights into chestnut (Castanea spp.) graft incompatibility through the monitoring of chemical and physiological parameters. →

Main conclusion Incompatible chestnut grafts exhibited a notably reduced stomatal conductance, mirroring the trend observed for leaf chlorophyll content. Woody tissues at the graft interface of these combinations showed a significantly higher total phenolic content, especially in the internal layers. In recent years, significant efforts have been made to study the mechanisms of graft incompatibility in horticultural species, though research on minor species like chestnut remains limited. This study investigated the physiological and chemical dynamics in various chestnut grafts, aiming to develop a method for the early detection of graft incompatibility. The total phenolic content (TPC) and specific phenolic markers were analyzed at two phenological stages, callusing (CAL) and end of the vegetative cycle (EVC), using spectrophotometric and chromatographic techniques. These analyses were performed on three sections comprising the graft. Stomatal conductance (G sw ) and leaf chlorophyll content were assessed during the growing season as support tools, being non-destructive useful indicators of plant water status. Significant differences in the physiological traits among compatible and incompatible grafting combinations were evident and remained stable throughout the season. Compatible combinations consistently displayed greater leaf chlorophyll content and higher stomatal conductance, highlighting their superior physiological performance. TPC increased significantly from the CAL to EVC stage across all experimental grafting combinations and in all three analyzed sections. Greater phenol accumulation was observed at the graft union of incompatible combinations, particularly in the inner woody tissues. The phytochemical fingerprint revealed castalagin as the dominant compound, with significant increases in benzoic acids, catechins, and tannins during the growing season. However, the role of gallic acid and catechin as markers of graft incompatibility remains uncertain. The multidisciplinary approach provided valuable insights into the issue of graft incompatibility.

Why it matches plant phenotyping methods胸枯ぎ接ぎの不親和性という植物状態を、化学・生理指標で早期検出する方法の開発と比較評価が明示されており、単なる routine 測定ではない。

abstractThis study investigated the physiological and chemical dynamics in various chestnut grafts, aiming to develop a method for the early detection of graft incompatibility.

Quantitative vessel mapping on increment cores: a critical comparison of image acquisition methods. →

Introduction Quantitative wood anatomy is critical for establishing climate reconstruction proxies, understanding tree hydraulics, and quantifying carbon allocation. Its accuracy depends upon the image acquisition methods, which allows for the identification of the number and dimensions of vessels, fibres, and tracheids within a tree ring. Angiosperm wood is analysed with a variety of different image acquisition methods, including surface pictures, wood anatomical micro-sections, or X-ray computed micro-tomography. Despite known advantages and disadvantages, the quantitative impact of method selection on wood anatomical parameters is not well understood. Methods In this study, we present a systematic uncertainty analysis of the impact of the image acquisition method on commonly used anatomical parameters. We analysed four wood samples, representing a range of wood porosity, using surface pictures, micro-CT scans, and wood anatomical micro-sections. Inter-annual patterns were analysed and compared between methods from the five most frequently used parameters, namely mean lumen area ( MLA ), vessel density ( VD ), number of vessels ( VN ), mean hydraulic diameter ( D h ), and relative conductive area ( RCA ). A novel sectorial approach was applied on the wood samples to obtain intra-annual profiles of the lumen area ( A l ), specific theoretical hydraulic conductivity ( K s ), and wood density ( ρ ). Results Our quantitative vessel mapping revealed that values obtained for hydraulic wood anatomical parameters are comparable across different methods, supporting the use of easily applicable surface picture methods for ring-porous and specific diffuse-porous tree species. While intra-annual variability is well captured by the different methods across species, wood density ( ρ ) is overestimated due to the lack of fibre lumen area detection. Discussion Our study highlights the potential and limitations of different image acquisition methods for extracting wood anatomical parameters. Moreover, we present a standardized workflow for assessing radial tree ring profiles. These findings encourage the compilation of all studies using wood anatomical parameters and further research to refine these methods, ultimately enhancing the accuracy, replication, and spatial representation of wood anatomical studies.

Why it matches plant phenotyping methods木材解剖学的形質を抽出する画像取得法を比較・不確実性分析し、標準化ワークフローも提示しており、植物フェノタイピング手法が中心です。

abstractwe present a systematic uncertainty analysis of the impact of the image acquisition method on commonly used anatomical parameters.

Leaf-Whorl Inoculation with Sporisorium reilianum May Overcome Field Resistance of Maize →

Maize yield is threatened by increasing incidences of head smut disease caused by Sporisorium reilianum . To help breeders identify S. reilianum -resistant maize lines, the availability of efficient screening systems would be an advantage. Here we assessed maize lines with distinct levels of field resistance against head smut disease in greenhouse experiments using two different inoculation techniques. Addition of mixtures of mating-compatible sporidia to the soil at the seedling stage of the plant did not lead to plant disease, and we could detect only marginal amounts of fungal DNA in apical meristems at 18 days after inoculation. Inoculation of the maize lines by leaf-whorl inoculation led to both high disease incidence and prominent levels of fungal DNA in apical meristems in all tested maize lines regardless of their field resistance levels. Thus, S. reilianum entering the plant via the leaf whorl can escape existing resistance mechanisms of currently known field-resistant maize lines. Since field-resistant lines are also resistant to inoculation via teliospore-contaminated soil, we propose teliospore addition to seeds at the time of sowing (rather than leaf-whorl inoculation of seedlings) combined with quantitative detection of fungal DNA in apical meristems, as an efficient screening procedure to discover field-resistant lines. However, screening maize plants for resistance against the leaf-whorl inoculation method might be promising for the discovery of novel resistance mechanisms needed to develop durably resistant maize lines.

Why it matches plant phenotyping methodsトウモロコシの病害抵抗性を評価する接種・スクリーニング手順を比較検証し、効率的な抵抗性評価法を提案しており、病害状態の取得方法が研究の中心です。

abstractTo help breeders identify S. reilianum -resistant maize lines, the availability of efficient screening systems would be an advantage.

Computational wide-field imaging of poplar embolism and wound-response with a deployable microscope. →

Low-cost, minimally invasive microscopy for tracking cellular dynamics in living plants within their natural ecosystems is crucial for addressing fundamental questions in plant ecology and biology. However, existing solutions are constrained by coarse resolution, limited field-of-view (FoV), and poor deployability in natural settings. Here, we utilize a compact, portable microscope ("miniscope") for label-free (autofluorescence) imaging in living poplar wood. We systematically implement and evaluate multiple computational methods to enhance resolution and FoV. Our optimal computational pipeline, comprising maximal intensity projection, deconvolution, and flat-field correction, increases resolution by up to 39% on-axis and up to 49% at the field edges, resolving features of 2.87 μm, averaged over a FoV of ∼1 mm (diameter), compared with a 4.34 μm baseline. We demonstrate microscopy within the tissue of a living poplar plant in our greenhouse, observing the embolism of vessel elements, wound response, and tissue deformation from moisture evaporation.

Why it matches plant phenotyping methods生体ポプラ組織の細胞動態・木部塞栓・創傷応答を観察する携帯型顕微鏡と画像処理パイプラインを開発・評価しており、植物状態の取得手法が中心である。

abstractWe systematically implement and evaluate multiple computational methods to enhance resolution and FoV.

Plant paleoecophysiology traits in deep time: hydraulic conductivity and drought resistance in late Carboniferous Period plants →

Plants have been a key interface in the global carbon and water cycles for nearly 475 million years. The magnitude of vegetational effects has waxed and waned dynamically because plant abundance and community composition have changed over time. Unravelling how plant communities have shaped, and been shaped by, global biogeochemical cycles relies upon reconstructing the paleoecology and paleoecophysiology of plants, and this process can be challenging in deep time, when plant communities contained organisms with traits that are rare in—or absent from—present-day ecosystems. Fortunately, the archive of how plants have shaped and responded to environmental change is preserved in the fossil record, because the traits and properties of extinct plants can be interpreted from fossilized anatomy in a qualitative, semi-quantitative, and quantitative way. Traits related to water transport in plants. including drought resistance and hydraulic supply to leaves, are particularly useful and important because these traits link individual plant performance to the water and carbon cycles.The collapse of tropical everwet rainforests end of the Carboniferous Period (~300 Ma) provides an illustration of how plant water transport traits influenced, and were shaped by, the water and carbon cycles. These traits are quantified by combining mathematical models of stem hydraulic conductivity and drought resistance with anatomical measurements from scanning electron and light microscopy images of fossilized plant water transport cells, called xylem. Analysis of stem hydraulic traits in five lineages of extinct Carboniferous plants—arborescent lycophytes, stem group seed plants, stem group tree ferns, coniferophytes, and sphenophytes—reveals differential hydraulic capacity and drought resistance among these plants, despite their simultaneous presence in tropical everwet ecosystems. Significant differences in these two traits are not only present between these five lineages, but can also be observed within several of these plant groups: for example, key parameters may vary by more than an order of magnitude in related plants. High hydraulic capacity and low drought resistance traits were associated with a decline in relative abundance toward the close of the Carboniferous Period, whereas plants with lower hydraulic capacity and higher drought resistance traits increased in relative abundance and survived this floral transition. This change in relative abundance within these communities shaped the hydrologic and carbon cycles which, in turn, amplified environmental stress that, consequently, further altered plant community composition. Implementing this analysis in trait-aware paleoecosystem models illustrates the effect of plant traits on global environments, and vice versa, yielding insight into plant performance during extreme environmental change that is analogous to anthropogenic impacts predicted for the late 21st century and beyond.

Why it matches plant phenotyping methods化石植物の解剖学的画像測定と数学モデルを組み合わせ、木部の水理伝導度・乾燥抵抗性という植物生理形質を定量化しており、形質取得・推定手法が研究の中心的要素です。

abstractThese traits are quantified by combining mathematical models of stem hydraulic conductivity and drought resistance with anatomical measurements from scanning electron and light microscopy images of fossilized plant water transport cells, called xylem.

A simple and highly efficient protocol for 13 C-labeling of plant cell wall for structural and quantitative analyses via solid-state nuclear magnetic resonance. →

Background Plant cell walls are made of a complex network of interacting polymers that play a critical role in plant development and responses to environmental changes. Thus, improving plant biomass and fitness requires the elucidation of the structural organization of plant cell walls in their native environment. The 13 C-based multi-dimensional solid-state nuclear magnetic resonance (ssNMR) has been instrumental in revealing the structural information of plant cell walls through 2D and 3D correlation spectral analyses. However, the requirement of enriching plants with 13 C limits the applicability of this method. To our knowledge, there is only a very limited set of methods currently available that achieve high levels of 13 C-labeling of plant materials using 13 CO 2, and most of them require large amounts of 13 CO 2 in larger growth chambers. Results In this study, a simplified protocol for 13 C-labeling of plant materials is introduced that allows ca 60% labeling of the cell walls, as quantified by comparison with commercially labeled samples. This level of 13 C-enrichment is sufficient for all conventional 2D and 3D correlation ssNMR experiments for detailed analysis of plant cell wall structure. The protocol is based on a convenient and easy setup to supply both 13 C-labeled glucose and 13 CO 2 using a vacuum-desiccator. The protocol does not require large amounts of 13 CO 2 . Conclusion This study shows that our 13 C-labeling of plant materials can make the accessibility to ssNMR technique easy and affordable. The derived high-resolution 2D and 3D correlation spectra are used to extract structural information of plant cell walls. This helps to better understand the influence of polysaccharide-polysaccharide interaction on plant performance and allows for a more precise parametrization of plant cell wall models.

Why it matches plant phenotyping methods植物細胞壁の構造情報を取得するssNMR測定のための13C標識プロトコルを開発・定量検証しており、植物の構造的形質取得が中心である。

abstracta simplified protocol for 13 C-labeling of plant materials is introduced that allows ca 60% labeling of the cell walls, as quantified by comparison with commercially labeled samples.

Camelot: a Computer Automated Micro Extensometer with Low-cost Optical Tracking →

Abstract Background: Plant growth and morphogenesis is a mechanical process controlled by genetic and molecular networks. Measuring mechanical properties at various scales is necessary to understand how these processes interact. However, obtaining a device to perform the measurements on plant samples of choice poses technical challenges and is often limited by high cost and availability of specialized components, the adequacy of which needs to be verified. Developing software to control and integrate the different pieces of equipment can be a complex task. Results: To overcome these challenges, we have developed a computer automated micro-extensometer combined with low-cost optical tracking (Camelot) that facilitates measurements of elasticity, creep, and yield stress. It consists of three primary components: a force sensor with a sample attachment point, an actuator with a second attachment point, and a camera. To monitor force, we use a parallel beam sensor, commonly used in digital weighing scales. To stretch the sample, we use a stepper motor with a screw mechanism moving a stage along linear rail. To monitor sample deformation, a compact digital microscope or a microscope camera are used. The system is controlled by MorphoRobotX, an integrated open-source software environment for mechanical experimentation. We first tested the basic Camelot setup, equipped with a digital microscope to track landmarks on the sample surface. We demonstrate that the system has sufficient precision to measure the stiffness in delicate plant samples, the etiolated hypocotyls of Arabidopsis , and were able to measure stiffness differences between wild type and a xyloglucan-deficient mutant. Next, we placed Camelot on an inverted microscope and used C-mount microscope camera to track displacement of cell junctions. We stretched onion epidermal peels in longitudinal and transverse directions and obtained results similar to those previously published. Finally, we used the setup coupled with an upright confocal microscope and measured anisotropic deformation of individual epidermal cells during stretching of an Arabidopsis leaf. Conclusions: The portability and suitability of Camelot for high-resolution optical tracking under a microscope make it an ideal tool for researchers in resource-limited settings or those pursuing exploratory biomechanics work.

Why it matches plant phenotyping methods植物サンプルの力学的形質（弾性、クリープ、降伏応力、剛性、変形）を測定する低コスト装置とソフトウェアを開発しており、植物表現型の取得方法が研究の中心である。

abstractwe have developed a computer automated micro-extensometer combined with low-cost optical tracking (Camelot) that facilitates measurements of elasticity, creep, and yield stress.

Using phenomic selection to predict hybrid values with NIR spectra measured on the parental lines: proof of concept on maize. →

Key message Phenomic selection based on parental spectra can be used to predict GCA and SCA in a sparse factorial design. Prediction approaches such as genomic selection can be game changers in hybrid breeding. They allow predicting the genetic values of hybrids without the need for their physical production. This leads to significant reductions in breeding cycle length, and so to the increase in genetic progress. However, these methods are often underutilized in breeding programs due to the substantial cost involved in genotyping thousands of candidate parental lines annually. To address this limitation, we propose a cost-effective alternative based on phenomic selection, where genotyping of parental lines is replaced by NIR spectroscopy. Standard prediction models are then applied for genomic and phenomic selection, using similarity matrices derived from either genotyping data (genomic selection) or NIR spectral data (phenomic selection). Our hypothesis is that the chemical composition of parental tissues captured by NIRS reflects the genetic similarity between parental lines. We evaluated both strategies using a sparse factorial design, whose hybrids have been phenotyped in a multi-environment trial network, and with NIR spectra acquired on the parental lines on two independent environments. Both genomic and phenomic prediction approaches demonstrated moderate-to-high predictive abilities across various cross-validation scenarios. Our results also showcase the capability of phenomic selection to predict Mendelian sampling. This study serves as a proof of concept that low-cost high-throughput phenomics of parental lines can effectively be used to predict maize hybrids in independent trials. This paves the way for widespread adoption of prediction approaches at the very first stages of hybrid breeding, benefiting both major and orphan species.

Why it matches plant phenotyping methods親系統のNIRスペクトルを用いる高スループット表現型情報を、雑種予測へ適用・評価した研究であり、取得手法と予測ワークフローが中心的です。

abstractwe propose a cost-effective alternative based on phenomic selection, where genotyping of parental lines is replaced by NIR spectroscopy.

Nondestructive Detection and Quantification of Dysprosium in Plant Tissues →

ABSTRACT Background The growing demand for rare-earth elements (REEs), particularly dysprosium (Dy), in part driven by clean energy technologies, underscores the need for sustainable extraction methods. Recovery of Dy, particularly from geographically distributed waste sources is challenging. This gap positions phytomining—a technique using plants to accumulate metals— as a promising alternative. However, plant species differ in their ability to accumulate metals in high concentrations, necessitating efficient screening methods. In this study, we developed a high-throughput fluorescence-based assay to detect and quantify Dy uptake in plant tissues. Results Our Dy detection method exploits Dy’s unique spectroscopic properties for sensitive and efficient analysis, enabling detection of concentrations as low as 0.3 µM. By incorporating sodium tungstate (Na WO) as a fluorescence enhancer, we achieved robust emissions at 480 and 580 nm, facilitating Dy quantification in complex plant matrices. Additionally, time-resolved fluorescence techniques reduced background autofluorescence from plant tissues, enhancing signal specificity. Validation against Inductively Coupled Plasma Mass Spectrometry (ICP-MS) demonstrated strong correlation. Greenhouse trials confirmed the method’s utility for screening Dy accumulation in living plants and highlight the potential for rapid standoff detection. Conclusions This fluorescence-based approach offers a scalable, efficient tool for identifying Dy-accumulating plants, advancing phytomining as a sustainable strategy for REE recovery.

Why it matches plant phenotyping methods植物組織中のDy蓄積という植物状態を対象に、蛍光による高スループット測定法を開発し、ICP-MSで検証しているため、フェノタイピング手法が中心である。

abstractwe developed a high-throughput fluorescence-based assay to detect and quantify Dy uptake in plant tissues.

Panoptic segmentation for complete labeling of fruit microstructure in 3D micro-CT images with deep learning →

Metabolic processes in plant organs involving transport of water, metabolic gasses, and nutrients depend on the three-dimensional (3D) microscopic tissue morphology. However, imaging and quantifying this microstructure, including the spatial layout of parenchyma cells, pores, vascular bundles and special features such as stone cell clusters (brachysclereids), is challenging. To address this, a 3D deep learning-based panoptic segmentation model, combining semantic and instance segmentation, was developed to accelerate and improve microstructure characterization of apple and pear fruit tissue in X-ray micro-computed tomography (CT) images. In addition, various training datasets and data augmentation techniques, including synthetic data, were explored to enhance segmentation quality. The 3D panoptic segmentation achieved an Aggregated Jaccard Index of 0.89 and 0.77 for apple and pear tissue, respectively, outperforming both the previously designed 2D instance segmentation model and a marker-based watershed segmentation benchmark. The model successfully labelled vascular bundles with a Dice Similarity Coefficient (DSC) of 0.51 in apple tissue and 0.79 in pear tissue, although thin vasculature in apple remained more challenging to segment. The 3D panoptic segmentation model achieved a DSC of 0.81 and effectively segmented stone cell clusters in pear tissue. Despite evaluating different methods to enhance segmentation quality, none improved test performance beyond that of the model trained on the standard dataset. The proposed 3D panoptic segmentation model offers the most complete automated protocol to date for plant tissue labelling and morphometric quantification from native X-ray micro-CT images, without extensive sample preparation such as contrast labelling. The developed method, if not replaces, drastically accelerates conventional human-in-the-loop analysis of such images.

Why it matches plant phenotyping methods植物果実組織の3D微細構造をマイクロCT画像から自動抽出・定量化する深層学習手法を開発し、既存手法およびベンチマークと性能比較しているため、植物フェノタイピング手法が研究の中心です。

abstracta 3D deep learning-based panoptic segmentation model, combining semantic and instance segmentation, was developed to accelerate and improve microstructure characterization of apple and pear fruit tissue in X-ray micro-computed tomography (CT) images.

Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI. →

This study introduces a non-destructive, quantitative method using low-field MRI to assess moisture mobility and content distribution in cherry tomatoes. This study developed an advanced 3D non-local mean denoising model to enhance tissue feature analysis and applied an optimized TransUNet model for structural segmentation, obtaining multi-echo data from six tissue types. The structural T2 relaxation inversion was refined by integrating an ACS-CIPSO algorithm. This approach addresses the challenge of low signal-to-noise ratios in multi-echo MRI images from low-field equipment by introducing an innovative solution that effectively reduces voxel noise while retaining structural relaxation variability. The study reveals that there are consistent patterns in the changes in moisture mobility and content across different structures of cherry tomatoes during their ripening process. Mono-exponential analysis reveals the patterns of changes in moisture mobility (T2) and content (A) across various structures. Furthermore, tri-exponential analysis elucidates the patterns of changes in bound water (T21), semi-bound water (T22), and free water (T23), along with their respective contents. These insights offer a novel perspective on the changes in moisture mobility throughout the ripening process of tomato fruit, thereby providing a research pathway for the precise assessment of moisture status and ripening expression in fruits.

Why it matches plant phenotyping methods低磁場MRIのノイズ低減、構造セグメンテーション、T2緩和反転を開発し、トマト果実の水分状態と成熟表現型を定量化する方法が研究の中心である。

abstractThis study introduces a non-destructive, quantitative method using low-field MRI to assess moisture mobility and content distribution in cherry tomatoes.

Three-dimensional tracking of organ development in live plants based on plasma membrane dyes at single-cell resolution. →

Plant developmental biology necessitates precise three-dimensional (3D) tracking of dynamic processes in live plants, and the 3D imaging technique in developmental bioimaging requires suitable fluorophores to achieve single-cell resolution imaging. Herein, we have designed a series of plasma membrane fluorescent dyes with a number of excellent properties and established a single-cell resolution imaging tool based on these dyes for three-dimensional imaging of various tissues and organs in living plants. The designed plasma membrane fluorescent dyes not only have the advantages of rapid wash-free staining, highly specific targeting, high brightness and high contrast imaging, ultralong imaging time and low biotoxicity, but also effectively avoid the autofluorescence interference of chlorophyll in cells, allowing for the development of a three-dimensional imaging approach of living plant organs with single-cell resolution. The three-dimensional histological structures of various organs of adult Arabidopsis thaliana, including roots, leaves, flowers, and fruits, were successfully reconstructed with single-cell resolution using this model plant. Furthermore, the 3D imaging method was employed to track the dynamic changes in tissue and organ morphology at the single-cell level during key plant developmental processes, including seed germination, root development, leaf growth, and anther development.

Why it matches plant phenotyping methods植物器官の3D形態を単一細胞解像度で取得・追跡する蛍光イメージング手法と色素を開発し、複数の器官・発生過程で実証しており、表現型取得法が研究の中心です。

abstractestablished a single-cell resolution imaging tool based on these dyes for three-dimensional imaging of various tissues and organs in living plants

Near-infrared fluorescent probe for visualization of nitroxyl in the plant response to stress. →

Background Nitroxyl (HNO) is an emerging signaling molecule that plays a significant regulatory role in various aspects of plant biology, including stress responses and developmental processes. However, understanding the precise actions of HNO in plants has been challenging due to the absence of highly sensitive and real-time in situ monitoring tools. Consequently, it is crucial to develop effective and accurate detection methods for HNO. Establishing such methodologies will enable researchers to elucidate the functional roles of HNO in plant physiological processes, thereby advancing our knowledge of plant resilience and adaptation under environmental stressors. Result Herein, we successfully constructed a near-infrared fluorescent probe, DCIF-HNO, based on the dicyanoisophorone platform as fluorophore and 2-(diphenylphosphino)benzoate as HNO recognition site for identifying HNO in plants. Probe DCIF-HNO exhibited rapid response, excellent selectivity, and high sensitivity to HNO in vitro spectroscopic tests, while also demonstrating low toxicity and biocompatibility. A rapid and portable smartphone sensing platform for HNO in actual samples was successfully constructed based on probe DCIF-HNO and color recognition application. Moreover, probe DCIF-HNO was successfully applied to plant cells and tissues, enabling real-time visualization and detection of HNO and revealing the complex network of HNO interactions during H 2 S/NO crosstalk in plants. Furthermore, the increase in HNO levels in plants response to high salt and Cr stress was observed using probe DCIF-HNO. Transcriptome sequencing and differential metabolites analysis were employed to gain insight into the mechanism of HNO production under Cr stress. Significance Due to the optical properties and high-resolution imaging capabilities of DCIF-HNO, this study offers a novel framework for elucidating the signaling role of HNO in plant stress responses. The precise visualization of HNO dynamics enhances our understanding of the complex molecular pathways involved in plant adaptation to abiotic stressors. This research not only advances plant physiology but also has significant implications for developing strategies to enhance agricultural resilience in challenging environmental conditions.

Why it matches plant phenotyping methods植物内HNOのリアルタイム可視化・検出プローブとスマートフォン計測基盤を開発し、ストレス応答という植物の生理状態を測定しているため、方法が中心的である。

abstractwe successfully constructed a near-infrared fluorescent probe, DCIF-HNO

Method for measuring the transpiration resistance of fruit and vegetables. →

This investigation explores the intricate relationship between postharvest quality losses in fruit and vegetables and the dynamic interplay of transpiration and respiration activities. It underscores the profound impact of inherent produce properties and postharvest environmental conditions on transpiration, inducing changes in both external appearance and internal quality, notably wilting. Despite their common use, produce-specific transpiration coefficients encounter limitations due to diverse assumptions in calculations. Surface conditions intricately link produce and air properties, necessitating a comprehensive understanding. Horticultural products, with high water content, undergo continuous water loss through transpiration, driven by the water potential difference between the product and ambient air. Transpiration encompasses tissue and boundary layer resistances, influenced by plant tissue properties and external factors. Fruits experiencing drought stress exhibit elevated tissue resistance, serving as a protective mechanism. Concurrently, boundary layer resistance, influenced by external parameters, significantly shapes postharvest behaviour. To address these complexities, a novel method developed allows separate analysis of produce properties, climate, and flow conditions. This innovative approach enhances the understanding of transpiration behaviour, providing a foundation for improved postharvest practices, technical configurations, and quality maintenance strategies.•Direct method for tissue resistance and boundary layer resistance determination for fruit and vegetables.•Non-destructive method to optimize postharvest by using produce as a sensor to ensure quality.

Why it matches plant phenotyping methods果実・野菜の組織抵抗および境界層抵抗を分離測定する新規・非破壊手法が中心で、植物器官の蒸散特性を定量化している。

abstractDirect method for tissue resistance and boundary layer resistance determination for fruit and vegetables.

A custom pipeline for building computational models of plant tissue →

Stalk lodging in the monocot Zea mays is an important agricultural issue that requires the development of a genome-to-phenome framework, mechanistically linking intermediate and high-level phenotypes. As part of that effort, tools are needed to enable better mechanistic understanding of the microstructure in herbaceous plants. A method was therefore developed to create finite element models using CT scan data for Zea mays. This method represents a pipeline for processing the image stacks and developing the finite element models. 2-dimensional finite element models, 3-dimensional watertight models, and 3-dimensional voxel-based finite element models were developed. The finite element models contain both the cell and cell wall structures that can be tested in silico for phenotypes such as structural stiffness and predicted tissue strength. This approach was shown to be successful, and a number of example analyses were presented to demonstrate its usefulness and versatility. This pipeline is important for two reasons: (1) it helps inform which microstructure phenotypes should be investigated to breed for more lodging-resistant stalks, and (2) represents an essential step in the development of a mechanistic hierarchical framework for the genome-to-phenome modeling of herbaceous plant stalk lodging.

Why it matches plant phenotyping methodsCT画像スタックからトウモロコシ組織の有限要素モデルを構築する画像処理・計算パイプラインが研究の中心であり、構造剛性や組織強度という植物表現型の推定・解析に用いられているため。

abstractA method was therefore developed to create finite element models using CT scan data for Zea mays.

Image dataset: Optimizing growth of nonembryogenic citrus tissue cultures using response surface methodology. →

The data are images of Valencia sweet orange nonembryogenic tissue grown on different culture media that varied in the composition of the mineral nutrients from three experiments. Experiment 1 was a 5-factor d-optimal response surface design of five groupings of the component salts that make up Murashige and Skoog (MS) basal salt medium. Experiment 2 was a 3-factor d-optimal response surface design of extended ranges of factors 1, 2, and 3 from Experiment 1. Experiment 3 was thirteen formulations that were predicted using the prediction model generated from the 5-factor RSM from Experiment 1. The predictions were for two types of growth. One, points were predicted where growth was equal to MS medium (the standard), and two, points predicted with growth greater than MS medium by a minimum of 25%. An image representative of each formulation in each of the experiments makes up the dataset. The data will be useful for 1) visualizing the effects of the diverse mineral nutrient compositions, effects that may not be fully captured with single measure metrics; 2) development of image analysis applications via computer vision and segmentation algorithms for additional insight or for more rapid and possibly accurate assessment of tissue growth and quality; and 3) as an educational resource to learn how to use multifactor experimental designs to assess in vitro growth.

Why it matches plant phenotyping methods植物組織の成長画像データセットを提供し、画像解析・コンピュータビジョンによる成長および品質評価への利用を明示しており、表現型取得・抽出が中心的なデータ資源である。

abstractThe data are images of Valencia sweet orange nonembryogenic tissue grown on different culture media

Chromatic covalent organic frameworks enabling in-vivo chemical tomography. →

Covalent organic frameworks designed as chromatic sensors offer opportunities to probe biological interfaces, particularly when combined with biocompatible matrices. Particularly compelling is the prospect of chemical tomography - or the 3D spatial mapping of chemical detail within the complex environment of living systems. Herein, we demonstrate a chromic Covalent Organic Framework (COF) integrated within silk fibroin (SF) microneedles that probe plant vasculature, sense the alkalization of vascular fluid as a biomarker for drought stress, and provide a 3D in-vivo mapping of chemical gradients using smartphone technology. A series of Schiff base COFs with tunable pKa ranging from 5.6 to 7.6 enable conical, optically transparent SF microneedles with COF coatings of 120 to 950 nm to probe vascular fluid and the surrounding tissues of tobacco and tomato plants. The conical design allows for 3D mapping of the chemical environment (such as pH) at standoff distances from the plant, enabling in-vivo chemical tomography. Chromatic COF sensors of this type will enable multidimensional chemical mapping of previously inaccessible and complex environments.

Why it matches plant phenotyping methods植物維管束のpH変化を乾燥ストレスの指標として測定し、COFマイクロニードルとスマートフォンによる3D化学マッピング手法を開発しているため、植物表現型取得法が中心です。

abstractsense the alkalization of vascular fluid as a biomarker for drought stress, and provide a 3D in-vivo mapping of chemical gradients using smartphone technology

Quantitative light element (sodium and potassium) profiling in plant tissues using monochromatic X-ray fluorescence analysis →

ABSTRACT Accurately determining the elemental composition of plant tissues is essential for physiological studies on plant stress, including salinity tolerance. However, high-throughput routine analysis of light elements (range of sodium to calcium) in plant samples is challenging due to the need for complete sample dissolution and expensive inductively coupled plasma-mass-spectrometry (ICP-MS) analysis. Lower costs method (ion chromatography, ion selective electrodes) exists, but also require sample dissolution and lack sensitivity for very small samples (<10 mg). This study reports on a new method for the quantitative analysis of light elements in plant tissues using monochromatic X-ray fluorescence (XRF) instrumentation and innovative sample preparation and mounting. We used this approach to assess elemental uptake, distribution, and accumulation in Arabidopsis thaliana and Oryza sativa plants subjected to salt stress. The method can be used on samples as small as 1 mg making it suitable for small Arabidopsis thaliana plants. We systematically evaluated different sample preparations methods, repeatability, and measurement times to confirm the robustness of the technique. The results show that the monochromatic XRF method delivers rapid, non-destructive, and extraction-free analysis, strongly correlating with ICP-MS acquired data. As such, the monochromatic XRF method is a reliable and efficient alternative for studying salinity tolerance ideally suited for investigating elemental composition of early plant developmental stages, offering new possibilities for research into early stimuli sensing, perception and nutrient efficiency.

Why it matches plant phenotyping methods植物組織の元素状態を測定するXRF法の開発と、試料調製・反復性・測定時間・ICP-MSとの相関による検証が中心であり、植物の生理状態を定量するフェノタイピング手法に該当する。

abstractThis study reports on a new method for the quantitative analysis of light elements in plant tissues using monochromatic X-ray fluorescence (XRF) instrumentation and innovative sample preparation and mounting.

Feasibility and potential of terahertz spectral and imaging technology for Apple Valsa canker detection: A preliminary investigation. →

Apple Valsa canker (AVC) caused by the Ascomycete Valsa mali, seriously constrains the production and quality of apple fruits. The symptomless incubation characteristics of Valsa mali make it highly challenging to detect AVC at an early infection stage. After infecting the wound of apple bark, the pathogenic hyphae of AVC will expand and colonize the phloem tissue. Meanwhile, various enzymes and toxic substances released by hyphae cause the decomposition of cellulose and lignin, and the generation of poisonous secondary metabolites in bark tissue. However, these early symptoms of AVC are invisible from the bark's appearance. Fortunately, Terahertz Spectral Imaging (ThzSI) technology with the advantage of penetrating, and fingerprinting is promising for detecting hidden or slight symptoms of the fungal infection. This study is a preliminary investigation of terahertz frequency-domain spectra for AVC in the early stage of infection. Healthy and two-week-infected apple tree branches were prepared for capturing ThzS images, and the spectral data were preprocessed by Multivariate scattering correction (MSC), Savitzky-Golay convolution smoothing (SG), and standard normal variate (SNV) respectively to remove data noise and improve data quality. Principal component analysis (PCA), competitive adaptive reweighted sampling (CARS), and random frog (RFROG) were employed to extract the spectral feature bands to eliminate redundant data and improve computational efficiency. Machine learning models were established based on the spectral features to detect AVC at an early infection stage, where 11 of them exhibited the best performance with F1-score of 99.72%. To further explore disease information in spatial spectra, imaging data were acquired using terahertz imaging technology. Based on imaging data, pseudo-color imaging, histogram equalization, and Otsu segmentation were employed to visualize early infection areas in apple barks. Furthermore, histogram feature (HF), shape feature (SF), and local binary pattern (LBP) extracted from terahertz spectral images were utilized to establish the SVM, RF, and KNN models. HF-SF-KNN and HF-SF-LBP-KNN with the best performance achieved F1-score of 98.82%. This study presents a preliminary application of terahertz spectral and imaging technology for early-stage AVC detection and demonstrates its feasibility. Additionally, it provides a new way to detect AVC, which expands the application of ThzSI technology in tree disease detection in orchards and lays the foundation for further research.

Why it matches plant phenotyping methodsリンゴ樹皮の感染症状をテラヘルツ分光・画像から検出・可視化し、前処理、特徴抽出、画像分割、機械学習モデルを評価しているため、植物病害状態の取得・推定手法が中心である。

abstractTerahertz Spectral Imaging (ThzSI) technology with the advantage of penetrating, and fingerprinting is promising for detecting hidden or slight symptoms of the fungal infection.

3D reconstruction and morphological characterisation of single wheat grains by X-ray μCT →

Abstract The intricate task of achieving three-dimensional (3D) visual reconstruction of wheat kernels represents a notable challenge within the domain of digital grain analysis, playing a pivotal role in the realms of grain storage, processing, and breeding. However, existing investigations focused on individual kernels predominantly encompass dimensions such as length, width, height, and epidermal texture features, with a tendency to be invasive to the internal organisational structure of the kernel. Non-local mean filtering algorithm is proposed to segment various tissues, and the 2D grey scale images are extracted from X-ray micro-computed tomography (μCT) to reconstruct a meticulous 3D visualisation model of individual wheat grains. Furthermore, building upon this foundation, an exhaustive assessment of morphological and structural parameters pertaining to each facet of the internal organisation of the wheat seed grain is conducted. Notably, these calculated parameters align with data generated by prior researchers，with 80% of the volume of the endosperm, 12% of the pericarp, about 2% of the endosperm and scutellum, and 4% of the pores. The established parameters and resultant 3D visual models serve as foundational components for subsequent in-depth examinations into various physicochemical properties, including quality characteristics, heat, and mass transfer attributes, as well as variations in its morphological structure during breeding, which are pertinent to individual grains. This research contributes valuable insights and methodologies that can propel the advancement of studies in wheat kernel analysis.

Why it matches plant phenotyping methodsX線μCT画像から小麦粒の3D形状・内部組織を再構成し、形態・構造パラメータを抽出する手法が研究の中心であり、植物器官形質の取得方法を開発・評価している。

abstractNon-local mean filtering algorithm is proposed to segment various tissues, and the 2D grey scale images are extracted from X-ray micro-computed tomography (μCT) to reconstruct a meticulous 3D visualisation model of individual wheat grains.

Linking structure to function: the connection between mesophyll structure and intrinsic water use efficiency. →

Climate change-driven drought events are becoming unescapable in an increasing number of areas worldwide. Understanding how plants are able to adapt to these changing environmental conditions is a non-trivial challenge. Physiologically, improving a plant's intrinsic water use efficiency (WUEi ) will be essential for plant survival in dry conditions. Physically, plant adaptation and acclimatisation are constrained by a plant's anatomy. In other words, there is a strong link between anatomical structure and physiological function. Former research predominantly focused on using 2D anatomical measurements to approximate 3D structures based on the assumption of ideal shapes, such as spherical spongy mesophyll cells. As a result of increasing progress in 3D imaging technology, the validity of these assumptions is being assessed, and recent research has indicated that these approximations can contain significant errors. We suggest to invert the workflow and use the less common 3D assessments to provide corrections and functions for the more widely available 2D assessments. By combining these 3D and corrected 2D anatomical assessments with physiological measurements of WUEi , our understanding of how a plant's physical adaptation affects its function will increase and greatly improve our ability to assess plant survival.

Why it matches plant phenotyping methods3Dおよび補正2Dによる植物解剖形質の評価ワークフローを中心に論じ、植物構造の測定・推定法の改善を提案しているため、方法論的レビュー／開発に該当する。

abstractFormer research predominantly focused on using 2D anatomical measurements to approximate 3D structures

Metabolic imaging in living plants: A promising field for chemical exchange saturation transfer (CEST) MRI →

Magnetic resonance imaging (MRI) is a versatile technique in the biomedical field, but its application to the study of plant metabolism in vivo remains challenging because of magnetic susceptibility problems. In this study, we report the establishment of chemical exchange saturation transfer (CEST) for plant MRI. This method enables noninvasive access to the metabolism of sugars and amino acids in complex sink organs (seeds, fruits, taproots, and tubers) of major crops (maize, barley, pea, potato, sugar beet, and sugarcane). Because of its high signal detection sensitivity and low susceptibility to magnetic field inhomogeneities, CEST analyzes heterogeneous botanical samples inaccessible to conventional magnetic resonance spectroscopy. The approach provides unprecedented insight into the dynamics and distribution of sugars and amino acids in intact, living plant tissue. The method is validated by chemical shift imaging, infrared microscopy, chromatography, and mass spectrometry. CEST is a versatile and promising tool for studying plant metabolism in vivo, with many applications in plant science and crop improvement.

Why it matches plant phenotyping methods植物の生体内代謝を非侵襲的に測定するCEST-MRI法を確立し、複数手法で検証しており、植物表現型取得法が研究の中心である。

abstractIn this study, we report the establishment of chemical exchange saturation transfer (CEST) for plant MRI.

A simple and efficient method for betalain quantification in RUBY-expressing plant samples →

The RUBY reporter system has demonstrated great potential as a visible marker to monitor gene expression in both transiently and stably transformed plant tissues. Ectopic expression of the RUBY reporter leads to bright red pigmentation in plant tissues that do not naturally accumulate betalain. Unlike traditional visual markers such as β-glucuronidase (GUS), luciferase (LUC), and various fluorescent proteins, the RUBY reporter system does not require sample sacrifice or special equipment for visualizing the gene expression. However, a robust quantitative analysis method for betalain content has been lacking, limiting accurate comparative analyses. In this work, we present a simple and rapid protocol for quantitative evaluation of RUBY expression in transgenic plant tissues. Using this method, we demonstrate that differential RUBY expression can be quantified in transiently transformed leaf tissues, such as agroinfiltrated Nicotiana benthamiana leaves, and in stable transgenic maize tissues, including seeds, leaves, and roots. We found that grinding fresh tissues with a hand grinder and plastic pestle, without the use of liquid nitrogen, is an effective method for rapid betalain extraction. Betalain contents estimated by spectrophotometric and High-Performance Liquid Chromatography (HPLC) analyses were highly consistent, validating that our rapid betalain extraction and quantification method is suitable for comparative analysis. In addition, betalain content was strongly correlated with RUBY expression level in agroinfiltrated N. benthamiana leaves, suggesting that our method can be useful for monitoring transient transformation efficiency in plants. Using our rapid protocol, we quantified varying levels of betalain pigment in N. benthamiana leaves, ranging from 110 to 1066 mg/kg of tissue, and in maize samples, ranging from 15.3 to 1028.7 mg/kg of tissue. This method is expected to streamline comparative studies in plants, providing valuable insights into the effectiveness of various promoters, enhancers, or other regulatory elements used in transgenic constructs.

Why it matches plant phenotyping methods植物組織の betalain 含量を定量する抽出・測定プロトコルの開発と、分光法およびHPLCによる検証が研究の中心であり、植物の色素状態・RUBY発現量を測定する方法である。

abstractIn this work, we present a simple and rapid protocol for quantitative evaluation of RUBY expression in transgenic plant tissues.

Implementation of Ribo-BiFC method to plant systems using a split mVenus approach →

Abstract Translation is a fundamental process for every living organism. In plants, the rate of translation is tightly modulated during development and in response to environmental cues. However, it is difficult to measure the actual translation state of the tissues in vivo . Here, we report the implementation of an in vivo translation marker based on bimolecular fluorescence complementation, the Ribo-BiFC. We combined method originally developed for fruit-fly with an improved low background split-mVenus BiFC system previously described in plants. We labelled Arabidopsis thaliana small subunit ribosomal protein (RPS) and large subunit ribosomal protein (RPL) with fragments of the mVenus fluorescent protein. Upon the assembly of the 80S ribosome, the mVenus fragments complemented and were detected by fluorescent microscopy. We show that these recombinant proteins are in close proximity in the tobacco epidermal cells, although the signal is reduced when compared to BiFC signal from known interactors. This Ribo-BiFC method system can be used in stable transgenic lines to enable visualisation of translational rate in plant tissues and could be used to study translation dynamics and its changes during plant development, under abiotic stress or in different genetic backgrounds.

Why it matches plant phenotyping methods植物組織内の翻訳速度という生理状態を可視化するRibo-BiFC法を実装・検証しており、表現型取得法が研究の中心である。

abstractHere, we report the implementation of an in vivo translation marker based on bimolecular fluorescence complementation, the Ribo-BiFC.

Large-volume fully automated cell reconstruction generates a cell atlas of plant tissues →

Abstract The geometric shape and arrangement of individual cells play a role in shaping organ functions. However, analyzing multicellular features and exploring their connectomes in centimeter-scale plant organs remain challenging. Here, we established a set of frameworks named large-volume fully automated cell reconstruction (LVACR), enabling the exploration of 3D cytological features and cellular connectivity in plant tissues. Through benchmark testing, our framework demonstrated superior efficiency in cell segmentation and aggregation, successfully addressing the inherent challenges posed by light sheet fluorescence microscopy imaging. Using LVACR, we successfully established a cell atlas of different plant tissues. Cellular morphology analysis revealed differences of cell clusters and shapes in between different poplar (Populus simonii Carr. and Populus canadensis Moench.) seeds, whereas topological analysis revealed that they maintained conserved cellular connectivity. Furthermore, LVACR spatiotemporally demonstrated an initial burst of cell proliferation, accompanied by morphological transformations at an early stage in developing the shoot apical meristem of Pinus tabuliformis Carr. seedlings. During subsequent development, cell differentiation produced anisotropic features, thereby resulting in various cell shapes. Overall, our findings provided valuable insights into the precise spatial arrangement and cellular behavior of multicellular organisms, thus enhancing our understanding of the complex processes underlying plant growth and differentiation.

Why it matches plant phenotyping methods植物組織の3D細胞形態・接続性を画像から抽出するLVACRを開発し、ベンチマーク検証と実データ適用を行っており、植物フェノタイピング手法が中心である。

abstractwe established a set of frameworks named large-volume fully automated cell reconstruction (LVACR), enabling the exploration of 3D cytological features and cellular connectivity in plant tissues.

Fluorescent carbon dot embedded polystyrene: an alternative for micro/nanoplastic translocation study in leguminous plants. →

Micro/nanoplastics are widespread in terrestrial ecosystem. Even though many studies have been reported on the effects of these in marine environment, studies concerning their accumulation and impact on terrestrial ecosystem have been scanty. The current study was designed to determine how terrestrial plants, especially legumes, interact with micro/nanoplastics to gain insights into their uptake and translocation. The paper describes the synthesis of fluorescent carbon dot embedded polystyrene (CDPS) followed by its characterization. Translocation studies at different concentrations from 2 to 100% (v/v) for tracking the movement and accumulation of microplastics in Vigna radiata and Vigna angularis were performed. The optical properties of the synthesized CDPS were investigated, and their translocation within the plants was visualized using fluorescence microscopy. These findings were further validated by scanning electron microscopy (SEM) imaging of the plant sections. The results showed that concentrations higher than 6% (v/v) displayed noticeable fluorescence in the vascular region and on the cell walls, while concentrations below this threshold did not. The study highlights the potential of utilizing fluorescent CDPS as markers for investigating the ecological consequences and biological absorption of microplastics in agricultural systems. This method offers a unique technique for monitoring and analyzing the routes of microplastic accumulation in edible plants, with significant implications for both food safety and environmental health.

Why it matches plant phenotyping methods蛍光標識粒子と蛍光顕微鏡・SEMを用いて植物体内のマイクロプラスチック蓄積・移行を可視化する手法が研究の中心であり、植物の生理状態（吸収・転流）を測定する方法として該当する。

abstractThe paper describes the synthesis of fluorescent carbon dot embedded polystyrene (CDPS) followed by its characterization.

Sandwich freezing and freeze substitution of Arabidopsis plant tissues for electron microscopy →

Abstract Sandwich freezing is a method of rapid freezing by sandwiching specimens between two copper disks, and it has been used for observing exquisite close-to-native ultrastructure of living yeast and bacteria. Recently, this method has been found to be useful for preserving cell images of glutaraldehyde-fixed cultured cells, as well as animal and human tissues. In the present study, this method was applied to observe the fine structure of living Arabidopsis plant tissues and was found to achieve excellent ultrastructural preservation of cells and tissues. This is the first report of applying the sandwich freezing method to observe plant tissues.

Why it matches plant phenotyping methods植物組織の細胞・組織微細構造を保存・観察するためのサンドイッチ凍結法を植物へ適用した技術研究であり、表現型取得法が中心である。

abstractIn the present study, this method was applied to observe the fine structure of living Arabidopsis plant tissues and was found to achieve excellent ultrastructural preservation of cells and tissues.

Visualization and Quantitative Evaluation of Functional Structures of Soybean Root Nodules via Synchrotron X-ray Imaging. →

The efficiency of N 2 -fixation in legume-rhizobia symbiosis is a function of root nodule activity. Nodules consist of 2 functionally important tissues: (a) a central infected zone (CIZ), colonized by rhizobia bacteria, which serves as the site of N 2 -fixation, and (b) vascular bundles (VBs), serving as conduits for the transport of water, nutrients, and fixed nitrogen compounds between the nodules and plant. A quantitative evaluation of these tissues is essential to unravel their functional importance in N 2 -fixation. Employing synchrotron-based x-ray microcomputed tomography (SR-μCT) at submicron resolutions, we obtained high-quality tomograms of fresh soybean root nodules in a non-invasive manner. A semi-automated segmentation algorithm was employed to generate 3-dimensional (3D) models of the internal root nodule structure of the CIZ and VBs, and their volumes were quantified based on the reconstructed 3D structures. Furthermore, synchrotron x-ray fluorescence imaging revealed a distinctive localization of Fe within CIZ tissue and Zn within VBs, allowing for their visualization in 2 dimensions. This study represents a pioneer application of the SR-μCT technique for volumetric quantification of CIZ and VB tissues in fresh, intact soybean root nodules. The proposed methods enable the exploitation of root nodule's anatomical features as novel traits in breeding, aiming to enhance N 2 -fixation through improved root nodule activity.

Why it matches plant phenotyping methodsSR-μCTと半自動3Dセグメンテーションを用いて根粒内部組織を可視化・体積定量する手法が中心であり、育種に利用可能な新規植物形質を抽出している。

abstractA semi-automated segmentation algorithm was employed to generate 3-dimensional (3D) models of the internal root nodule structure of the CIZ and VBs, and their volumes were quantified based on the reconstructed 3D structures.

Enhancement of in situ detection and imaging of phytohormones in plant tissues by MALDI ‐ MSI using 2,4‐dihydroxy‐5‐nitrobenzoic acid as a novel matrix →

Summary Phytohormones possess unique chemical structures, and their physiological effects are regulated through intricate interactions or crosstalk among multiple phytohormones. MALDI‐MSI enables the simultaneous detection and imaging of multiple hormones. However, its application for tracing phytohormones is currently restricted by low abundance of hormone in plant and suboptimal matrix selection. 2,4‐Dihydroxy‐5‐nitrobenzoic acid (DHNBA) was reported as a new MALDI matrix for the enhanced detection and imaging of multiple phytohormones in plant tissues. DHNBA demonstrates remarkable sensitivity improvement when compared to the commonly used matrix, 2,5‐dihydroxybenzoic acid (DHB), in the detection of isoprenoid cytokinins ( trans ‐zeatin ( t Z), dihy‐drozeatin (DHZ), meta ‐topolin ( m T), and N 6 ‐(Δ 2 ‐isopentenyl) adenine (iP)), jasmonic acid (JA), abscisic acid (ABA), and 1‐aminocyclo‐propane‐1‐carboxylic acid (ACC) standards. The distinctive properties of DHNBA (i.e. robust UV absorption, uniform matrix deposition, negligible background interference, and high ionization efficiency of phytohormones) make it as an ideal matrix for enhanced detection and imaging of phytohormones, including t Z, DHZ, ABA, indole‐3‐acetic acid (IAA), and ACC, by MALDI‐MSI in various plant tissues, for example germinating seeds, primary/lateral roots, and nodules. Employing DHNBA significantly enhances our capability to concurrently track complex phytohormone biosynthesis pathways while providing precise differentiation of the specific roles played by individual phytohormones within the same category. This will propel forward the comprehensive exploration of phytohormonal functions in plant science.

Why it matches plant phenotyping methods植物組織中の植物ホルモンをMALDI-MSIで検出・画像化するための新規マトリックスを開発し、感度や画像化性能を比較評価しており、フェノタイピング手法が中心である。

abstractThe distinctive properties of DHNBA (i.e. robust UV absorption, uniform matrix deposition, negligible background interference, and high ionization efficiency of phytohormones) make it as an ideal matrix for enhanced detection and imaging of phytohormones

Use of confocal laser scanning microscopy to locate Stenocarpella maydis in corn stalk (Zea mays) →

Abstract Stenocarpella maydis causes high production losses in almost all countries where corn ( Zea mays ) is cultivated. The rot caused by S. maydis may occur on the stalks and ears of corn plants. S. maydis in corn poses a significant threat to human and animal nutrition, mainly due to mycotoxins such as diplodiatoxin. This study aimed to validate an efficient methodology for visualizing S. maydis colonization in corn using clarification protocol, fluorochromes, and Confocal Laser Scanning Microscopy (CLSM). Conidial suspensions were inoculated into the corn stalk at the V6 stage using a syringe. Corn stalk fragments of 1 cm 2 were collected 21 days after inoculation (dai) for CLSM analysis. The samples were fixed in Karnovsky’s solution and clarified in KOH and chloral hydrate. The fungal structures were labeled with Alexa488-WGA at 1.0 mg mL − 1 for 30 min under vacuum (excitation at 488 and emission at 510–540 ƞm). Thereafter, the corn plant tissues were labeled with Calcofluor White at 0.1 mg mL − 1 (excitation at 405 and emission at 440–490 ƞm) for 30 min. The Laser Confocal LSM780 Zeiss Observer Z.1 microscope, LCI Plan-Neofluar 25×/0.8, and C-Apochromat 63×/1.20 objectives were used to acquire fluorescent images. At 21 dai, it was possible to observe the colonization and formation of pycnidia with bicellular conidia of the fungus S. maydis in corn stalk fragments. The fungus colonized parenchymatic tissues and vascular bundles of the corn stalk. In contrast, at 21 dai, colonization of the fungus S. maydis was not observed in the parenchymatic tissues and vascular bundles of the corn stalk from uninoculated control plants. Our study made it possible to validate a new methodology for studying the infectious process of S. maydis in corn stalk using clarification protocols, fluorochromes, and CLSM.

Why it matches plant phenotyping methodsトウモロコシ茎内の病原菌定着という植物病態を可視化するため、組織透明化・蛍光染色・共焦点顕微鏡法を開発・検証しており、植物表現型取得が中心である。

abstractThis study aimed to validate an efficient methodology for visualizing S. maydis colonization in corn using clarification protocol, fluorochromes, and Confocal Laser Scanning Microscopy (CLSM).

Detection of Anthocyanins in Potatoes Using Micro-Hyperspectral Images Based on Convolutional Neural Networks. →

The color potato has the function of both a food and vegetable. The color potato not only contains various amino acids and trace elements needed by the human body but also contains anthocyanins. Anthocyanins have many functions, such as antioxidation, inflammation inhibition, vision improvement, and cancer prevention, so colored potatoes are deeply loved by consumers and have good market prospects. However, at present, the detection of anthocyanin content in color potatoes mainly depends on chemical methods, which are time-consuming and laborious, so it is necessary to study a fast and accurate detection method. In this study, microscopic hyperspectral equipment was used to collect the spectral information of the outer skin and inner skin of potatoes. The original spectrum, pretreatment spectrum, and characteristic spectrum variables of the outer skin and inner skin were predicted by the convolution neural network (CNN) algorithm and partial least squares regression (PLS) algorithm, respectively, and the performance of the model was evaluated by the prediction set correlation coefficient (Rp), prediction set root mean square error (RMSEP), correction set correlation coefficient (Rc), correction set root mean square error (RMSEC), and residual prediction deviation (RPD). The results revealed that the inner skin Raw + CNN model constructed under raw spectral data is optimal with Rc = 0.9508, RMSEC = 0.0374%, Rp = 0.9461, RMSEP = 0.2361% and RPD = 4.4933. The inner skin Savitzky-Golay (SG) + Detrend (DET) + CNN model constructed from pre-processed spectral data is optimal with Rc = 0.9499, RMSEC = 0.0359%, Rp = 0.9439, RMSEP = 0.2384%, RPD = 4.6516. The inner skin DET + competitive adaptive reweighted sampling (CARS) +CNN model constructed from the feature-based spectral data was optimal with Rc = 0.9527, RMSEC = 0.0708%, Rp = 0.9457, RMSEP = 0.2711%, and RPD = 4.1623. It can be seen that the Rp, RMSEP, Rc, RMSEC, and RPD values for modeling the spectral information of the inner skin were higher than those of the outer skin under the three different spectral data. The prediction accuracy of the model built by the CNN algorithm was better than the conventional algorithm PLS, the application of the CNN algorithm in inner skin can achieve accurate prediction of anthocyanin content in potato.

Why it matches plant phenotyping methodsジャガイモ組織のマイクロハイパースペクトル画像からアントシアニン含量という植物器官形質をCNN等で推定する測定法を開発・評価しており、表現型取得が中心である。

abstractit is necessary to study a fast and accurate detection method

Non-destructive wood identification using X-ray µCT scanning: which resolution do we need? →

Background Taxonomic identification of wood specimens provides vital information for a wide variety of academic (e.g. paleoecology, cultural heritage studies) and commercial (e.g. wood trade) purposes. It is generally accomplished through the observation of key anatomical features. Classic methodologies mostly require destructive sub-sampling, which is not always acceptable. X-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure. There is, however, no standardized approach that determines the required resolution for proper wood identification using X-ray µCT. Here we compared X-ray µCT scans of 17 African wood species at four resolutions (1 µm, 3 µm, 8 µm and 15 µm). The species were selected from the Xylarium of the Royal Museum for Central Africa, Belgium, and represent a wide variety of wood-anatomical features. Results For each resolution, we determined which standardized anatomical features can be distinguished or measured, using the anatomical descriptions and microscopic photographs on the Inside Wood Online Database as a reference. We show that small-scale features (e.g. pits and fibres) can be best distinguished at high resolution (especially 1 µm voxel size). In contrast, large-scale features (e.g. vessel porosity or arrangement) can be best observed at low resolution due to a larger field of view. Intermediate resolutions are optimal (especially 3 µm voxel size), allowing recognition of most small- and large-scale features. While the potential for wood identification is thus highest at 3 µm, the scans at 1 µm and 8 µm were successful in more than half of the studied cases, and even the 15 µm resolution showed a high potential for 40% of the samples. Conclusions The results show the potential of X-ray µCT for non-destructive wood identification. Each of the four studied resolutions proved to contain information on the anatomical features and has the potential to lead to an identification. The dataset of 17 scanned species is made available online and serves as the first step towards a reference database of scanned wood species, facilitating and encouraging more systematic use of X-ray µCT for the identification of wood species.

Why it matches plant phenotyping methodsX線µCTによる木材内部の解剖学的特徴の非破壊取得について、解像度を比較・評価し、参照データベース用データセットも提供しているため、植物形質取得法が中心です。

abstractX-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure.

Live Imaging of the Shoot Apical Meristem of Intact, Soil-Grown, Flowering Arabidopsis Plants. →

All aerial organs in plants originate from the shoot apical meristem, a specialized tissue at the tip of a plant, enclosing a few stem cells. Understanding developmental dynamics within this tissue in relation to internal and external stimuli is of crucial importance. Imaging the meristem at the cellular level beyond very early stages requires the apex to be detached from the plant body, a procedure that does not allow studies in living, intact plants over longer periods. This protocol describes a new confocal microscopy method with the potential to image the shoot apical meristem of an intact, soil-grown, flowering Arabidopsis plant over several days. The setup opens new avenues to study apical stem cells, their interconnection with the whole plant, and their responses to environmental stimuli. Key features • Novel dissection and imaging method of the shoot apical meristem of Arabidopsis . • Procedure performed with intact, soil-grown, flowering plants. • Possibility of long-term live imaging of the shoot apical meristem. • Protocol can be adapted to different plant species.

Why it matches plant phenotyping methods生きた植物のシュート頂端分裂組織を長期間観察するための新規共焦点イメージング手法・プロトコルが中心であり、植物の形態・発生状態を取得する方法として収載対象です。

abstractThis protocol describes a new confocal microscopy method with the potential to image the shoot apical meristem of an intact, soil-grown, flowering Arabidopsis plant over several days.

Rational design of Near-Infrared fluorescent probe for monitoring HNO in plants. →

Nitroxyl (HNO), a reactive nitrogen species (RNS), is essential for plant growth. However, the action of HNO in plants has been difficult to understand due to the lack of highly sensitive and real-time in-situ monitoring tools. Herein, we presented a near-infrared fluorescent probe, DCI-HNO, based on dicyanoisophorone fluorophore, for real-time mapping HNO in plants. The introduction of a phosphine moiety as a specific HNO recognition unit can inhibit the intramolecular charge transfer (ICT) of probe DCI-HNO. However, in the presence of HNO, the ICT process occurred, leading to the emission at 665 nm. Probe DCI-HNO exhibited high sensitivity (97 nM), rapid response time (8 min), large Stokes shift (135 nm) for detection of HNO in plants. The novel developed probe has successfully imaged endogenous HNO produced during NO/H 2 S cross-talk in plant tissues. Additionally, the up-regulated in HNO levels during tobacco aging and in response to stress has been confirmed. Therefore, probe DCI-HNO has provided a reliable method for monitoring the NO/H 2 S cross-talk and revealing the role of HNO in plants.

Why it matches plant phenotyping methods植物組織内のHNOをリアルタイム可視化・定量する蛍光プローブを開発し、感度や応答時間を評価しているため、植物の生理状態を取得する方法開発が中心である。

abstractwe presented a near-infrared fluorescent probe, DCI-HNO, based on dicyanoisophorone fluorophore, for real-time mapping HNO in plants.

Mathematical Modeling of the Heat Transfer Process in Spherical Objects With Flat, Cylindrical and Spherical Defects →

This article discusses the application of thermal quality control methods for plant tissues. The purpose of the work is to determine the optimal parameters of thermal impact on a spherical-shaped plant control object, ensuring the detection of surface and subsurface defects. The authors of the work proposed mathematical models of the temperature field for a spherical body with defects and a flat sample when exposed to the thermal influence of a pulsed source. As a result of the use of mathematical models, the thermophysical characteristics of plant tissues of varying degrees of disease damage were obtained, which made it possible to simulate the temperature field of the control object and obtain an image of classified tissues. The developed recommendations made it possible to select the optimal parameters of the thermal effect on the test object.

Why it matches plant phenotyping methods植物組織の表面・内部欠陥や病害状態を熱画像と温度場モデルで検出・分類する方法の開発が中心であり、単なる routine 測定ではない。

abstractThe purpose of the work is to determine the optimal parameters of thermal impact on a spherical-shaped plant control object, ensuring the detection of surface and subsurface defects.

Attenuated total reflection Fourier-transform infrared spectroscopy for the prediction of hormone concentrations in plants. →

Plant hormones are important in the control of physiological and developmental processes including seed germination, senescence, flowering, stomatal aperture, and ultimately the overall growth and yield of plants. Many currently available methods to quantify such growth regulators quickly and accurately require extensive sample purification using complex analytic techniques. Herein we used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles of both freeze-dried ground leaf tissue and extracted xylem sap of Japanese knotweed ( Reynoutria japonica ) plants grown under different environmental conditions. In addition to these predictions made with partial least squares regression, further analysis of spectral data was performed using chemometric techniques, including principal component analysis, linear discriminant analysis, and support vector machines (SVM). Plants grown in different environments had sufficiently different biochemical profiles, including plant hormonal compounds, to allow successful differentiation by ATR-FTIR spectroscopy coupled with SVM. ATR-FTIR spectral biomarkers highlighted a range of biomolecules responsible for the differing spectral signatures between growth environments, such as triacylglycerol, proteins and amino acids, tannins, pectin, polysaccharides such as starch and cellulose, DNA and RNA. Using partial least squares regression, we show the potential for accurate prediction of plant hormone concentrations from ATR-FTIR spectral profiles, calibrated with hormonal data quantified by UHPLC-HRMS. The application of ATR-FTIR spectroscopy and chemometrics offers accurate prediction of hormone concentrations in plant samples, with advantages over existing approaches.

Why it matches plant phenotyping methodsATR-FTIRスペクトルとケモメトリクスで植物ホルモン濃度を予測する方法を開発・検証しており、植物の生理状態の定量が中心的な技術貢献である。

abstractwe used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles

Optimized routing algorithm with AlexNet-ShuffleNet for plant leaf disease and infectious classification in IoT →

Abstract In agriculture, utilizing images to detect plant leaf diseases is a vital area in precision farming. Typically, trained professionals physically inspect plant tissues to identify disease range. Nowadays, AI has made foremost paces in detecting and classifying plant diseases. Moreover, Internet of Things (IoT) has several applications, containing Agricultural-IoT (AIoT), which is considered to elevate agricultural yields. This paper intends to develop an approach in IoT for plant disease classification. Initially, simulation of IoT is done and the IoT nodes route sensed plant leaf images by proposed Serial Exponential Golf Optimization Algorithm (SEGOA), which is established by modifying Golf Optimization Algorithm (GOA) using Exponential Weighted Moving Average (EWMA) to the destination, where plant leaf disease detection is executed. To extract the RoI, CNN is used to discover diseased part in plant leaf. Then, plant leaves is classified as healthy and diseased subclasses by employing AlexNet-ShuffleNet. Moreover, the disease types is classified more into fungal/bacterial/viral infection using the AlexNet-ShuffleNet. Performance of adopted work is assessed by utilizing the metrics, such as energy, accuracy, sensitivity, and specificity. Overall outcome of AlexNet-ShuffleNet give a promising result, such as accuracy of 94.6%, sensitivity of 98.7% and specificity of 94%.

Why it matches plant phenotyping methods植物葉画像から病変領域を抽出し、健全・罹病状態および病原タイプを分類する画像解析手法を開発・評価しており、植物病害表現型の取得が中心である。

abstractThis paper intends to develop an approach in IoT for plant disease classification.

Dual Infrared 2‐Photon Microscopy Achieves Minimal Background Deep Tissue Imaging in Brain and Plant Tissues →

Abstract Traditional deep fluorescence imaging has primarily focused on red‐shifting imaging wavelengths into the near‐infrared (NIR) windows or implementation of multi‐photon excitation approaches. Here, the advantages of NIR and multiphoton imaging are combined by developing a dual‐infrared two‐photon microscope that enables high‐resolution deep imaging in biological tissues. This study first computationally identifies that photon absorption, as opposed to scattering, is the primary contributor to signal attenuation. A NIR two‐photon microscope is constructed next with a 1640 nm femtosecond pulsed laser and a NIR PMT detector to image biological tissues labeled with fluorescent single‐walled carbon nanotubes (SWNTs). Spatial imaging resolutions are achieved close to the Abbe resolution limit and eliminate blur and background autofluorescence of biomolecules, 300 µm deep into brain slices and through the full 120 µm thickness of a Nicotiana benthamiana leaf. NIR‐II two‐photon microscopy can also measure tissue heterogeneity by quantifying how much the fluorescence power law function varies across tissues, a feature this study exploits to distinguish Huntington's Disease afflicted mouse brain tissues from wildtype. These results suggest dual‐infrared two‐photon microscopy can accomplish in‐tissue structural imaging and biochemical sensing with a minimal background, and with high spatial resolution, in optically opaque or highly autofluorescent biological tissues.

Why it matches plant phenotyping methods植物組織を対象に、深部構造イメージングと組織不均一性の測定を可能にする二光子顕微鏡を開発しており、植物組織への適用も明示されているため、方法開発として中心的である。

abstractA NIR two‐photon microscope is constructed next with a 1640 nm femtosecond pulsed laser and a NIR PMT detector to image biological tissues

2D and 3D visualization of herbaceous plant–plant contact zones using high‐resolution X‐ray computed tomography (HRXCT) →

Societal Impact Statement Parasitic plants that deprive crops of water and nutrients are an increasingly concerning food security issue, affecting the livelihood of millions of subsistence, small‐ and mid‐scale farmers. An in‐depth understanding of parasite–host interactions is required to develop species‐specific and ecologically sustainable parasite management methods. The non‐invasive visualization of herbaceous contact zones, applicable to diverse parasite–host pathosystems presented in this study, brings methodological advance to the research of biotic interactions between crops and plant parasites belonging to the most devastating parasitic plant family (Orobanchaceae). This work also provides first insights into how the parasites' feeding organ displaces host tissue beyond the direct parasite–host interface. Summary High‐resolution X‐ray computed tomography (HRXCT) enables sectioning‐free two‐dimensional imaging of biological structures and reconstruction of three‐dimensional objects. Although its application is common in many areas of biomedicine and despite its flexibility regarding resolution levels, the technology remains underutilized in the plant sciences. Here, we explored HRXCT for the study of parasitic plant–plant interactions by developing protocols to access soft‐tissue host–parasite contact zones at cell‐level resolution. We tested various sample preparation methods and contrast stains for their efficiency to improve the imaging of haustorium samples. In doing so, we achieved cellular resolution with the visible cellular organization of haustorial structures, especially of the vascular system. Fresh stained and dehydrated sample preparation of soft haustoria enables the highest spatial resolution with fine‐cellular discrimination of haustorium versus host cells. Application of cell‐level resolved HRXCT to five pathosystems: Alectra ‐cowpea, Phelipanche ‐tomato, Phtheirospermum ‐tomato, Rhamphicarpa ‐tomato, and Striga ‐sorghum highlighted a life history‐specific organization and uncovered an as yet undescribed internal displacement of host tissue at parasite–host interfaces. Following image‐based training, our HRXCT approach could invoke AI‐based cell recognition for automated parasite cell–host cell differentiation. Superseding extensive microsectioning for 3D imaging, the newly established HRXCT protocol for 2D‐ and 3D‐visualization of herbaceous plant–plant contact zones and the first insights gained from it, is useful for mid‐throughput, comparative studies of parasitic plant–host interactions.

Why it matches plant phenotyping methodsHRXCTによる植物組織の2D・3D画像取得プロトコルを開発し、試料調製・染色を比較検証したうえで、寄生植物と宿主の接触領域を細胞レベルで可視化する方法が中心である。

abstractHere, we explored HRXCT for the study of parasitic plant–plant interactions by developing protocols to access soft‐tissue host–parasite contact zones at cell‐level resolution.

Quantitative MRI imaging of parenchyma and venation networks in Brassica napus leaves: effects of development and dehydration. →

Background Characterisation of the structure and water status of leaf tissues is essential to the understanding of leaf hydraulic functioning under optimal and stressed conditions. Magnetic Resonance Imaging is unique in its capacity to access this information in a spatially resolved, non-invasive and non-destructive way. The purpose of this study was to develop an original approach based on transverse relaxation mapping by Magnetic Resonance Imaging for the detection of changes in water status and distribution at cell and tissue levels in Brassica napus leaves during blade development and dehydration. Results By combining transverse relaxation maps with a classification scheme, we were able to distinguish specific zones of areoles and veins. The tissue heterogeneity observed in young leaves still occurred in mature and senescent leaves, but with different distributions of T 2 values in accordance with the basipetal progression of leaf blade development, revealing changes in tissue structure. When subjected to severe water stress, all blade zones showed similar behaviours. Conclusion This study demonstrates the great potential of Magnetic Resonance Imaging in assessing information on the structure and water status of leaves. The feasibility of in planta leaf measurements was demonstrated, opening up many opportunities for the investigation of leaf structure and hydraulic functioning during development and/or in response to abiotic stresses.

Why it matches plant phenotyping methods葉の構造と水分状態を定量MRIで空間的に測定する新規手法を開発し、分類法と組み合わせて葉組織・葉脈を評価しており、植物フェノタイピング手法が中心である。

abstractThe purpose of this study was to develop an original approach based on transverse relaxation mapping by Magnetic Resonance Imaging for the detection of changes in water status and distribution at cell and tissue levels in Brassica napus leaves during blade development and dehydration.

The use of a portable X-ray fluorescence spectrometer for measuring nickel in plants: sample preparation and validation. →

X-ray fluorescence is a fast, cost-effective, and eco-friendly method for elemental analyses. Portable X-ray fluorescence spectrometers (pXRF) have proven instrumental in detecting metals across diverse matrices, including plants. However, sample preparation and measurement procedures need to be standardized for each instrument. This study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF, employing empirical calibration based on inductively coupled plasma optical emission spectroscopy (ICP-OES) Ni data. The evaluation involved 300 plant samples of 14 species with variable of Ni accumulation. Various dwell times (30, 60, 90, 120, 300 s) and sample masses (0.5, 1.0, 1.5, 2.0 g) were tested. Calibration models were developed through empirical and correction factor approaches. The results showed that the use of 1.0 g of sample (0.14 g cm -2 ) and a dwell time of 60 s for the study conditions were appropriate for detection by pXRF. Ni concentrations determined by ICP-OES were highly correlated (R 2 = 0.94) with those measured by the pXRF instrument. Therefore, pXRF can provide reliable detection of Ni in plant samples, avoiding the digestion of samples and reducing the decision-making time in environmental management.

Why it matches plant phenotyping methods植物試料中のNi濃度を測定するpXRF手法について、試料調製・測定条件・校正・ICP-OESとの比較検証を中心に扱っており、植物の元素状態を取得する測定法の技術的妥当性評価である。

abstractThis study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF

Plant Disease Detection Using Deep-Learning →

Abstract Increasing demands for food security and sustainable agriculture have spurred the development of innovative technologies in the agricultural sector. This initiative aims to tackle the pressing concern of plant diseases through the implementation of cutting-edge deep learning methodologies to ensure precise and effective disease identification. By harnessing the potential of deep neural networks, the system conducts an analysis of plant leaf images in order to detect indications and manifestations of diseases. By delivering a scalable, automated, and accurate solution, this novel strategy intends to destroy conventional plant disease detection techniques. By training a deep-learning model on a heterogeneous dataset of plant images, the project acquires knowledge of intricate patterns and characteristics that are linked to a multitude of diseases. By incorporating convolutional neural networks (CNNs), the model is capable of deriving hierarchical representations from input images, which aids in the intricate differentiation between diseased and healthy plant tissues. The potential of this technology's implementation in early disease detection is substantial; it would enable farmers to promptly execute interventions that prevent the transmission of infections, thereby ultimately enhancing crop productivity and promoting sustainability. By integrating state-of-the-art deep learning techniques with agricultural science, this endeavor tackles a pivotal facet of worldwide food production. In addition to facilitating the rapid identification of maladies, the plant disease detection system under consideration lays the groundwork for the future advancement of intelligent agricultural systems. The effective incorporation of technology in the agricultural sector serves as a noteworthy milestone in the progression towards precision farming, which guarantees the health of commodities and promotes sustainable methodologies that benefit both farmers and the global populace at large.

Why it matches plant phenotyping methods植物葉画像から病徴・健全組織をCNNで識別する手法が研究の中心であり、植物の病害状態を直接推定する画像ベース表現型計測に該当する。

abstractthe system conducts an analysis of plant leaf images in order to detect indications and manifestations of diseases

Elemental profiling and genome-wide association mapping reveal genomic variants modulating ionomic composition in Populus trichocarpa leaves →

The ionome represents elemental composition in plant tissues and can be an indicator of nutrient status as well as overall plant performance. Thus, identifying genetic determinants governing elemental uptake and storage is an important goal in plant breeding and engineering. In this study, we coupled high-throughput ionome characterization with high-resolution genome-wide association studies (GWAS) to uncover genetic loci that modulate ionomic composition in leaves of 584 black cottonwood poplar ( Populus trichocarpa ) genotypes. Congruence of alternate ionomic profiling platforms, i.e., inductively coupled plasma-mass spectrometry (ICP-MS), neutron activation analysis (NAA) and laser-induced breakdown spectroscopy (LIBS), was performed on leaf samples from a subset of the population. Significant agreement was observed across the three platforms with some notable exceptions for individual elements. Subsequently, we used the ICP-MS platform to profile the 584 genotypes focusing on 20 elements. GWAS performed using a set of high-density (>8.2 million) single nucleotide polymorphisms (SNP), identified multiple loci significantly associated with variations in these mineral elements. The potential causal genes for variations in the ionome were significantly enriched in genes whose homologs were previously associated to ion homeostasis in other species. Notably, a polymorphic copy of the high-affinity molybdenum transporter MOT1 was found directly associated to molybdenum content in leaf tissues. The results of the GWAS also provided evidence of physiological and genetic interactions between mineral elements in poplar. The new candidate genes predicted to play a key role in cross-homeostasis of multiple elements are new targets for engineering a variety of traits of interest in tree species.

Why it matches plant phenotyping methods葉の元素組成という植物状態を測定する複数の高スループット計測プラットフォームを比較・検証しており、GWASだけでなく表現型取得法の技術的評価が明示されています。

abstractwe coupled high-throughput ionome characterization with high-resolution genome-wide association studies (GWAS)

Genome-wide association study and network analysis of in vitro transformation in Populus trichocarpa support key roles of diverse phytohormone pathways and cross talk. →

Wide variation in amenability to transformation and regeneration (TR) among many plant species and genotypes presents a challenge to the use of genetic engineering in research and breeding. To help understand the causes of this variation, we performed association mapping and network analysis using a population of 1204 wild trees of Populus trichocarpa (black cottonwood). To enable precise and high-throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross-referenced complementary red, green, and blue (RGB) and fluorescent-hyperspectral images. We performed association mapping using single-marker and combined variant methods, followed by statistical tests for epistasis and integration of published multi-omic datasets to identify likely regulatory hubs. We report 409 candidate genes implicated by associations within 5 kb of coding sequences, and epistasis tests implicated 81 of these candidate genes as regulators of one another. Gene ontology terms related to protein-protein interactions and transcriptional regulation are overrepresented, among others. In addition to auxin and cytokinin pathways long established as critical to TR, our results highlight the importance of stress and wounding pathways. Potential regulatory hubs of signaling within and across these pathways include GROWTH REGULATORY FACTOR 1 (GRF1), PHOSPHATIDYLINOSITOL 4-KINASE β1 (PI-4Kβ1), and OBF-BINDING PROTEIN 1 (OBP1).

Why it matches plant phenotyping methodsRGB画像と蛍光ハイパースペクトル画像を統合したコンピュータビジョンシステムを開発し、カルスおよびシュートの形質転換・再生を高精度かつハイスループットに表現型解析することが中心的な方法論的貢献である。

abstractTo enable precise and high-throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross-referenced complementary red, green, and blue (RGB) and fluorescent-hyperspectral images.

Label-free structural imaging of plant roots and microbes using third- harmonic generation microscopy →

ABSTRACT Root biology is pivotal in addressing global challenges including sustainable agriculture and climate change. However, roots have been relatively understudied among plant organs, partly due to the difficulties in imaging root structures in their natural environment. Here we used microfabricated ecosystems (EcoFABs) to establish growing environments with optical access and employed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution. THG enabled us to observe key plant root structures including the vasculature, Casparian strips, dividing meristematic cells, and root cap cells, as well as subcellular features including nuclear envelopes, nucleoli, starch granules, and putative stress granules. THG from the cell walls of bacteria and fungi also provides label-free contrast for visualizing these microbes in the root rhizosphere. With simultaneously recorded 3PF fluorescence signal, we demonstrated our ability to investigate root-microbe interactions by achieving single-bacterium tracking and subcellular imaging of fungal spores and hyphae in the rhizosphere.

Why it matches plant phenotyping methodsTHG・3PFによる生根の構造と細胞内特徴を、ラベルフリーかつ生体内で可視化するイメージング手法が研究の中心であり、植物形態・状態の表現型取得に直接関与する。

abstractemployed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution

Mechanistic and data-driven perspectives on plant uptake of organic pollutants. →

Establishing reliable predictive models for plant uptake of organic pollutants is crucial for environmental risk assessment and guiding phytoremediation efforts. This study compiled an expanded dataset of plant cuticle-water partition coefficients (K cw ), a useful indicator for plant uptake, for 371 data points of 148 unique compounds and various plant species. Quantum/computational chemistry software and tools were utilized to compute various molecular descriptors, aiming to comprehensively characterize the properties and structures of each compound. Three types of models were developed to predict K cw : a mechanism-driven pp-LFER model, a data-driven machine learning model, and an integrated mechanism-data-driven model. The mechanism-data-driven GBRT-ppLFER model exhibited superior performance, achieving RMSE train = 0.133 and RMSE test = 0.301 while maintaining interpretability. The Shapley Additive Explanation analysis indicated that pp-LFER parameters, ESPI, FwRadicalmax, ExtFP607, and RDF70s are the key factors influencing plant uptake in the GBRT-ppLFER model. Overall, pp-LFER parameter, ESPI, and ExtFP607 show positive effects, while the remaining factors exhibit negative effects. Partial dependency analysis further indicated that plant uptake is not solely determined by individual factors but rather by the combined interactions of multiple factors. Specifically, compounds with ppLFER parameter >4, ESPI > -25.5, 0.098 cw values from the GBRT-ppLFER model were effectively employed to estimate the plant-water partition coefficients and bioconcentration factors across different plant species and growth media (water, sand, and soil), achieving an outstanding performance with an RMSE of 0.497. This study provides effective tools for assessing plant uptake of organic pollutants and deepens our understanding of plant-environment-compound interactions.

Why it matches plant phenotyping methods植物による有機汚染物質の取り込み量・植物水分配係数を推定する機構モデル、機械学習モデル、統合モデルを開発・評価しており、植物の取り込み状態を抽出する計算手法が研究の中心である。

abstractThree types of models were developed to predict K cw : a mechanism-driven pp-LFER model, a data-driven machine learning model, and an integrated mechanism-data-driven model.

Quantitative RNA spatial profiling using single-molecule RNA FISH on plant tissue cryosections →

ABSTRACT Single-molecule fluorescence in situ hybridization (smFISH) has emerged as a powerful tool to study gene expression dynamics with unparalleled precision and spatial resolution in a variety of biological systems. Recent advancements have expanded its application to encompass plant studies, yet a demand persists for a simple and robust smFISH method adapted to plant tissue sections. Here, we present an optimized smFISH protocol (cryo-smFISH) for visualizing and quantifying single mRNA molecules in plant tissue cryosections. This method exhibits remarkable sensitivity, capable of detecting low-expression transcripts, including long non-coding RNAs. Integrating a deep learning-based algorithm in our image analysis pipeline, our method enables us to assign RNA abundance precisely in nuclear and cytoplasmic compartments. Compatibility with Immunofluorescence also allows RNA and endogenous proteins to be visualized and quantified simultaneously. Finally, this study presents for the first time the use of smFISH for single-cell RNA sequencing (scRNA-seq) validation in plants. By extending the smFISH method to plant cryosections, an even broader community of plant scientists will be able to exploit the multiple potentials of quantitative transcript analysis at cellular and subcellular resolutions.

Why it matches plant phenotyping methods植物組織切片向けにsmFISHプロトコルと画像解析を最適化し、細胞内RNA量を定量する方法を開発しており、植物状態の測定手法が中心である。

abstractHere, we present an optimized smFISH protocol (cryo-smFISH) for visualizing and quantifying single mRNA molecules in plant tissue cryosections.

A robust transformer-based pipeline of 3D cell alignment, denoise and instance segmentation on electron microscopy sequence images →

Germline cells are critical for transmitting genetic information to subsequent generations in biological organisms. While their differentiation from somatic cells during embryonic development is well-documented in most animals, the regulatory mechanisms initiating plant germline cells are not well understood. To thoroughly investigate the complex morphological transformations of their ultrastructure over developmental time, nanoscale 3D reconstruction of entire plant tissues is necessary, achievable exclusively through electron microscopy imaging. This paper presents a full-process framework designed for reconstructing large-volume plant tissue from serial electron microscopy images. The framework ensures end-to-end direct output of reconstruction results, including topological networks and morphological analysis. The proposed 3D cell alignment, denoise, and instance segmentation pipeline (3DCADS) leverages deep learning to provide a cell instance segmentation workflow for electron microscopy image series, ensuring accurate and robust 3D cell reconstructions with high computational efficiency. The pipeline involves five stages: the registration of electron microscopy serial images; image enhancement and denoising; semantic segmentation using a Transformer-based neural network; instance segmentation through a supervoxel-based clustering algorithm; and an automated analysis and statistical assessment of the reconstruction results, with the mapping of topological connections. The 3DCADS model's precision was validated on a plant tissue ground-truth dataset, outperforming traditional baseline models and deep learning baselines in overall accuracy. The framework was applied to the reconstruction of early meiosis stages in the anthers of Arabidopsis thaliana, resulting in a topological connectivity network and analysis of morphological parameters and characteristics of cell distribution. The experiment underscores the 3DCADS model's potential for biological tissue identification and its significance in quantitative analysis of plant cell development, crucial for examining samples across different genetic phenotypes and mutations in plant development. Additionally, the paper discusses the regulatory mechanisms of Arabidopsis thaliana's germline cells and the development of stamen cells before meiosis, offering new insights into the transition from somatic to germline cell fate in plants.

Why it matches plant phenotyping methods植物組織の3D画像再構成・細胞インスタンス分割・形態解析を行う手法が研究の中心であり、植物組織データセットで検証されています。

abstractThis paper presents a full-process framework designed for reconstructing large-volume plant tissue from serial electron microscopy images.

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue →

Abstract Accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease‐resistant crop varieties. Here, a phenotyping platform for rapid, continuous‐time, and quantitative assessment of HR is demonstrated: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating detection of microscopic levels of cell death. Validation is performed by transiently expressing the effector protein AVRblb2 in transgenic Nicotiana benthamiana (expressing the corresponding resistance protein Rpi‐blb2) to reliably induce HR. Detection of cell death is achieved at microscopic intensities, where leaf tissue appears healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously. This data is used to develop supervised machine‐learning (ML) models for classification of HR. Input data (inclusive of the entire tested concentration range) is classified as HR‐positive or negative with 84.1% mean accuracy (F1 score = 0.75) at 1 h and with 87.8% mean accuracy (F1 score = 0.81) at 22 h. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

Why it matches plant phenotyping methods植物組織のプログラム細胞死・過敏感反応を電気インピーダンスで連続定量するフェノタイピング基盤を開発し、機械学習分類も検証しているため、方法が研究の中心である。

abstractHere, a phenotyping platform for rapid, continuous‐time, and quantitative assessment of HR is demonstrated: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL).

Imaging plant cell walls using fluorescent stains: The beauty is in the details →

Abstract Plants continuously face various environmental stressors throughout their lifetime. To be able to grow and adapt in different environments, they developed specialized tissues that allowed them to maintain a protected yet interconnected body. These tissues undergo specific primary and secondary cell wall modifications that are essential to ensure normal plant growth, adaptation and successful land colonization. The composition of cell walls can vary among different plant species, organs and tissues. The ability to remodel their cell walls is fundamental for plants to be able to cope with multiple biotic and abiotic stressors. A better understanding of the changes taking place in plant cell walls may help identify and develop new strategies as well as tools to enhance plants’ survival under environmental stresses or prevent pathogen attack. Since the invention of microscopy, numerous imaging techniques have been developed to determine the composition and dynamics of plant cell walls during normal growth and in response to environmental stimuli. In this review, we discuss the main advances in imaging plant cell walls, with a particular focus on fluorescent stains for different cell wall components and their compatibility with tissue clearing techniques. Lay Description : Plants are continuously subjected to various environmental stresses during their lifespan. They evolved specialized tissues that thrive in different environments, enabling them to maintain a protected yet interconnected body. Such tissues undergo distinct primary and secondary cell wall alterations essential to normal plant growth, their adaptability and successful land colonization. Cell wall composition may differ among various plant species, organs and even tissues. To deal with various biotic and abiotic stresses, plants must have the capacity to remodel their cell walls. Gaining insight into changes that take place in plant cell walls will help identify and create novel tools and strategies to improve plants’ ability to withstand environmental challenges. Multiple imaging techniques have been developed since the introduction of microscopy to analyse the composition and dynamics of plant cell walls during growth and in response to environmental changes. Advancements in plant tissue cleaning procedures and their compatibility with cell wall stains have significantly enhanced our ability to perform high‐resolution cell wall imaging. At the same time, several factors influence the effectiveness of cleaning and staining plant specimens, as well as the time necessary for the process, including the specimen's size, thickness, tissue complexity and the presence of autofluorescence. In this review, we will discuss the major advances in imaging plant cell walls, with a particular emphasis on fluorescent stains for diverse cell wall components and their compatibility with tissue clearing techniques. We hope that this review will assist readers in selecting the most appropriate stain or combination of stains to highlight specific cell wall components of interest.

Why it matches plant phenotyping methods植物細胞壁の蛍光染色・組織透明化とイメージング技術を中心に整理した方法論レビューであり、植物の形態・状態の画像取得手法が主題である。

abstractIn this review, we discuss the main advances in imaging plant cell walls, with a particular focus on fluorescent stains for different cell wall components and their compatibility with tissue clearing techniques.

Water exchange between the Chlorenchyma and the Hydrenchyma and its physiological role in leaves with Crassulacean acid metabolism. →

Direct and non-destructive measurements of plant-water relations of plants exhibiting the Crassulacean acid metabolism (CAM) photosynthetic pathway are seldom addressed, with most findings inferred from gas exchange measurements. The main focus of this paper was to study how the water exchange between the chlorenchyma and the hydrenchyma depends on and follows the CAM photosynthetic diel pattern using non-invasive and continuous methods. Gas exchange and leaf patch clamp pressure probe (LPCP) measurements were performed on Aloe vera (L.) Burm f., a CAM species, and compared to measurements on banana (Musa acuminata Colla), a C 3 species. The LPCP output pressure, P p , of Aloe vera plants follows its diel CAM photosynthetic cycle, reversed to that observed in banana and other C 3 species. The four phases of CAM photosynthesis can also be identified in the diel LPCP output pressure, P p , cycle. The P p values in Aloe vera are determined by the hydrenchyma turgor pressure, with both parameters being reversely related. A non-invasive and continuous assessment of the water exchange between the chlorenchyma and the hydrenchyma in CAM plants, namely, by following the changes in the hydrenchyma turgor pressure, is presented. However, showing once more how the LPCP output pressure, P p , depends on the leaf structure, such an approach can be used to study plant-water relations in other CAM species with a leaf structure similar to Aloe vera, with the hydrenchyma composing most of the leaf volume.

Why it matches plant phenotyping methodsLPCPを用いた非侵襲・連続的な葉内水交換および水分状態の測定法を中心に提示しており、植物生理形質の取得方法が研究の主要目的である。

abstractDirect and non-destructive measurements of plant-water relations of plants exhibiting the Crassulacean acid metabolism (CAM) photosynthetic pathway are seldom addressed

A rapid and robust colorimetric method for measuring relative abundance of auxins in plant tissues →

Abstract Introduction Auxin estimation in plant tissues is a crucial component of auxin signaling studies. Despite the availability of various high‐throughput auxin quantification methods like LC‐MS, GC‐MS, HPLC, biosensors, and DR5‐ gus/gfp ‐based assays, auxin quantification remains troublesome because these techniques are very expensive and technology intensive and they mostly involve elaborate sample preparation or require the development of transgenic plants. Objectives To find a solution to these problems, we made use of an old auxin detection system to quantify microbe derived auxins and modified it to effectively measure auxin levels in rice plants. Materials and methods Auxins from different tissues of rice plants, including root samples of seedlings exposed to IAA/TIBA or subjected to different abiotic stresses, were extracted in ethanol. The total auxin level was measured by the presently described colorimetric assay and counterchecked by other auxin estimation methods like LC‐MS or gus staining of DR5‐ gus overexpressing lines. Results The presented colorimetric method could measure (1) the auxin levels in different tissues of rice plants, thus identifying the regions of higher auxin abundance, (2) the differential accumulation of auxins in rice roots when auxin or its transport inhibitor was supplied exogenously, and (3) the levels of auxin in roots of rice seedlings subjected to various abiotic stresses. The thus obtained auxin levels correlated well with the auxin levels determined by other methods like LC‐MS or gus staining and the expression pattern of auxin biosynthesis pathway genes. Conclusions The auxin estimation method described here is simple, rapid, cost‐effective, and sensitive and allows for the efficient detection of relative auxin abundances in plant tissues.

Why it matches plant phenotyping methods植物組織中のオーキシン量という生理形質を測定する、迅速・低コストな比色フェノタイピング法を開発し、LC-MS等で検証しているため。

abstractwe made use of an old auxin detection system to quantify microbe derived auxins and modified it to effectively measure auxin levels in rice plants

A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context →

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We developed a novel approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg, and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters. We also share a diverse high-quality training dataset of about 10,000 nuclei. Furthermore, we advanced the MorphoGraphX analysis and visualization software by, among other things, providing a method for linking 3D segmented nuclei to their surrounding cells in 3D digital organs. We found that the nuclear-to-cell volume ratio varies between different ovule tissues and during the development of a tissue. Finally, we extended the PlantSeg 3D segmentation pipeline with a proofreading script that uses 3D segmented nuclei as seeds to correct cell segmentation errors in difficult-to-segment tissues. Summary StatementWe present computational tools that allow versatile and accurate 3D nuclear segmentation in plant organs, enable the analysis of cell-nucleus geometric relationships, and improve the accuracy of 3D cell segmentation.

Why it matches plant phenotyping methods植物器官の3D核・細胞形態を定量化する画像解析ツール、学習モデル、データセット、セグメンテーション改良法が研究の中心であり、植物の形態状態を抽出するフェノタイピング手法に該当する。

abstractWe present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs.

Root Expansion Microscopy (ROOT-ExM): A streamlined super resolution method for plants →

Expansion microscopy (ExM) has revolutionized biological imaging by physically enlarging samples, surpassing the light diffraction limit and enabling nanoscale visualization using standard microscopes. While extensively employed across a wide range of biological samples, its application to plant tissues is sparse. In this work, we present ROOT-ExM, an expansion method suited for stiff and intricate multicellular plant tissues, focusing on the primary root of Arabidopsis thaliana. ROOT-ExM achieves isotropic expansion with a fourfold increase in resolution, enabling super-resolution microscopy comparable to STimulated Emission Depletion (STED) microscopy. Labelling is achieved through immunolocalization, compartment-specific dyes, and native fluorescence preservation, while N-Hydroxysuccinimide (NHS) ester-dye conjugates reveal the ultrastructural context of cells alongside specific labelling. We successfully applied ROOT-ExM to image various cellular structures, including the Golgi apparatus, the endoplasmic reticulum, the cytoskeleton, and wall-embedded structures such as plasmodesmata. When combined with lattice light sheet microscopy (LLSM), ROOT-ExM achieves 3D quantitative analysis of nanoscale cellular process, revealing increased vesicular fusion in close proximity of the cell plate during cell division. Achieving super-resolution fluorescence imaging in plant biology remains a formidable challenge. Our findings underscore that ROOT-ExM provides a remarkable, cost-effective solution to this challenge, paving the way for unprecedented insights into plant cellular subcellular architecture. One sentence summaryROOT-ExM achieves super-resolution expansion microscopy in plants

Why it matches plant phenotyping methods植物組織向けの超解像イメージング手法そのものを開発し、細胞構造の3D定量解析に応用しており、画像取得法が研究の中心である。

abstractIn this work, we present ROOT-ExM, an expansion method suited for stiff and intricate multicellular plant tissues, focusing on the primary root of Arabidopsis thaliana.

Bi-directional hyperspectral reconstruction of cherry tomato: diagnosis of internal tissues maturation stage and composition →

Introduction Precision monitoring maturity in climacteric fruits like tomato is crucial for minimising losses within the food supply chain and enhancing pre- and post-harvest production and utilisation. Objectives This paper introduces an approach to analyse the precision maturation of tomato using hyperspectral tomography-like. Methods A novel bi-directional spectral reconstruction method is presented, leveraging visible to near-infrared (Vis-NIR) information gathered from tomato spectra and their internal tissues (skin, pulp, and seeds). The study, encompassing 118 tomatoes at various maturation stages, employs a multi-block hierarchical principal component analysis combined with partial least squares for bi-directional reconstruction. The approach involves predicting internal tissue spectra by decomposing the overall tomato spectral information, creating a superset with eight latent variables for each tissue. The reverse process also utilises eight latent variables for reconstructing skin, pulp, and seed spectral data. Results The reconstruction of the tomato spectra presents a mean absolute percentage error of 30.44 % and 5.37 %, 5.25 % and 6.42 % and Pearson's correlation coefficient of 0.85, 0.98, 0.99 and 0.99 for the skin, pulp and seed, respectively. Quality parameters, including soluble solid content (%), chlorophyll (a.u.), lycopene (a.u.), and puncture force (N), were assessed and modelled with PLS with the original and reconstructed datasets, presenting a range of R2 higher than 0.84 in the reconstructed dataset. An empirical demonstration of the tomato maturation in the internal tissues revealed the dynamic of the chlorophyll and lycopene in the different tissues during the maturation process. Conclusion The proposed approach for inner tomato tissue spectral inference is highly reliable, provides early indications and is easy to operate. This study highlights the potential of Vis-NIR devices in precision fruit maturation assessment, surpassing conventional labour-intensive techniques in cost-effectiveness and efficiency. The implications of this advancement extend to various agronomic and food chain applications, promising substantial improvements in monitoring and enhancing fruit quality.

Why it matches plant phenotyping methodsトマト内部組織の成熟状態・品質特性を推定する双方向ハイパースペクトル再構成法が研究の中心であり、再構成精度と品質パラメータ推定性能も評価しているため、植物フェノタイピング手法として収録する。

abstractA novel bi-directional spectral reconstruction method is presented, leveraging visible to near-infrared (Vis-NIR) information gathered from tomato spectra and their internal tissues (skin, pulp, and seeds).

Assaying Effector Cell-to-Cell Mobility in Plant Tissues Identifies Hypermobility and Indirect Manipulation of Plasmodesmata →

In plants, plasmodesmata establish cytoplasmic continuity between cells to allow for communication and resource exchange across the cell wall. While plant pathogens use plasmodesmata as a pathway for both molecular and physical invasion, the benefits of molecular invasion (cell-to-cell movement of pathogen effectors) are poorly understood. To establish a methodology for identification and characterization of the cell-to-cell mobility of effectors, we performed a quantitative live imaging-based screen of candidate effectors of the fungal pathogen Colletotrichum higginsianum. We predicted C. higginsianum effectors by their expression profiles, the presence of a secretion signal, and their predicted and in planta localization when fused to green fluorescent protein. We assayed for cell-to-cell mobility of nucleocytosolic effectors and identified 14 that are cell-to-cell mobile. We identified that three of these effectors are “hypermobile,” showing cell-to-cell mobility greater than expected for a protein of that size. To explore the mechanism of hypermobility, we chose two hypermobile effectors and measured their impact on plasmodesmata function and found that even though they show no direct association with plasmodesmata, each increases the transport capacity of plasmodesmata. Thus, our methods for quantitative analysis of cell-to-cell mobility of candidate microbe-derived effectors, or any suite of host proteins, can identify cell-to-cell hypermobility and offer greater understanding of how proteins affect plasmodesmal function and intercellular connectivity. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Why it matches plant phenotyping methods植物組織内のエフェクター細胞間移動を定量ライブイメージングで測定する方法を確立し、候補タンパク質の移動性と原形質連絡の輸送能力を評価しており、植物状態の取得法が中心的です。

abstractTo establish a methodology for identification and characterization of the cell-to-cell mobility of effectors, we performed a quantitative live imaging-based screen of candidate effectors of the fungal pathogen Colletotrichum higginsianum.

Fluorescence hybridization chain reaction enables localization of multiple molecular classes combined with plant cell ultrastructure →

ABSTRACT Background Recent developments in hybridization chain reaction (HCR) have enabled robust simultaneous localization of multiple mRNA transcripts using fluorescence in situ hybridization (FISH). Once multiple split initiator oligonucleotide probes bind their target mRNA, HCR uses DNA base-pairing of fluorophore-labeled hairpin sets to self-assemble into large polymers, amplifying the fluorescence signal and reducing non-specific background. Few studies have applied HCR in plants, despite its demonstrated utility in whole mount animal tissues and cell culture. Our aim was to optimize this technique for sectioned plant tissues embedded with paraffin and methacrylate resins, and to test its utility in combination with immunolocalization and subsequent correlation with cell ultrastructure using scanning electron microscopy. Results Application of HCR to 10 µm paraffin sections of 17-day-old Setaria viridis (green millet) inflorescences using confocal microscopy revealed that the transcripts of the transcription factor KNOTTED 1 ( KN1 ) were localized to developing floret meristem and vascular tissue while SHATTERING 1 ( SH1 ) and MYB26 transcripts were co-localized to the breakpoint below the floral structures (the abscission zone). We also used methacrylate de-embedment with 1.5 µm and 0.5 µm sections of 3-day-old Arabidopsis thaliana seedlings to show tissue specific CHLOROPHYLL BINDING FACTOR a/b ( CAB1 ) mRNA highly expressed in photosynthetic tissues and ELONGATION FACTOR 1 ALPHA ( EF1 α ) highly expressed in meristematic tissues of the shoot apex. The housekeeping gene ACTIN7 ( ACT7 ) mRNA was more uniformly distributed with reduced signals using lattice structured-illumination microscopy. HCR using 1.5 µm methacrylate sections was followed by backscattered imaging and scanning electron microscopy thus demonstrating the feasibility of correlating fluorescent localization with ultrastructure. Conclusion HCR was successfully adapted for use with both paraffin and methacrylate de-embedment on diverse plant tissues in two model organisms, allowing for concurrent cellular and subcellular localization of multiple mRNAs, antibodies and other affinity probe classes. The mild hybridization conditions used in HCR made it highly amenable to observe immunofluorescence in the same section. De-embedded semi-thin methacrylate sections with HCR were compatible with correlative electron microscopy approaches. Our protocol provides numerous practical tips for successful HCR and affinity probe labeling in electron microscopy-compatible, sectioned plant material.

Why it matches plant phenotyping methods植物組織で複数mRNAを局在化するHCR法を最適化し、異なる切片材料・モデル植物・顕微鏡法で実証した方法開発研究である。

abstractOur aim was to optimize this technique for sectioned plant tissues embedded with paraffin and methacrylate resins, and to test its utility in combination with immunolocalization and subsequent correlation with cell ultrastructure using scanning electron microscopy.

Vibrational spectroscopic profiling of biomolecular interactions between oak powdery mildew and oak leaves. →

Oak powdery mildew, caused by the biotrophic fungus Erysiphe alphitoides , is a prevalent disease affecting oak trees, such as English oak ( Quercus robur ). While mature oak populations are generally less susceptible to this disease, it can endanger young oak seedlings and new leaves on mature trees. Although disruptions of photosynthate and carbohydrate translocation have been observed, accurately detecting and understanding the specific biomolecular interactions between the fungus and the leaves of oak trees is currently lacking. Herein, via hybrid Raman spectroscopy combined with an advanced artificial neural network algorithm, the underpinning biomolecular interactions between biological soft matter, i.e. , Quercus robur leaves and Erysiphe alphitoides , are investigated and profiled, generating a spectral library and shedding light on the changes induced by fungal infection and the tree's defence response. The adaxial surfaces of oak leaves are categorised based on either the presence or absence of Erysiphe alphitoides mildew and further distinguishing between covered or not covered infected leaf tissues, yielding three disease classes including healthy controls, non-mildew covered and mildew-covered. By analysing spectral changes between each disease category per tissue type, we identified important biomolecular interactions including disruption of chlorophyll in the non-vein and venule tissues, pathogen-induced degradation of cellulose and pectin and tree-initiated lignification of cell walls in response, amongst others, in lateral vein and mid-vein tissues. Via our developed computational algorithm, the underlying biomolecular differences between classes were identified and allowed accurate and rapid classification of disease with high accuracy of 69.6% for non-vein, 73.5% for venule, 82.1% for lateral vein and 85.6% for mid-vein tissues. Interfacial wetting differences between non-mildew covered and mildew-covered tissue were further analysed on the surfaces of non-vein and venule tissue. The overall results demonstrated the ability of Raman spectroscopy, combined with advanced AI, to act as a powerful and specific tool to probe foliar interactions between forest pathogens and host trees with the simultaneous potential to probe and catalogue molecular interactions between biological soft matter, paving the way for exploring similar relations in broader forest tree-pathogen systems.

Why it matches plant phenotyping methods葉の感染状態をRaman分光とニューラルネットワークで分類・推定する手法を開発し、疾患クラス分類性能も評価しており、植物フェノタイピング手法が中心である。

abstractvia hybrid Raman spectroscopy combined with an advanced artificial neural network algorithm

Automatic 3D cell segmentation of fruit parenchyma tissue from X-ray micro CT images using deep learning →

Background High quality 3D information of the microscopic plant tissue morphology-the spatial organization of cells and intercellular spaces in tissues-helps in understanding physiological processes in a wide variety of plants and tissues. X-ray micro-CT is a valuable tool that is becoming increasingly available in plant research to obtain 3D microstructural information of the intercellular pore space and individual pore sizes and shapes of tissues. However, individual cell morphology is difficult to retrieve from micro-CT as cells cannot be segmented properly due to negligible density differences at cell-to-cell interfaces. To address this, deep learning-based models were trained and tested to segment individual cells using X-ray micro-CT images of parenchyma tissue samples from apple and pear fruit with different cell and porosity characteristics. Results The best segmentation model achieved an Aggregated Jaccard Index (AJI) of 0.86 and 0.73 for apple and pear tissue, respectively, which is an improvement over the current benchmark method that achieved AJIs of 0.73 and 0.67. Furthermore, the neural network was able to detect other plant tissue structures such as vascular bundles and stone cell clusters (brachysclereids), of which the latter were shown to strongly influence the spatial organization of pear cells. Based on the AJIs, apple tissue was found to be easier to segment, as the porosity and specific surface area of the pore space are higher and lower, respectively, compared to pear tissue. Moreover, samples with lower pore network connectivity, proved very difficult to segment. Conclusions The proposed method can be used to automatically quantify 3D cell morphology of plant tissue from micro-CT instead of opting for laborious manual annotations or less accurate segmentation approaches. In case fruit tissue porosity or pore network connectivity is too low or the specific surface area of the pore space too high, native X-ray micro-CT is unable to provide proper marker points of cell outlines, and one should rely on more elaborate contrast-enhancing scan protocols.

Why it matches plant phenotyping methodsX線マイクロCT画像から植物組織の個別細胞形態を3D定量化する深層学習セグメンテーション手法を開発・ベンチマークしており、植物表現型取得が研究の中心です。

abstractdeep learning-based models were trained and tested to segment individual cells using X-ray micro-CT images of parenchyma tissue samples from apple and pear fruit

Biospectroscopic fingerprinting phytotoxicity towards environmental monitoring for food security and contaminated site remediation. →

Human activities have resulted in severe environmental pollution since the industrial revolution. Phytotoxicity-based environmental monitoring is well known due to its sedentary nature, abundance, and sensitivity to environmental changes, which are essential preconditions to avoiding potential environmental and ecological risks. However, conventional morphological and physiological methods for phytotoxicity assessment mainly focus on descriptive determination rather than mechanism analysis and face challenges of labour and time-consumption, lack of standardized protocol and difficulties in data interpretation. Molecular-based tests could reveal the toxicity mechanisms but fail in real-time and in-situ monitoring because of their endpoint manner and destructive operation in collecting cellular components. Herein, we systematically propose and lay out a biospectroscopic tool (e.g., infrared and Raman spectroscopy) coupled with multivariate data analysis as a relatively non-destructive and high-throughput approach to quantitatively measure phytotoxicity levels and qualitatively profile phytotoxicity mechanisms by classifying spectral fingerprints of biomolecules in plant tissues in response to environmental stresses. With established databases and multivariate analysis, this biospectroscopic fingerprinting approach allows ultrafast, in situ and on-site diagnosis of phytotoxicity. Overall, the proposed protocol and validation of biospectroscopic fingerprinting phytotoxicity can distinguish the representative biomarkers and interrogate the relevant mechanisms to quantify the stresses of interest, e.g., environmental pollutants. This state-of-the-art concept and design broaden the knowledge of phytotoxicity assessment, advance novel implementations of phytotoxicity assay, and offer vast potential for long-term field phytotoxicity monitoring trials in situ.

Why it matches plant phenotyping methods植物組織のスペクトル情報と多変量解析により植物毒性を定量・判定するバイオスペクトロスコピー手法を提案・検証しており、植物状態の取得が中心である。

abstractwe systematically propose and lay out a biospectroscopic tool (e.g., infrared and Raman spectroscopy) coupled with multivariate data analysis as a relatively non-destructive and high-throughput approach to quantitatively measure phytotoxicity levels

Plant Cell Wall Enzymatic Deconstruction: Bridging the Gap Between Micro and Nano Scales →

Understanding and overcoming the resistance of plant cell wall to enzymatic deconstruction is crucial to achieve a sustainable and economical conversion of plant biomass to bio-based products as alternatives to petroleum-based products. Despite the significant scientific advances over the past decades, the plant cell wall deconstruction at cell and tissue scales has remained under-investigated. In this study, to quantitatively characterize plant cell wall deconstruction, we set up an original imaging pipeline by combining time-lapse 4D (space + time) fluorescence confocal imaging, and a novel computational tool, to track and quantify cell wall deconstruction at cell and tissue scales offering a digital representation of cell wall deconstruction. Using this pipeline on poplar wood sections, we computed dynamics of several cellular parameters (e.g. cell wall volume, surface area, and number of cell neighbors) while measuring cellulose conversion. The results showed that the effect of enzymatic deconstruction at the cell scale is predominantly noticeable in terms of cell wall volume reduction rather than a significant decrease in surface area and accessible surface area. The results also revealed a negative correlation between pre-hydrolysis 3D cell wall compactness measures and volumetric cell wall deconstruction. The strength of this correlation was modulated by enzymatic activity. Combining cell wall compactness with the number of neighboring cells as a tissue-scale parameter yielded a stronger correlation. Our results also revealed a strong positive correlation between average volumetric cell wall deconstruction and cellulose conversion, thus establishing a link between key parameters and bridging the gap between nano and micro scales.

Why it matches plant phenotyping methods植物細胞壁の分解状態を定量化する4D蛍光画像パイプラインと計算ツールの開発が研究の中心であり、細胞壁体積・表面積・細胞隣接数などの植物組織形質を抽出している。

abstractwe set up an original imaging pipeline by combining time-lapse 4D (space + time) fluorescence confocal imaging, and a novel computational tool, to track and quantify cell wall deconstruction at cell and tissue scales

High Throughput Tomography (HiTT) on EMBL beamline P14 on PETRA III. →

Here, high-throughput tomography (HiTT), a fast and versatile phase-contrast imaging platform for life-science samples on the EMBL beamline P14 at DESY in Hamburg, Germany, is presented. A high-photon-flux undulator beamline is used to perform tomographic phase-contrast acquisition in about two minutes which is linked to an automated data processing pipeline that delivers a 3D reconstructed data set less than a minute and a half after the completion of the X-ray scan. Combining this workflow with a sophisticated robotic sample changer enables the streamlined collection and reconstruction of X-ray imaging data from potentially hundreds of samples during a beam-time shift. HiTT permits optimal data collection for many different samples and makes possible the imaging of large sample cohorts thus allowing population studies to be attempted. The successful application of HiTT on various soft tissue samples in both liquid (hydrated and also dehydrated) and paraffin-embedded preparations is demonstrated. Furthermore, the feasibility of HiTT to be used as a targeting tool for volume electron microscopy, as well as using HiTT to study plant morphology, is demonstrated. It is also shown how the high-throughput nature of the work has allowed large numbers of `identical' samples to be imaged to enable statistically relevant sample volumes to be studied.

Why it matches plant phenotyping methods高速X線トモグラフィー、ロボット試料交換、自動再構成を統合した高スループット画像化プラットフォームが主題であり、植物形態の画像計測への適用も明示されている。

abstracthigh-throughput tomography (HiTT), a fast and versatile phase-contrast imaging platform for life-science samples

Water exchange between the Chlorenchyma and the Hydrenchyma and its physiological role in leaves with Crassulacean acid metabolism →

Direct and non‐destructive measurements of plant‐water relations of plants exhibiting the Crassulacean acid metabolism (CAM) photosynthetic pathway are seldom addressed, with most findings inferred from gas exchange measurements. The main focus of this paper was to study how the water exchange between the chlorenchyma and the hydrenchyma depends on and follows the CAM photosynthetic diel pattern using non‐invasive and continuous methods. Gas exchange and leaf patch clamp pressure probe (LPCP) measurements were performed on Aloe vera (L.) Burm f., a CAM species, and compared to measurements on banana (Musa acuminata Colla), a C₃ species. The LPCP output pressure, Pₚ, of Aloe vera plants follows its diel CAM photosynthetic cycle, reversed to that observed in banana and other C₃ species. The four phases of CAM photosynthesis can also be identified in the diel LPCP output pressure, Pₚ, cycle. The Pₚ values in Aloe vera are determined by the hydrenchyma turgor pressure, with both parameters being reversely related. A non‐invasive and continuous assessment of the water exchange between the chlorenchyma and the hydrenchyma in CAM plants, namely, by following the changes in the hydrenchyma turgor pressure, is presented. However, showing once more how the LPCP output pressure, Pₚ, depends on the leaf structure, such an approach can be used to study plant‐water relations in other CAM species with a leaf structure similar to Aloe vera, with the hydrenchyma composing most of the leaf volume.

Why it matches plant phenotyping methodsLPCPを用いた非侵襲・連続的な葉内水分交換／ハイドレンキマの膨圧測定を中心に、CAM植物の水分状態を評価する方法を提示・適用しているため。

abstractA non‐invasive and continuous assessment of the water exchange between the chlorenchyma and the hydrenchyma in CAM plants, namely, by following the changes in the hydrenchyma turgor pressure, is presented.

Characterisation and optical detection of puffy Satsuma mandarin →

Puffiness is one of the dominant postharvest disorders in easy-peeling citrus cultivars. In this study, the structural changes between healthy and puffy Satsuma mandarin were investigated and the potential of using optical methods for disorder detection was explored. To gain more insight in this disorder, the external appearance and internal quality attributes were first compared between healthy and puffy Iwasaki Satsuma mandarins at three harvest times. Although no consistent differences were observed in the appearance of fruits, the soluble solids content and Brix minus acid values in puffy mandarin were found to be higher compared to the corresponding healthy fruit. The structural properties of the flavedo and albedo tissue layer in the peel were quantified from X-ray CT scans. Whilst no differences were observed in the size of the oil glands in the flavedo, the pore size in the albedo of puffy mandarin was found to be larger with later harvest. The bulk optical properties of the intact fruit were estimated from laser scatter images with a metamodel calibrated on optical phantoms. The reduced scattering coefficient (μₛ') for the intact fruit was found to be lower in puffy mandarin relative to healthy fruit. The distinction between healthy and puffy mandarin based on μₛ' was further validated on Goku Wase Satsuma mandarin. The results obtained indicate that healthy and puffy mandarin can be separated well based on their μₛ' at all the selected wavelengths. This provides a basis for the non-destructive optical detection of puffing disorder at an early stage.

Why it matches plant phenotyping methods柑橘果実の生理・構造状態（puffiness）を光学計測とX線CTで非破壊検出する方法を開発・検証しており、植物フェノタイピング手法が中心である。

abstractthe potential of using optical methods for disorder detection was explored

An open-source machine-learning approach for obtaining high-quality quantitative wood anatomy data from E. grandis and P. radiata xylem. →

Quantitative wood anatomy is a subfield in dendrochronology that requires effective open-source image analysis tools. In this research, the bioimage analysis software QuPath (v0.4.4) is introduced as a candidate for accurately quantifying the cellular properties of the xylem in an automated manner. Additionally, the potential of QuPath to detect the transition of early- to latewood tracheids over the growing season was evaluated to assess a potential application in dendroecological studies. Various algorithms in QuPath were optimized to quantify different xylem cell types in Eucalyptus grandis and the transition of early- to latewood tracheids in Pinus radiata. These algorithms were coded into cell detection scripts for automatic quantification of stem microsections and compared to a manually curated method to assess the accuracy of the cell detections. The automatic cell detection approach, using QuPath, has been validated to be reproducible with an acceptable error when assessing fibers, vessels, early- and latewood tracheids. However, further optimization for parenchyma is still required. This proposed method developed in QuPath provides a scalable and accurate approach for quantifying anatomical features in stem microsections. With minor amendments to the detection and classification algorithms, this strategy is likely to be viable in other plant species.

Why it matches plant phenotyping methods植物木部細胞の解剖学的形質を画像から自動抽出するQuPathベースの手法を開発・最適化し、手動法との比較で精度と再現性を検証しているため、フェノタイピング手法が中心です。

abstractthe bioimage analysis software QuPath (v0.4.4) is introduced as a candidate for accurately quantifying the cellular properties of the xylem in an automated manner.

Precision maturation assessment of grape tissues: Hyperspectral bi-directional reconstruction using tomography-like based on multi-block hierarchical principal component analysis →

This paper introduces a tomography-like method for assessing grape maturation. It analyses inner tissue spectra through point-of-measurement (POM) sensing. A multi-block hierarchical principal component analysis (MHPCA) algorithm was used for the spectral reconstruction of total grapes (skin, pulp, and seed). Two grape cultivars, Loureiro (white; n = 216) and Vinhão (red; n = 205) were measured at 12 dates after veraison (DAV). The reconstructed spectra showed no significant differences (p < 0.001) from the originals for both grapes. Loureiro had better statistical metrics (Person's correlation coefficient (r) values for: total grape: 0.99, skin: 1; pulp: 1, seed: 0.94) than Vinhão (r values for: total grape: 0.92, skin: 0.92; pulp: 0.95, seed: 0.95). Using self-learning artificial intelligence (SL-AI), the following parameters were predicted for both grapes: soluble solids content (%; MAPE <13%), puncture force (N; MAPE <29%), chlorophyll content (a.u.; MAPE <29%), and anthocyanin content (a.u.; MAPE <17%, Vinhão only). When comparing observed values with predicted skin, pulp, and seed spectra, Vinhão showed no statistical differences for most parameters, except pulp chlorophyll on one DAV in the final maturation stage. The same was done with the Loureiro cultivar. Although Loureiro mostly showed no statistical differences in assessed parameters across tissues and dates, variations were found in pulp and skin chlorophyll content and puncture force. This tomography-like approach based on tissue maturation can help viticulturists to access instant data on grape maturation, supporting informed decision-making and promoting more sustainable agricultural practices.

Why it matches plant phenotyping methodsブドウ組織の成熟に関するスペクトルを再構成し、糖度・硬度・クロロフィル・アントシアニンなどの植物器官形質を予測する新規センシング／計算手法を開発・検証しており、フェノタイピング手法が中心である。

abstractThis paper introduces a tomography-like method for assessing grape maturation.

Laser Ablation-Capillary Absorption Spectroscopy: A novel approach for high throughput and increased spatial resolution measurements of δ13C in plant-soil systems →

Spatial and temporal heterogeneity of nutrient exchange within the rhizosphere is a topic of increasing interest, although challenging to study due to limits in existing analytical capabilities. Here, we developed and demonstrated a new approach applying laser ablation sample introduction to capillary absorption spectroscopy (LA-CAS) to characterize carbon isotopic distribution within plant tissues, rhizosphere, and soil. We exposed switchgrass plants to ¹³CO₂ to allow tracing of ¹³C-labeled photosynthates within plant biomass and into the associated soil. The LA-CAS methods we describe leverage continuous measurements of a sample stream derived from laser ablation line scans (10–25 μm in width) over a sample surface which enables the user to produce an isotope map with a) higher data density or b) over larger spatial areas versus previously existing techniques. This versatility of LA-CAS is assessed through testing of a range of laser parameters (spot size, scan rates) on various materials (soil, plant biomass/tissues, and rhizosphere). We demonstrate the ability of LA-CAS to provide near instantaneous δ¹³C measurements over isotopically distinct surfaces to enable high spatially resolved mapping of ¹³C-labeled material within the rhizosphere. Applying LA-CAS analysis to plant biomass, we observed higher δ¹³C values concentrated within phloem structures, consistent with localized photosynthate transport. When mapping across the rhizosphere, ¹³C-enriched soil was typically present within 5–10 μm of root boundaries with a steep spatial increase in δ¹³C when the scan approached the middle of the root. As with all LA approaches, care is required to ensure accurate results as phenomena linked to ablation, combustion, and isotopic measurement can impart artifacts if not carefully controlled. Still, taken as a whole, our demonstrations highlight the increased sample throughput, improved data density, and enhanced δ¹³C capability of LA-CAS versus other LA techniques and emphasize the role this method can play in future plant and rhizosphere related studies.

Why it matches plant phenotyping methods植物組織・根圏におけるδ13Cの空間分布を高スループットかつ高解像度で測定するLA-CAS法を開発・評価しており、植物状態の取得手法が研究の中心である。

abstractHere, we developed and demonstrated a new approach applying laser ablation sample introduction to capillary absorption spectroscopy (LA-CAS) to characterize carbon isotopic distribution within plant tissues, rhizosphere, and soil.

Multi-Sensor Remote Sensing to Estimate Biophysical Variables of Green-Onion Crop (Allium cepa L.) under Different Sources of Magnesium in Ismailia, Egypt →

Foliar feeding has been confirmed to be the fastest way of dealing with nutrient deficiencies and increasing the yield and quality of crop products. The synthesis of chlorophyll and photosynthesis are directly related to magnesium (Mg), which operates in the improvement of plant tissues and enhances the appearance of plants. This study aimed to analyze the correlation between two biophysical variables, including the leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), and seven spectral vegetation indices. The spectral indices under investigation were Atmospherically Resistant Vegetation Index (ARVI), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Disease–Water Stress Index (DSWI), Modified Chlorophyll Absorption Ratio Index (MCARI), the Red-Edge Inflection Point Index (REIP), and Pigment-Specific Simple Ratio (PSSRa). These indices were derived from Sentinel-2 data to investigate the impact of applying foliar applications of Mg from various sources in the production of green-onion crops. The biophysical variables were derived using field measurements and Sentinel-2 data under the effects of different sources of Mg foliar sprays. The correlation coefficient between field-measured LAI and remotely sensed, calculated LAI was 0.72 in two seasons. Concerning FAPAR, it was found that the correlation between remotely sensed calculated FAPAR and field-measured FAPAR was 0.66 in the first season and 0.89 in the second season. The magnesium oxide nanoparticle (nMgO) treatments resulted in significantly higher yields than the different treatments of foliar applications. The LAI and FAPAR variables showed a positive correlation with yield in the first season (October) and in the second season (March). Yield in treatment by nMgO varied significantly from that in the other treatments, ranging from 69-ton ha−1 in the first season to 74.9-ton ha−1 in the second season. Linear regression between LAI and PSSRa showed the highest correlation coefficient (0.90) compared with other vegetation indices in the first season. In the same season, the highest correlation coefficient (0.94) was found between FAPAR and PSSRa. In the second season, the highest accuracy to the estimate LAI was found in the correlation between MCARI and PSSRa, with correlation coefficients of 0.9 and 0.91, respectively. In the second season, the highest accuracy to the estimate FAPAR was found with the correlation between PSSRa, ARVI, and NDVI, with correlation coefficients 0.97 and 0.96, respectively. The highest correlation coefficients between vegetation indices and yield were found with ARVI and NDVI in the first season, and only with NDVI in the second season.

Why it matches plant phenotyping methodsSentinel-2と圃場測定を用いてLAI・FAPARを推定し、実測値との相関で検証しており、植物形質取得法が研究の中心的要素である。

abstractThe biophysical variables were derived using field measurements and Sentinel-2 data under the effects of different sources of Mg foliar sprays.

Highly Selective and Rapid "Turn-On" Fluorogenic Chemosensor for Detection of Salicylic Acid in Plants and Food Samples. →

Salicylic acid (SA) is one of the chemical molecules, involved in plant growth and immunity, thereby contributing to the control of pests and pathogens, and even applied in fruit and vegetable preservation. However, only a few tools have ever been designed or executed to understand the physiological processes induced by SA or its function in plant immunity and residue detection in food. Hence, three Rh6G-based fluorogenic chemosensors were synthesized to detect phytohormone SA based on the "OFF-ON" mechanism. The probes showed high selectivity, ultrafast response time (<60 s), and nanomolar detection limit for SA. Moreover, the probe possessed outstanding profiling that can be successfully used for SA imaging of callus and plants. Furthermore, the fluorescence pattern indicated that SA could occur in the distal transport in plants. These remarkable results contribute to improving our understanding of the multiple physiological and pathological processes involved in SA for plant disease diagnosis and for the development of immune activators. In addition, SA detection in some agricultural products used probes to extend the practical application because its use is prohibited in some countries and is harmful to SA-sensitized persons. Interestingly, the as-obtained test paper displayed that SA could be imaged by ultraviolet (UV) and was directly visible to the naked eye. Given the above outcomes, these probes could be used to monitor SA in vitro and in vivo, including, but not limited to, plant biology, food residue detection, and sewage detection.

Why it matches plant phenotyping methods植物内のサリチル酸という生理状態を可視化・検出する蛍光センサーを開発し、植物およびカルスでのイメージングに適用しているため、植物フェノタイピング手法が中心です。

abstractthree Rh6G-based fluorogenic chemosensors were synthesized to detect phytohormone SA based on the "OFF-ON" mechanism.

Tracing the opposing assimilate and nutrient flows in live conifer needles. →

The vasculature along conifer needles is fundamentally different from that in angiosperm leaves as it contains a unique transfusion tissue inside the bundle sheath. In this study, we used specific tracers to identify the pathway of photoassimilates from mesophyll to phloem, and the opposing pathway of nutrients from xylem to mesophyll. For symplasmic transport we applied esculin to the tip of attached pine needles and followed its movement down the phloem. For apoplasmic transport we let detached needles take up a membrane-impermeable contrast agent and used micro-X-ray computed tomography to map critical water exchange interfaces and domain borders. Microscopy and segmentation of the X-ray data enabled us to render and quantify the functional 3D structure of the water-filled apoplasm and the complementary symplasmic domain. The transfusion tracheid system formed a sponge-like apoplasmic domain that was blocked at the bundle sheath. Transfusion parenchyma cell chains bridged this domain as tortuous symplasmic pathways with strong local anisotropy which, as evidenced by the accumulation of esculin, pointed to the phloem flanks as the preferred phloem-loading path. Simple estimates supported a pivotal role of the bundle sheath, showing that a bidirectional movement of nutrient ions and assimilates is feasible and emphasizing the role of the bundle sheath in nutrient and assimilate exchange.

Why it matches plant phenotyping methodsマイクロX線CT、画像セグメンテーション、3D構造の可視化・定量が、トレーサー輸送と針葉の機能構造解析の中心的手法であるため。

abstractused micro-X-ray computed tomography to map critical water exchange interfaces and domain borders

Growth couples temporal and spatial fluctuations of tissue properties during morphogenesis →

Living tissues display fluctuations – random spatial and temporal variations of tissue properties around their reference values – at multiple scales. It is believed that such fluctuations may enable tissues to sense their state or their size. Recent theoretical studies developed specific models of fluctuations in growing tissues and predicted that fluctuations of growth show long-range correlations. Here we elaborated upon these predictions and we tested them using experimental data. We first introduced a minimal model for the fluctuations of any quantity that has some level of temporal persistence or memory, such as concentration of a molecule, local growth rate, or mechanical property. We found that long-range correlations are generic, applying to any such quantity, and that growth couples temporal and spatial fluctuations, through a mechanism that we call ‘fluctuation stretching’ — growth enlarges the lengthscale of variation of this quantity. We then analysed growth data from sepals of the model plant Arabidopsis and we quantified spatial and temporal fluctuations of cell growth using the previously developed Cellular Fourier Transform. Growth appears to have long-range correlations. We compared different genotypes and growth conditions: mutants with lower or higher response to mechanical stress have lower temporal correlations and longer-range spatial correlations than wild-type plants. Finally, we used theoretical predictions to merge experimental data from all conditions and developmental stages into an unifying curve, validating the notion that temporal and spatial fluctuations are coupled by growth. Altogether, our work reveals kinematic constraints on spatiotemporal fluctuations that have an impact on the robustness of morphogenesis. Significance Statement How do organs and organisms grow and achieve robust shapes in the face of subcellular and cellular variability? In order to address this outstanding mystery, we investigated the variability of growth at multiple scales and we analysed experimental data from growing plant tissues. Our results support the prediction that tissue expansion couples temporal memory of growth with spatial variability of growth. Our work reveals a constraint on the spatial and temporal variability of growth that may impact the robustness of morphogenesis.

Why it matches plant phenotyping methodsArabidopsis萼片の細胞成長をCellular Fourier Transformで定量し、時空間変動を解析・理論予測と比較して検証しており、植物成長表現型の抽出・解析が研究の中心です。

abstractFinally, we used theoretical predictions to merge experimental data from all conditions and developmental stages into an unifying curve, validating the notion that temporal and spatial fluctuations are coupled by growth.

Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection →

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model's resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications.

Why it matches plant phenotyping methods植物病害の状態をハイパースペクトル画像とオミクスデータから推定するEG-CNNモデルを開発・評価しており、病害表現型の取得・抽出手法が中心である。

abstractWe propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study.

The optical method based on gas injection overestimates leaf vulnerability to xylem embolism in three woody species. →

Plant hydraulic traits related to leaf drought tolerance, like the water potential at turgor loss point (TLP) and the water potential inducing 50% loss of hydraulic conductance (P50), are extremely useful to predict the potential impacts of drought on plants. While novel techniques have allowed the inclusion of TLP in studies targeting a large group of species, fast and reliable protocols to measure leaf P50 are still lacking. Recently, the optical method coupled with the gas injection (GI) technique has been proposed as a possibility to speed up the P50 estimation. Here, we present a comparison of leaf optical vulnerability curves (OVcs) measured in three woody species, namely Acer campestre (Ac), Ostrya carpinifolia (Oc) and Populus nigra (Pn), based on bench dehydration (BD) or GI of detached branches. For Pn, we also compared optical data with direct micro-computed tomography (micro-CT) imaging in both intact saplings and cut shoots subjected to BD. Based on the BD procedure, Ac, Oc and Pn had P50 values of -2.87, -2.47 and -2.11 MPa, respectively, while the GI procedure overestimated the leaf vulnerability (-2.68, -2.04 and -1.54 MPa for Ac, Oc and Pn, respectively). The overestimation was higher for Oc and Pn than for Ac, likely reflecting the species-specific vessel lengths. According to micro-CT observations performed on Pn, the leaf midrib showed none or very few embolized conduits at -1.2 MPa, consistent with the OVcs obtained with the BD procedure but at odds with that derived on the basis of GI. Overall, our data suggest that coupling the optical method with GI might not be a reliable technique to quantify leaf hydraulic vulnerability since it could be affected by the 'open-vessel' artifact. Accurate detection of xylem embolism in the leaf vein network should be based on BD, preferably of intact up-rooted plants.

Why it matches plant phenotyping methods葉の木部エンボリズム脆弱性を測定する光学法・ガス注入法を比較し、マイクロCTで検証しており、植物生理形質の取得法の技術評価が中心である。

abstractfast and reliable protocols to measure leaf P50 are still lacking.

The shape and volume of air, kernels, and cracks, in a nutshell →

Abstract Walnuts are the second most produced and consumed tree nut, with over 2.6 million metric tons produced in the 2022-23 harvest cycle alone. The United States is the second largest producer, accounting for 25% of the total global supply. Nonetheless, producers face an ever-growing demand in a more uncertain climate landscape, which requires effective and efficient walnut selection and breeding of new cultivars with increased kernel content and easy-to-open shells. Past and current efforts select for these traits using hand-held calipers and eye-based evaluations. Yet there is plenty of morphology that meets the eye but goes unmeasured, such as the volume of inner air or the convexity of the kernel. Here, we study the shape of walnut fruits based on X-ray CT (Computed Tomography) 3D reconstructions. We compute 49 different morphological phenotypes for 1264 individuals comprising 149 accessions. These phenotypes are complemented by traits of breeding interest such as ease of kernel removal and kernel weight. Through allometric relationships —relative growth of one tissue to another—, we identify possible biophysical constraints at play during development. We explore multiple correlations between all morphological and commercial traits, and identify which morphological traits can explain the most variability of commercial traits. We show that using only volume and thickness-based traits, especially inner air content, we can successfully encode several of the commercial traits. Core Ideas X-ray Computed Tomography (CT) imaging is used to compute a broad array of morpho-logical phenotypes in walnuts. These morphological traits suggest biophysical constraints at play during walnut development. Relative inner air, shell, and packing tissue volumes are significantly correlated to the rest of shape phenotypes. These volumes produce the best prediction models for traits of commercial interest such as shell strength. Inexpensive phenotyping platforms that focus solely on volume measurement would enable better walnut breeding.

Why it matches plant phenotyping methodsクルミ果実を対象にX線CT 3D画像から49種類の形態表現型を抽出する手法を中心に扱い、育種形質への応用・予測も評価しているため。

abstractHere, we study the shape of walnut fruits based on X-ray CT (Computed Tomography) 3D reconstructions. We compute 49 different morphological phenotypes for 1264 individuals comprising 149 accessions.

Predicting photosynthetic pathway from anatomy using machine learning →

- Plants with Crassulacean acid metabolism (CAM) have long been associated with a specialized anatomy, including succulence and thick photosynthetic tissues. Firm, quantitative boundaries between non-CAM and CAM plants have yet to be established - if they indeed exist. - Using novel computer vision software to measure anatomy, we combined new measurements with published data across flowering plants. We then used machine learning and phylogenetic comparative methods to investigate relationships between CAM and anatomy. - We found significant differences in photosynthetic tissue anatomy between plants with differing CAM phenotypes. Machine learning based classification was over 95% accurate in differentiating CAM from non-CAM anatomy, and had over 70% recall of distinct CAM phenotypes. Phylogenetic least squares regression and threshold analyses revealed that CAM evolution was significantly correlated with increased mesophyll cell size, thicker leaves, and decreased intercellular airspace. - Our findings suggest that machine learning may be used to aid the discovery of new CAM species and that the evolutionary trajectory from non-CAM to strong, obligate CAM requires continual anatomical specialization.

Why it matches plant phenotyping methods植物解剖形態を測定する新規コンピュータビジョンソフトウェアと、CAM表現型を分類する機械学習を中心的に開発・適用しているため、植物フェノタイピング手法として採択。

abstractUsing novel computer vision software to measure anatomy, we combined new measurements with published data across flowering plants.

Detached Maize Sheaths for Live-Cell Imaging of Infection by Fungal Foliar Maize Pathogens. →

We have optimized a protocol to inoculate maize leaf sheaths with hemibiotrophic and necrotrophic foliar pathogenic fungi. The method is modified from one originally applied to rice leaf sheaths and allows direct microscopic observation of fungal growth and development in living plant cells. Leaf sheaths collected from maize seedlings with two fully emerged leaf collars are inoculated with 20 µL drops of 5 x 10 5 spores/mL fungal spore suspensions and incubated in humidity chambers at 23 °C under continuous fluorescent light. After 24-72 h, excess tissue is removed with a razor blade to leave a single layer of epidermal cells, an optically clear sample that can be imaged directly without the necessity for chemical fixation or clearing. Plant and fungal cells remain alive for the duration of the experiment and interactions can be visualized in real-time. Sheaths can be stained or subjected to plasmolysis to study the developmental cytology and viability of host and pathogen cells during infection and colonization. Fungal strains transformed to express fluorescent proteins can be inoculated or co-inoculated on the sheaths for increased resolution and to facilitate the evaluation of competitive or synergistic interactions. Fungal strains expressing fluorescent fusion proteins can be used to track and quantify the production and targeting of these individual proteins in planta. Inoculated sheath tissues can be extracted to characterize nucleic acids, proteins, or metabolites. The use of these sheath assays has greatly advanced the detailed studies of the mechanisms of fungal pathogenicity in maize and also of fungal protein effectors and secondary metabolites contributing to pathogenicity.

Why it matches plant phenotyping methodsトウモロコシ葉鞘を用いた感染過程の生細胞イメージング法を最適化し、植物細胞内での病原菌の成長・発達や相互作用を直接観察・定量する技術が中心である。

abstractWe have optimized a protocol to inoculate maize leaf sheaths with hemibiotrophic and necrotrophic foliar pathogenic fungi.

A novel workflow for unbiased quantification of autophagosomes in 3D in Arabidopsis thaliana roots →

ABSTRACT Macroautophagy is frequently quantified by live imaging of autophagosomes decorated with a marker of fluorescently tagged ATG8 protein (FT-ATG8) in Arabidopsis thaliana . This requires generation of suitable plant material by time-consuming crossing or transformation with FT-ATG8 marker. Autophagosome quantification by image analysis often relies on their counting in individual focal planes. This approach is prone to deliver biased results due to inappropriate sampling of the regions of interest in the Z-direction, as the actual 3D distribution of autophagosomes is usually not taken into account. To overcome such drawbacks, we have developed and tested a workflow consisting of immunofluorescence microscopy of autophagosomes labelled with anti-ATG8 antibody followed by stereological image analysis employing the optical disector and the Cavalieri principle. Our immunolabelling protocol specifically recognized autophagosomes in epidermal cells of A. thaliana root. Higher numbers of immunolabelled autophagosomes were observed when compared with those recognized with FT- At ATG8e marker, suggesting that single At ATG8 isoform markers cannot detect all autophagosomes in a cell. Therefore, immunolabelling provides more precise information as the anti-ATG8 antibody recognizes virtually all At ATG8 isoforms. The number of autophagosomes per tissue volume determined by stereological methods correlated with the intensity of autophagy induction treatment. Compared to autophagosome quantifications in maximum intensity projections, stereological methods detected autophagosomes present in a given volume with higher accuracy. Our novel application of immunolabelling combined with stereological methods constitutes a powerful toolbox for unbiased and reproducible quantification of autophagosomes and offers a convenient alternative to the standard of live imaging using FP-ATG8 marker.

Why it matches plant phenotyping methods植物のオートファゴソーム状態を対象に、免疫蛍光イメージングと立体解析を組み合わせた定量ワークフローを開発・検証しており、表現型取得法が研究の中心である。

abstractwe have developed and tested a workflow consisting of immunofluorescence microscopy of autophagosomes labelled with anti-ATG8 antibody followed by stereological image analysis employing the optical disector and the Cavalieri principle.

High Throughput Tomography (HiTT) on EMBL Beamline P14 on PETRA III →

Here we present High-Throughput Tomography (HiTT), a fast and versatile phase-contrast imaging platform for life-science samples on the EMBL beamline P14 at DESY in Hamburg, Germany. We use a high photon flux undulator beamline to perform tomographic phase contrast acquisition in about two minutes which is linked to an automated data processing pipeline that delivers a 3D reconstructed data set less than a minute and a half after the completion of the X-ray scan. Combining this workflow with a sophisticated robotic sample changer enables the streamlined collection and reconstruction of X-ray imaging data from potentially hundreds of samples during a beamtime shift. HiTT permits optimal data collection for many different samples and makes possible the imaging of large sample cohorts thus allowing population studies to be attempted. We demonstrate the successful application of HiTT on various soft tissue samples in both liquid (hydrated and also dehydrated) and paraffin embedded preparations. Furthermore, we demonstrate the feasibility of HiTT to be used as a targeting tool for volume electron microscopy (vEM), as well as using HiTT to study plant morphology. We also show how the high throughput nature of the work has allowed large numbers of “identical” samples to be imaged to enable statistically relevant sample volumes to be studied. Synopsis We present HiTT – high throughput tomography – a propagation based phase contrast X-ray imaging technique which can visualise 1 mm 3 biological samples of various types at high resolution. The 3D reconstructions of the imaged volumes are calculated automatically once data collection is complete. The entire process from pressing start on data collection to viewing the final data takes less than 3 minutes. This speed in combination with the use of the automated sample changer to exchange the samples truly enables high throughput X-ray imaging for the first time.

Why it matches plant phenotyping methods高速・自動3D X線トモグラフィー基盤の開発と、植物形態の画像化への適用が中心であり、植物表現型計測手法として適格です。

abstractHere we present High-Throughput Tomography (HiTT), a fast and versatile phase-contrast imaging platform for life-science samples on the EMBL beamline P14 at DESY in Hamburg, Germany.

In situ imaging of signaling molecule carbon monoxide in plants with a fluorescent probe. →

Carbon monoxide (CO) is a recently discovered gasotransmitter. In animals, it has been found that endogenously produced CO participates in the regulation of various metabolic processes. Recent research has indicated that CO, acting as a signaling molecule, plays a crucial regulatory role in plant development and their response to abiotic stress. In this work, we developed a fluorescent probe, named COP (carbonic oxide Probe), for the in situ imaging of CO in Arabidopsis thaliana plant tissues. The probe was designed by combining malononitrile-naphthalene as the fluorophore and a typical palladium-mediated reaction mechanism. When reacted with the released CO, COP showed an obvious fluorescence enhancement at 575 nm, which could be observed in naked-eye conditions. With a linear range of 0-10 μM, the limit of detection of COP was determined as 0.38 μM. The detection system based on COP indicated several advantages including relatively rapid response within 20 min, steadiness in a wide pH range of 5.0-10.0, high selectivity, and applicative anti-interference. Moreover, with a penetration depth of 30 μm, COP enabled 3D imaging of CO dynamics in plant samples, whether it was caused by agent release, heavy metal stress, or inner oxidation. This work provides a fluorescent probe for monitoring CO levels in plant samples, and it expands the application field of CO-detection technology, assisting researchers in understanding the dynamic changes in plant physiological processes, making it an important tool for studying plant physiology and biological processes.

Why it matches plant phenotyping methods植物組織内のCO動態を可視化・定量する蛍光プローブを開発し、植物サンプルでの3Dイメージング性能も評価しており、表現型・生理状態の取得法が中心である。

abstractIn this work, we developed a fluorescent probe, named COP (carbonic oxide Probe), for the in situ imaging of CO in Arabidopsis thaliana plant tissues.

High-energy interference-free K-lines synchrotron X-ray fluorescence microscopy of rare earth elements in hyperaccumulator plants. →

Synchrotron-based micro-X-ray fluorescence analysis (µXRF) is a nondestructive and highly sensitive technique. However, element mapping of rare earth elements (REEs) under standard conditions requires care, since energy-dispersive detectors are not able to differentiate accurately between REEs L-shell X-ray emission lines overlapping with K-shell X-ray emission lines of common transition elements of high concentrations. We aim to test REE element mapping with high-energy interference-free excitation of the REE K-lines on hyperaccumulator plant tissues and compare with measurements with REE L-shell excitation at the microprobe experiment of beamline P06 (PETRA III, DESY). A combination of compound refractive lens optics (CRLs) was used to obtain a micrometer-sized focused incident beam with an energy of 44 keV and an extra-thick silicon drift detector optimized for high-energy X-ray detection to detect the K-lines of yttrium (Y), lanthanum (La), cerium (Ce), praseodymium (Pr), and neodymium (Nd) without any interferences due to line overlaps. High-energy excitation from La to Nd in the hyperaccumulator organs was successful but compared to L-line excitation less efficient and therefore slow (∼10-fold slower than similar maps at lower incident energy) due to lower flux and detection efficiency. However, REE K-lines do not suffer significantly from self-absorption, which makes XRF tomography of millimeter-sized frozen-hydrated plant samples possible. The K-line excitation of REEs at the P06 CRL setup has scope for application in samples that are particularly prone to REE interfering elements, such as soil samples with high concomitant Ti, Cr, Fe, Mn, and Ni concentrations.

Why it matches plant phenotyping methods植物組織中の希土類元素分布を測定するµXRF法の技術開発・比較検証が中心であり、植物の元素蓄積状態を直接マッピングする方法論研究である。

abstractWe aim to test REE element mapping with high-energy interference-free excitation of the REE K-lines on hyperaccumulator plant tissues and compare with measurements with REE L-shell excitation

Green Index: a widely accessible method to quantify greenness of photosynthetic organisms →

Abstract Plant phenotyping involves the quantitative determination of complex plant traits using image analysis. One important parameter is how green plant tissues appear to the observer, which is indicative of their health and developmental stage. Various formulas have been developed to quantify this by calculating leaf greenness scores. We have developed a revised formula called “Green Index” (GI) devised out of the need to quantitatively assess how the apparent greenness of seedlings changes during de-etiolation. The GI calculation is simple, uses widely available RGB values of pixels in images as input, and does not require commercial software platforms or advanced computational skills. In this study we describe the conception of the GI formula, compare it with other widely used greenness formulas, and test its wider application in plant phenotyping using the open source free software platform RawTherapee. We demonstrate the utility of the GI in addressing common issues encountered in assessing plant biology experiments, underscoring its potential as a reliable and accessible tool. Finally, we explore the correlation between GI and chlorophyll content, assess its reliance on different types of photography, and summarizes the key steps for its effective utilization.

Why it matches plant phenotyping methods植物の緑色を画像RGB値から定量化するGreen Indexを開発し、既存式との比較、適用性・撮影条件・クロロフィルとの相関を検証しており、植物表現型取得法が研究の中心です。

abstractWe have developed a revised formula called “Green Index” (GI)

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue →

The accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease-resistant crop varieties. In this study, we report an accelerated phenotyping platform for the continuous-time, rapid and quantitative assessment of HR: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating the detection of microscopic levels of cell death. We validated PASTEL by transiently expressing the effector protein AVRblb2 in transgenic lines of the model plant Nicotiana benthamiana (expressing the corresponding resistance protein Rpi-blb2) to reliably induce HR. We were able to detect cell death at microscopic intensities, where leaf tissue appeared healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously (sub-seconds to minutes). Using this data, we developed a supervised machine learning models for classification of HR. We were able to classify input data (inclusive of our entire tested concentration range) as HR-positive or negative with 84.1% mean accuracy (F 1 score = 0.75) at 1 hour and with 87.8% mean accuracy (F 1 score = 0.81) at 22 hours. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

Why it matches plant phenotyping methods植物組織の過敏感反応による細胞死を連続的・定量的に測定する分光計測プラットフォームと機械学習分類モデルを開発・検証しており、植物表現型取得が研究の中心である。

abstractwe report an accelerated phenotyping platform for the continuous-time, rapid and quantitative assessment of HR: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL).

Three-dimensional visualization of plant tissues and organs by X-ray micro–computed tomography →

Studies visualizing plant tissues and organs in three-dimension (3D) using micro-computed tomography (CT) published since approximately 2015 are reviewed. In this period, the number of publications in the field of plant sciences dealing with micro-CT has increased along with the development of high-performance lab-based micro-CT systems as well as the continuous development of cutting-edge technologies at synchrotron radiation facilities. The widespread use of commercially available lab-based micro-CT systems enabling phase-contrast imaging technique, which is suitable for the visualization of biological specimens composed of light elements, appears to have facilitated these studies. Unique features of the plant body, which are particularly utilized for the imaging of plant organs and tissues by micro-CT, are having functional air spaces and specialized cell walls, such as lignified ones. In this review, we briefly describe the basis of micro-CT technology first and then get down into details of its application in 3D visualization in plant sciences, which are categorized as follows: imaging of various organs, caryopses, seeds, other organs (reproductive organs, leaves, stems and petioles), various tissues (leaf venations, xylems, air-filled tissues, cell boundaries, cell walls), embolisms and root systems, hoping that wide users of microscopes and other imaging technologies will be interested also in micro-CT and obtain some hints for a deeper understanding of the structure of plant tissues and organs in 3D. Majority of the current morphological studies using micro-CT still appear to be at a qualitative level. Development of methodology for accurate 3D segmentation is needed for the transition of the studies from a qualitative level to a quantitative level in the future.

Why it matches plant phenotyping methods植物組織・器官の3D形態を取得するマイクロCT技術を中心に扱い、定量化に向けたセグメンテーション手法の必要性も論じる方法レビューである。

titleThree-dimensional visualization of plant tissues and organs by X-ray micro–computed tomography

Localized measurements of water potential reveal large loss of conductance in living tissues of maize leaves →

The water status of the living tissue in leaves between the xylem and stomata (outside xylem zone - OXZ) play a critical role for plant function and global mass and energy balance but has remained largely inaccessible. We resolve the local water relations of OXZ tissue using a nanogel reporter of water potential ({psi}), AquaDust, that enables an in-situ, non-destructive measurement of both{psi} of xylem and highly localized{psi} at the terminus of transpiration in the OXZ. Working in maize, these localized measurements reveal gradients in the OXZ that are several fold larger than those based on conventional methods, and values of{psi} in the mesophyll apoplast well below the macroscopic turgor loss potential. We find a strong loss of hydraulic conductance in both the bundle sheath and the mesophyll with decreasing xylem potential but not with evaporative demand. Our measurements suggest an active role played by the OXZ in regulating the transpiration path and our methods provide novel means to study this phenomenon.

Why it matches plant phenotyping methodsAquaDustを用いた葉内の局所的な水ポテンシャル測定法が研究の中心であり、植物の水状態・水理特性を定量化している。

abstractWe resolve the local water relations of OXZ tissue using a nanogel reporter of water potential ({psi}), AquaDust, that enables an in-situ, non-destructive measurement of both{psi} of xylem and highly localized{psi} at the terminus of transpiration in the OXZ.

Microscopical Analysis of Autofluorescence as a Complementary and Useful Method to Assess Differences in Anatomy and Structural Distribution Underlying Evolutive Variation in Loss of Seed Dispersal in Common Bean. →

The common bean has received attention as a model plant for legume studies, but little information is available about the morphology of its pods and the relation of this morphology to the loss of seed dispersal and/or the pod string, which are key agronomic traits of legume domestication. Dehiscence is related to the pod morphology and anatomy of pod tissues because of the weakening of the dorsal and ventral dehiscence zones and the tensions of the pod walls. These tensions are produced by the differential mechanical properties of lignified and non-lignified tissues and changes in turgor associated with fruit maturation. In this research, we histologically studied the dehiscence zone of the ventral and dorsal sutures of the pod in two contrasting genotypes for the dehiscence and string, by comparing different histochemical methods with autofluorescence. We found that the secondary cell wall modifications of the ventral suture of the pod were clearly different between the dehiscence-susceptible and stringy PHA1037 and the dehiscence-resistant and stringless PHA0595 genotypes. The susceptible genotype had cells of bundle caps arranged in a more easily breakable bowtie knot shape. The resistant genotype had a larger vascular bundle area and larger fibre cap cells (FCCs), and due to their thickness, the external valve margin cells were significantly stronger than those from PHA1037. Our findings suggest that the FCC area, and the cell arrangement in the bundle cap, might be partial structures involved in the pod dehiscence of the common bean. The autofluorescence pattern at the ventral suture allowed us to quickly identify the dehiscent phenotype and gain a better understanding of cell wall tissue modifications that took place along the bean's evolution, which had an impact on crop improvement. We report a simple autofluorescence protocol to reliably identify secondary cell wall organization and its relationship to the dehiscence and string in the common bean.

Why it matches plant phenotyping methods豆莢の裂開性・string形質を対象に、自己蛍光による組織構造の迅速判定プロトコルを提示しており、表現型取得法が研究の中心である。

abstractThe autofluorescence pattern at the ventral suture allowed us to quickly identify the dehiscent phenotype

A CRISPR-induced DNA break can trigger crossover, chromosomal loss and chromothripsis-like rearrangements →

The fate of DNA double-strand breaks (DSBs) generated by the Cas9 nuclease has been thoroughly studied. Repair via non-homologous end-joining (NHEJ) or homologous recombination (HR) is the common outcome. However, little is known about unrepaired DSBs and the type of damage they can trigger in plants. In this work, we designed a new assay that detects loss of heterozygosity (LOH) in somatic cells, enabling the study of a broad range of DSB-induced genomic events. The system relies on a mapped phenotypic marker which produces a light purple color (Betalain pigment) in all plant tissues. Plants with sectors lacking the Betalain marker upon DSB induction between the marker and the centromere were tested for LOH events. Using this assay we detected a flower with a twin yellow and dark purple sector, corresponding to a germinally transmitted somatic crossover event. We also identified instances of small deletions of genomic regions spanning the T-DNA and whole chromosome loss. In addition, we show that major chromosomal rearrangements including loss of large fragments, inversions, and translocations were clearly associated with the CRISPR-induced DSB. Detailed characterization of complex rearrangements by whole genome sequencing, molecular, and cytological analyses, supports a model in which breakage-fusion-bridge cycle followed by chromothripsis-like rearrangements had been induced. Our LOH assay provides a new tool for precise breeding via targeted crossover detection. It also uncovers CRISPR mediated chromothripsis-lke events that had not been previously identified in plants.

Why it matches plant phenotyping methods植物組織の色素表現型を利用して体細胞LOHや染色体イベントを検出する新規アッセイを開発しており、表現型に基づく測定法が研究の中心である。

abstractIn this work, we designed a new assay that detects loss of heterozygosity (LOH) in somatic cells, enabling the study of a broad range of DSB-induced genomic events.

New insight into the genetic basis of oil content based on noninvasive three-dimensional phenotyping and tissue-specific transcriptome in Brassica napus →

Abstract Background Increasing seed oil content is the most important breeding goal in Brassica napus , and phenotyping is crucial to dissect its genetic basis in crops. To date, QTL mapping for oil content has been based on whole seeds, and the lipid distribution is far from uniform in different tissues of seeds in B. napus . In this case, the phenotype based on whole seeds was unable to sufficiently reveal the complex genetic characteristics of seed oil content. Results Here, the three-dimensional (3D) distribution of lipid was determined for B. napus seeds by magnetic resonance imaging (MRI) and 3D quantitative analysis, and ten novel oil content-related traits were obtained by subdividing the seeds. Based on a high-density genetic linkage map, 35 QTLs were identified for 4 tissues, the outer cotyledon (OC), inner cotyledon (IC), radicle (R) and seed coat (SC), which explained up to 13.76% of the phenotypic variation. Notably, 14 tissue-specific QTLs were reported for the first time, 7 of which were novel. Moreover, haplotype analysis showed that the favorable alleles for different seed tissues exhibited cumulative effects on oil content. Furthermore, tissue-specific transcriptomes revealed that more active energy and pyruvate metabolism influenced carbon flow in the IC, OC and R than in the SC at the early and middle seed development stages, thus affecting the distribution difference in oil content. Combining tissue-specific QTL mapping and transcriptomics, 86 important candidate genes associated with lipid metabolism were identified that underlie 19 unique QTLs, including the fatty acid synthesis rate-limiting enzyme-related gene CAC2 , in the QTLs for OC and IC. Conclusions The present study provides further insight into the genetic basis of seed oil content at the tissue-specific level.

Why it matches plant phenotyping methodsMRIと3D定量解析を用いて種子組織別の脂質分布から複数の油含量形質を抽出しており、植物フェノタイピング手法の適用が研究の中心的要素です。

titlenoninvasive three-dimensional phenotyping

How to sample a seizure plant: the role of the visualization spatial distribution analysis of Lophophora williamsii as an example →

Natural compounds in plants are often unevenly distributed, and determining the best sampling locations to obtain the most representative results is technically challenging. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide the basis for formulating sampling guideline. For a succulent plant sample, ensuring the authenticity and in situ nature of the spatial distribution analysis results during MSI analysis also needs to be thoroughly considered. In this study, we developed a well-established and reliable MALDI-MSI method based on preservation methods, slice conditions, auxiliary matrices, and MALDI parameters to detect and visualize the spatial distribution of mescaline in situ in Lophophora williamsii . The MALDI-MSI results were validated using liquid chromatography-tandem mass spectrometry. Low-temperature storage at -80°C and drying of "bookmarks" were the appropriate storage methods for succulent plant samples and their flower samples, and cutting into 40 μm thick sections at -20°C using gelatin as the embedding medium is the appropriate sectioning method. The use of DCTB (trans-2-[3-(4-tert-butylphenyl)-2-methyl-2-propenylidene]malononitrile) as an auxiliary matrix and a laser intensity of 45 are favourable MALDI parameter conditions for mescaline analysis. The region of interest semi-quantitative analysis revealed that mescaline is concentrated in the epidermal tissues of L. williamsii as well as in the meristematic tissues of the crown. The study findings not only help to provide a basis for determining the best sampling locations for mescaline in L. williamsii , but they also provide a reference for the optimization of storage and preparation conditions for raw plant organs before MALDI detection. Key points An accurate in situ MSI method for fresh water-rich succulent plants was obtained based on multi-parameter comparative experiments.Spatial imaging analysis of mescaline in Lophophora williamsii was performed using the above method.Based on the above results and previous results, a sampling proposal for forensic medicine practice is tentatively proposed.

Why it matches plant phenotyping methods植物組織内の化合物空間分布を可視化・半定量するMALDI-MSI法の開発とLC-MS/MSによる検証が研究の中心であり、植物器官の状態・分布を測定する方法論的貢献に該当する。

abstractwe developed a well-established and reliable MALDI-MSI method based on preservation methods, slice conditions, auxiliary matrices, and MALDI parameters to detect and visualize the spatial distribution of mescaline in situ in Lophophora williamsii

In-section Click-iT detection and super-resolution CLEM: Shedding light on nucleolar ultrastructure and S-phase progression in plants. →

Correlative light and electron microscopy (CLEM) is an essential tool that allows for localisation of a particular target molecule(s) and their spatial correlation with the ultrastructural map of subcellular features at the nanometer scale. Adoption of these advanced imaging methods has been limited in plant biology, due to challenges with plant tissue permeability, fluorescence labelling efficiency, indexing of features of interest throughout the complex 3D volume and their re-localization on micrographs of ultrathin cross-sections. Here, we demonstrate an imaging approach based on tissue processing and embedding into methacrylate resin followed by imaging of serial sections by both, single-molecule localization microscopy and transmission electron microscopy for correlative analysis. Importantly, we demonstrate that the use of a particular type of embedding resin is not only compatible with single-molecule localization microscopy but shows a dramatic improvement in fluorophore blinking behavior relative to the whole-mount approaches. Here we used commercially available Click-iT ethynyl-deoxyuridine cell proliferation kit to visualize the DNA replication sites of wild-type Arabidopsis thaliana seedlings, as well as FASCIATA1 and NUCLEOLIN1 mutants and applied our on-section CLEM imaging workflow for the analysis of S-phase progression and nucleolar organization in mutant plants with aberrant nucleolar phenotypes.

Why it matches plant phenotyping methods植物組織向けの超解像・電子顕微鏡CLEM撮像ワークフローを開発・実証しており、核小体構造やS期進行という植物状態の取得が中心的な方法論的貢献である。

abstractHere, we demonstrate an imaging approach based on tissue processing and embedding into methacrylate resin followed by imaging of serial sections by both, single-molecule localization microscopy and transmission electron microscopy for correlative analysis.

Towards the mechanistic understanding of plant-source water isotopic offsets →

In recent years, the widespread use of laser-based analyzers of the isotopic composition of water (δ 18 O and δ 2 H) resulted in an increase in the temporal and spatial resolution of measurements of plant water and their sources. Such datasets revealed previously undetected mismatches between the isotopic composition of subsurface water pools and bulk xylem water usually extracted by cryogenic distillation. To understand the underlying cause of these isotopic mismatches, plant ecophysiologists and ecohydrologists have conducted numerous experiments to address a range of hypotheses. Measurement artifacts produced by water extraction techniques in both bulk xylem water and soil water were claimed to be behind the observed mismatches. However, there is not yet a consensus on a sole mechanism to explain all cases. On the other hand, our research demonstrated the existence of isotopic heterogeneities between the water in different xylem compartments, which also have contrasting degrees of hydraulic connectivity with the transpiration stream. Analogous isotopic patterns were observed in soil water pools and attributed to physicochemical interactions with soil particles. Altogether, it seems that the water pools that are measured matter, and that not all isotopic mismatches can be attributed to methodological artifacts. Given the widespread occurrence of these isotopic mismatches, it is urgent to identify the cause, either natural, artificial, or both. This will allow us to make informed choices of the extraction techniques in each situation and eventually, we could be able to correct potentially biased old datasets. In this regard, we will summarize the most recent findings and suggest research strategies to unravel the underlying mechanisms of isotopic mismatches. In addition, we will outline how such strategies can also provide important insights for closely related disciplines such as plant hydraulics or isotopic analyses of tree-ring archives.

Why it matches plant phenotyping methods植物水の同位体組成という生理状態の測定について、抽出法による測定アーティファクトや測定戦略を中心に整理・検討する方法論的レビューであり、単なる生物学的測定結果の報告ではない。

abstractMeasurement artifacts produced by water extraction techniques in both bulk xylem water and soil water were claimed to be behind the observed mismatches.

3D imaging reveals apical stem cell responses to ambient temperature →

Abstract Plant growth is driven by apical meristems at the shoot and root growth points, which comprise continuously active stem cell populations. While many of the key factors involved in homeostasis of the shoot apical meristem (SAM) have been extensively studied under artificial constant growth conditions, only little is known how variations in the environment affect the underlying regulatory network. To shed light on the responses of the SAM to ambient temperature, we combined 3D live imaging of fluorescent reporter lines that allowed us to monitor the activity of two key regulators of stem cell homeostasis in the SAM namely CLAVATA3 ( CLV3) and WUSCHEL (WUS), with computational image analysis to derive morphological and cellular parameters of the SAM. Whereas CLV3 expression marks the stem cell population, WUS promoter activity is confined to the organizing center (OC), the niche cells adjacent to the stem cells, hence allowing us to record on the two central cell populations of the SAM. Applying an integrated computational analysis of our data we found that variations in ambient temperature not only led to specific changes in spatial expression patterns of key regulators of SAM homeostasis, but also correlated with modifications in overall cellular organization and shoot meristem morphology.

Why it matches plant phenotyping methods3Dライブイメージングと計算画像解析を統合し、温度応答に伴うSAMの形態・細胞パラメータを抽出しており、植物表現型の取得・解析が研究の中心です。

abstractApplying an integrated computational analysis of our data

GWAS identifies candidate regulators of in planta regeneration in Populus trichocarpa →

Plant regeneration is an important dimension of plant propagation, and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. While association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants, the power of these methods relies on the accuracy and scale of phenotypic data used. To enable a largescale GWAS of in planta regeneration in model tree Populus, we implemented a workflow involving semantic segmentation to quantify regenerating plant tissues (callus and shoot) over time. We found the resulting statistics are of highly non-normal distributions, which necessitated transformations or permutations to avoid violating assumptions of linear models used in GWAS. While transformations can lead to a loss of statistical power, we demonstrate that this can be mitigated by the application of the Augmented Rank Truncation method, or avoided altogether using the Multi-Threaded Monte Carlo SNP-set (Sequence) Kernel Association Test to compute empirical p-values in GWAS. We report over 200 statistically supported candidate genes, with top candidates including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. We demonstrate that sensitive genetic discovery for complex developmental traits can be enabled by a workflow based on computer vision and adaptation of several statistical approaches necessitated by to the complexity of regeneration trait expression and distribution.

Why it matches plant phenotyping methods再生組織（カルスとシュート）を意味的セグメンテーションで時系列定量する画像ベース表現型ワークフローが、GWAS用データ取得の中心的手法として明示されているため。

abstractwe implemented a workflow involving semantic segmentation to quantify regenerating plant tissues (callus and shoot) over time.

Analysis of Light Penetration Depth in Apple Tissues by Depth-Resolved Spatial-Frequency Domain Imaging. →

Spatial-frequency domain imaging (SFDI) has been developed as an emerging modality for detecting early-stage bruises of fruits, such as apples, due to its unique advantage of a depth-resolved imaging feature. This paper presents theoretical and experimental analyses to determine the light penetration depth in apple tissues under spatially modulated illumination. Simulation and practical experiments were then carried out to explore the maximum light penetration depths in 'Golden Delicious' apples. Then, apple experiments for early-stage bruise detection using the estimated reduced scattering coefficient mapping were conducted to validate the results of light penetration depths. The results showed that the simulations produced comparable or a little larger light penetration depth in apple tissues (~2.2 mm) than the practical experiment (~1.8 mm or ~2.3 mm). Apple peel further decreased the light penetration depth due to the high absorption properties of pigment contents. Apple bruises located beneath the surface peel with the depth of about 0-1.2 mm could be effectively detected by the SFDI technique. This study, to our knowledge, made the first effort to investigate the light penetration depth in apple tissues by SFDI, which would provide useful information for enhanced detection of early-stage apple bruising by selecting the appropriate spatial frequency.

Why it matches plant phenotyping methodsSFDIによるリンゴ組織の光侵達深度を解析・検証し、青果表面下の打撲を検出する画像計測法を技術的に評価しているため、植物状態の取得法が中心である。

abstractThis paper presents theoretical and experimental analyses to determine the light penetration depth in apple tissues under spatially modulated illumination.

Visualisation of calcium oxalate crystal macropatterns in plant leaves using an improved fast preparation method →

Abstract Leaves of the majority of plants contain calcium oxalate (CaOx) crystals or druses which often occur in spectacular distribution patterns. Numerous studies on CaOx in plant tissues across many different plant groups have been published, since it can be visualised readily under a light microscope (LM). However, there is surprisingly limited knowledge on the actual, precise distribution of CaOx in the leaves of quite ordinary plants such as common native and exotic trees. Traditional sample preparation for the documentation of the distribution of CaOx crystals in a given sample – including overall distribution – requires time‐consuming clearing procedures. Here we present a refined fast preparation method to visualise the overall CaOx complement in a sample: The plant material is ashed and the ash viewed under the polarising microscope. This is a rapid method which overcomes many shortcomings of other methods and permits the visualisation of the entire CaOx content in most leaf samples. Pros and cons in comparison with the conventional clearing technique are discussed. Further aspects for CaOx investigations by micro‐CT and scanning electron microscopy are discussed.

Why it matches plant phenotyping methods葉中のシュウ酸カルシウム結晶の分布を可視化する試料調製法を開発・改良し、従来法と比較しているため、植物形質取得法が中心である。

abstractHere we present a refined fast preparation method to visualise the overall CaOx complement in a sample: The plant material is ashed and the ash viewed under the polarising microscope.

Deep machine learning for cell segmentation and quantitative analysis of radial plant growth →

Plants produce the major part of terrestrial biomass and are long-term deposits of atmospheric carbon. This capacity is to a large extent due to radial growth of woody species - a process driven by cambium stem cells located in distinct niches of shoot and root axes. In the model species Arabidopsis thaliana, thousands of cells are produced by the cambium in radial orientation generating a complex organ anatomy enabling long-distance transport, mechanical support and protection against biotic and abiotic stressors. These complex organ dynamics make a comprehensive and unbiased analysis of radial growth challenging and asks for tools for automated quantification. Here, we combined the recently developed PlantSeg and MorphographX image analysis tools, to characterize tissue morphogenesis of the Arabidopsis hypocotyl. After sequential training of segmentation models on ovules, shoot apical meristems and adult hypocotyls using deep machine learning, followed by the training of cell type classification models, our pipeline segments complex images of transverse hypocotyl sections with high accuracy and classifies central hypocotyl cell types. By applying our pipeline on both wild type and phloem intercalated with xylem (pxy) mutants, we also show that this strategy faithfully detects major anatomical aberrations. Collectively, we conclude that our established pipeline is a powerful phenotyping tool comprehensively extracting cellular parameters and providing access to tissue topology during radial plant growth.

Why it matches plant phenotyping methods深層学習による細胞セグメンテーション・分類パイプラインを開発し、植物組織の形態形成と細胞パラメータを自動抽出する研究であり、植物表現型取得手法が中心である。

abstractwe combined the recently developed PlantSeg and MorphographX image analysis tools, to characterize tissue morphogenesis of the Arabidopsis hypocotyl.

Live imaging of Arabidopsis shoot primordia via a confocal laser scanning microscope. →

Live imaging through confocal laser scanning microscopy enables the recording, analysis, and comparison of the dynamics of shapes and gene expression patterns of plant shoot apical meristems (SAMs) or primordia. Here, we provide a protocol to describe the preparation process of imaging Arabidopsis SAMs and primordia using a confocal microscope. We describe steps for dissection, visualization of meristems using dyes and fluorescent proteins, and gain 3D morphology of meristems. We then detail analysis of shoot meristems using time-lapse imaging. For complete details on the use and execution of this protocol, please refer to Peng et al. (2022). 1 .

Why it matches plant phenotyping methods植物シュート頂端分裂組織の形態・動態を共焦点ライブイメージングで取得・解析する実験プロトコルであり、画像ベースの表現型取得法が中心である。

abstractLive imaging through confocal laser scanning microscopy enables the recording, analysis, and comparison of the dynamics of shapes and gene expression patterns of plant shoot apical meristems (SAMs) or primordia.

The impact of xylem geometry on olive cultivar resistance to Xylella fastidiosa: An image‐based study →

Xylella fastidiosa is a xylem‐limited plant pathogen infecting many crops globally and is the cause of the recent olive disease epidemic in Italy. One strategy proposed to mitigate losses is to replant susceptible crops with resistant varieties. Several genetic, biochemical and biophysical traits are associated to X. fastidiosa disease resistance. However, mechanisms underpinning resistance are poorly understood. We hypothesize that the susceptibility of olive cultivars to infection will correlate to xylem vessel diameters, with narrower vessels being resistant to air embolisms and having slower flow rates limiting pathogen spread. To test this, we scanned stems from four olive cultivars of varying susceptibility to X. fastidiosa using X‐ray computed tomography. Scans were processed by a bespoke methodology that segmented vessels, facilitating diameter measurements. Though significant differences were not found comparing stem‐average vessel section diameters among cultivars, they were found when comparing diameter distributions. Moreover, the measurements indicated that although vessel diameter distributions may play a role regarding the resistance of Leccino, it is unlikely they do for FS17. Considering Young–Laplace and Hagen–Poiseuille equations, we inferred differences in embolism susceptibility and hydraulic conductivity of the vasculature. Our results suggest susceptible cultivars, having a greater proportion of larger vessels, are more vulnerable to air embolisms. In addition, results suggest that under certain pressure conditions, functional vasculature in susceptible cultivars could be subject to greater stresses than in resistant cultivars. These results support investigation into xylem morphological screening to help inform olive replanting. Furthermore, our framework could test the relevance of xylem geometry to disease resistance in other crops.

Why it matches plant phenotyping methodsX線CT画像から木部道管をセグメンテーションし、直径分布を測定する手法が研究の中心であり、病害抵抗性に関わる植物形態形質の取得・解析を実施している。

abstractScans were processed by a bespoke methodology that segmented vessels, facilitating diameter measurements.

High-throughput, dynamic, multi-dimensional: an expanding repertoire of plant respiration measurements. →

A recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources. At the tissue level, several independent respiration measurement options are now available, each with distinct advantages and suitability, including high-throughput sampling capacity. These advancements facilitate the inclusion of respiration rate data into large-scale biological studies such as genetic screens, ecological surveys, crop breeding trials, and multi-omics molecular studies. As a result, our understanding of the correlations of respiration with other biological and biochemical measurements is rapidly increasing. Difficult questions persist concerning the interpretation and utilization of respiration data; concepts such as allocation of respiration to growth versus maintenance, the unnecessary or inefficient use of carbon and energy by respiration, and predictions of future respiration rates in response to environmental change are all insufficiently grounded in empirical data. However, we emphasize that new experimental designs involving novel combinations of respiration rate data with other measurements will flesh-out our current theories of respiration. Furthermore, dynamic recordings of respiration rate, which have long been used at the scale of mitochondria, are increasingly being used at larger scales of size and time to reflect processes of cellular signal transduction and physiological response to the environment. We also highlight how respiratory methods are being better adapted to different plant tissues including roots and seeds, which have been somewhat neglected historically.

Why it matches plant phenotyping methods植物の呼吸速度を測定する技術の革新、高スループット化、動的記録、組織別適応を中心に扱う方法論的レビューであり、植物生理形質の取得法が主題である。

abstractA recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources.

Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing →

Background Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sugar beet (Beta vulgaris). Sugar beet storage roots are characterized by heterogeneous tissue with several cambium rings surrounded by small-celled vascular tissue and big-celled sugar-storing parenchyma between the rings. This study presents a procedure for phenotyping heterogeneous tissues like beetroots by imaging. Results Ten Beta genotypes (nine sugar beet and one fodder beet) were included to establish a pipeline for the automated histologic evaluation of cell characteristics and tissue arrangement using digital image processing written in the programming language R. The identification of cells has been validated by comparison with manual cell identification. Cells are reliably discriminated from intercellular spaces, and cells with similar morphological features are assigned to biological tissue types. Conclusions Genotypic differences in cell diameter and cell arrangement can straightforwardly be phenotyped by the presented workflow. The presented routine can further identify genotypic differences in cell diameter and cell arrangement during early growth stages and between sugar storage capabilities.

Why it matches plant phenotyping methodsデジタル画像処理による根の細胞形態・組織配置の自動フェノタイピング手法を開発し、手動同定との比較で検証しているため。

abstractThis study presents a procedure for phenotyping heterogeneous tissues like beetroots by imaging.

Laser ablation tomography (LATscan) as a new tool for anatomical studies of woody plants →

Traditionally, botanists study plant anatomy by carefully sectioning samples, histological staining to highlight tissues of interests, then imaging slides under light microscopy. This approach generates significant details; however, this workflow is laborious, particularly in woody vines (lianas) with heterogeneous anatomies, and ultimately yields two-dimensional (2D) images. Laser ablation tomography (LATscan) is a high-throughput imaging system that yields hundreds of images per minute. This method has proven useful for studying the structure of delicate plant tissues; however, its utility in understanding the structure of woody tissues is underexplored. We report LATscan-derived anatomical data from several stems of lianas (c. 20 mm) of seven species and compare these results with those obtained through traditional anatomical techniques. LATscan successfully allows the description of tissue composition by differentiating cell type, size, and shape, but also permits the recognition of distinct cell wall composition (e.g. lignin, suberin, cellulose) based on differential fluorescent signals on unstained samples. LATscan generate high-quality 2D images and 3D reconstructions of woody plant samples; therefore, this new technology is useful for both qualitative and quantitative analyses. This high-throughput imaging technology has the potential to bolster phenotyping of vegetative and reproductive anatomy, wood anatomy, and other biological systems.

Why it matches plant phenotyping methods木本植物の解剖学的形質を取得する高速イメージング技術を開発・比較検証しており、植物フェノタイピングへの応用も明示されているため。

abstractLaser ablation tomography (LATscan) is a high-throughput imaging system that yields hundreds of images per minute.

Transmembrane potential, an indicator in situ reporting cellular senescence and stress response in plant tissues →

Background Plant cells usually sustain a stable membrane potential due to influx and/or efflux of charged ions across plasma membrane. With the growth and development of plants, different tissues and cells undergo systemic or local programmed decline. Whether the membrane potential of plasma membrane could report senescence signal of plant tissues and cells is unclear. Results We applied a maneuverable transmembrane potential (TMP) detection method with patch-clamp setup to examine the senescence signal of leaf tissue cells in situ over the whole life cycle in Arabidopsis thaliana. The data showed that the TMPs of plant tissues and cells were varied at different growth stages, and the change of TMP was higher at the vegetative growth stage than at the reproductive stage of plant growth. The distinct change of TMP was detectable between the normal and the senescent tissues and cells in several plant species. Moreover, diverse abiotic stimuli, such as heat stress, hyperpolarized the TMP in a short time, followed by depolarized membrane potential with the senescence occurring. We further examined the TMP of plant chloroplasts, which also indicates the senescence signal in organelles. Conclusions This convenient TMP detection method can report the senescence signal of plant tissues and cells, and can also indicate the potential of plant tolerance to environmental stress.

Why it matches plant phenotyping methods植物組織・細胞の老化やストレス状態を in situ で推定する膜電位測定法を開発・適用し、正常組織や老化組織、複数植物種、ストレス条件で検証しているため、フェノタイピング手法が中心である。

abstractWe applied a maneuverable transmembrane potential (TMP) detection method with patch-clamp setup to examine the senescence signal of leaf tissue cells in situ over the whole life cycle in Arabidopsis thaliana.

Microneedle-Coupled Epidermal Sensors for In-Situ-Multiplexed Ion Detection in Interstitial Fluids. →

Maintaining the concentrations of various ions in body fluids is critical to all living organisms. In this contribution, we designed a flexible microneedle patch coupled electrode array (MNP-EA) for the in situ multiplexed detection of ion species (Na + , K + , Ca 2+ , and H + ) in tissue interstitial fluid (ISF). The microneedles (MNs) are mechanically robust for skin or cuticle penetration (0.21 N/needle) and highly swellable to quickly extract sufficient ISF onto the ion-selective electrochemical electrodes (∼6.87 μL/needle in 5 min). The potentiometric sensor can simultaneously detect these ion species with nearly Nernstian response in the ranges wider enough for diagnosis purposes (Na + : 0.75-200 mM, K + : 1-128 mM, Ca 2+ : 0.25-4.25 mM, pH: 5.5-8.5). The in vivo experiments on mice, humans, and plants demonstrate the feasibility of MNP-EA for timely and convenient diagnosis of ion imbalances with minimal invasiveness. This transdermal sensing platform shall be instrumental to home-based diagnosis and health monitoring of chronic diseases and is also promising for smart agriculture and the study of plant biology.

Why it matches plant phenotyping methods植物を含む生体内イオン状態を測定する低侵襲マイクロニードル電気化学センシング基盤の開発であり、植物での実証も明示されているため、植物生理状態のフェノタイピング手法として中心的です。

abstractwe designed a flexible microneedle patch coupled electrode array (MNP-EA) for the in situ multiplexed detection of ion species (Na + , K + , Ca 2+ , and H + ) in tissue interstitial fluid (ISF).

Time-Resolved Chemical Phenotyping of Whole Plant Roots with Printed Electrochemical Sensors and Machine Learning →

Plants are non-equilibrium systems consisting of time-dependent biological processes. Phenotyping of chemical responses, however, is typically performed using plant tissues, which behave differently to whole plants, in one-off measurements. Single point measurements cannot capture the information rich time-resolved changes in chemical signals in plants associated with nutrient uptake, immunity or growth. In this work, we report a high-throughput, modular, real-time chemical phenotyping platform for continuous monitoring of chemical signals in the often-neglected root environment of whole plants: TETRIS ( T ime-resolved E lectrochemical T echnology for plant R oot I n-situ chemical S ensing). TETRIS consists of screen-printed electrochemical sensors for monitoring concentrations of salt, pH and H 2 O 2 in the root environment of whole plants. TETRIS can detect time-sensitive chemical signals and be operated in parallel through multiplexing to elucidate the overall chemical behavior of living plants. Using TETRIS, we determined the rates of uptake of a range of ions (including nutrients and heavy metals) in Brassica oleracea acephala. We also modulated ion uptake using the ion channel blocker LaCl 3 , which we could monitor using TETRIS. We developed a machine learning model to predict the rates of uptake of salts, both harmful and beneficial, demonstrating that TETRIS can be used for rapid mapping of ion uptake for new plant varieties. TETRIS has the potential to overcome the urgent “bottleneck” in high-throughput screening in producing high yielding plant varieties with improved resistance against stress.

Why it matches plant phenotyping methods植物全体の根圏における化学シグナルを連続測定する高スループット表現型解析プラットフォームを開発し、イオン吸収速度の推定と機械学習による予測まで行っており、フェノタイピング手法が研究の中心である。

abstractwe report a high-throughput, modular, real-time chemical phenotyping platform for continuous monitoring of chemical signals in the often-neglected root environment of whole plants

Use of Near Infrared Spectroscopy (NIRS) to estimate physical, anatomical and hydraulic properties of Eucalyptus wood →

Tree breeding programs and wood industries require simple, time- and cost-effective techniques to process large volumes of samples. In recent decades, near-infrared spectroscopy (NIRS) has been acknowledged as one of the most powerful techniques for wood analysis, making it the most used tool for high-throughput phenotyping. Previous studies have shown that a significant number of anatomical, physical, chemical and mechanical wood properties can be estimated through NIRS, both for angiosperm and gymnosperm species. However, the ability of this technique to predict functional traits related to drought resistance has been poorly explored, especially in angiosperm species. This is particularly relevant since determining xylem hydraulic properties by conventional techniques is complex and time-consuming, clearly limiting its use in studies and applications that demand large amounts of samples. In this study, we measured several wood anatomical and hydraulic traits and collected NIR spectra in branches of two Eucalyptus L’Hér species. We developed NIRS calibration models and discussed their ability to accurately predict the studied traits. The models generated allowed us to adequately calibrate the reference traits, with high R2 (≥0.75) for traits such as P12, P88, the slope of the vulnerability curves to xylem embolism or the fiber wall fraction, and with lower R2 (0.39–0.52) for P50, maximum hydraulic conductivity or frequency of ray parenchyma. We found that certain wavenumbers improve models’ calibration, with those in the range of 4000–5500 cm−1 predicting the highest number of both anatomical and functional traits. We concluded that the use of NIRS allows calibrating models with potential predictive value not only for wood structural and chemical variables but also for anatomical and functional traits related to drought resistance in wood types with complex structure as eucalypts. These results are promising in light of the required knowledge about species and genotypes adaptability to global climatic change.

Why it matches plant phenotyping methodsNIRSを用いてユーカリ木部の解剖学的・水理学的形質を推定する校正モデルを開発・評価しており、植物フェノタイピング手法が研究の中心である。

abstractIn this study, we measured several wood anatomical and hydraulic traits and collected NIR spectra in branches of two Eucalyptus L’Hér species. We developed NIRS calibration models and discussed their ability to accurately predict the studied traits.

Return on carbon investment for plant water transport tissues: functional life span matters →

Trees invest carbon in stem growth every year, and allocate the carbon to build xylem vessels, varying in length and diameter, which serve as a path for the transport of water and nutrients from the soil to the leaves. To assess the cost and benefits of carbon investment into xylem and the resulting hydraulic conductivity, we used a combination of two methods. The first was a novel method of measuring hydraulic conductivity under suction using a syringe pump. The second used dye and cryo-microscopy to determine the ratio and dimensions of conducting vessels in individual year rings. Using these methods, we were able to determine that for Fagus sylvatica , larger vessels did not have lower carbon costs per conductivity due to the shorter functional lifespan, whereas the hydraulic conductivity per cross-sectional area was not larger than smaller vessels. In fact, we found a greater wood density for samples with larger median vessel diameter, implying that larger vessels need more carbon for structural support. Here we present these findings and discuss the potential application of the methods to understand how plants adapt their xylem carbon allocation across species and environmental conditions.

Why it matches plant phenotyping methods植物の木部水輸送特性を測定する新規手法と染色・低温顕微鏡法が研究の中心であり、植物生理形質の取得方法を扱っているため。

abstractThe first was a novel method of measuring hydraulic conductivity under suction using a syringe pump.

Tissue structural analysis for internal browning sweet potatoes using magnetic resonance imaging and bio-electrochemical impedance spectroscopy →

Occurrence of internal browning in sweet potato tuber has recently been confirmed, and its chemical and bacterial characteristics have been reported. However, the structural characteristics of such tissues are unknown. We investigated the tissue structural characteristics inside a browning sweet potato through magnetic resonance imaging (MRI) and bio-electrochemical impedance spectroscopy (BIS) and the relationship was discussed. The high-resolution proton density-weighted (PDW) and proton spin–spin relaxation time (T₂)-weighted (T2W) images of cutting out samples obtained from micro-imaging revealed changes in the physical structure surrounding the browning tissues. The T₂ distribution maps of the same browning samples assumed the changes in the water distribution and water mobility, which generally changes under the influence of solutes, such as metabolites, starch, protein, and metal ions. BIS further confirmed the variation in the distribution of electrolytes in the tissues. MRI may provide a non-destructive assessment of the internal browning of whole sweet potatoes.

Why it matches plant phenotyping methodsMRIとBISを用いてサツマイモ内部褐変の組織構造・水分/電解質分布を評価し、非破壊的な褐変判定への適用可能性を示すことが中心であり、植物状態の取得手法として該当する。

abstractWe investigated the tissue structural characteristics inside a browning sweet potato through magnetic resonance imaging (MRI) and bio-electrochemical impedance spectroscopy (BIS)

Targeting Ultrastructural Events at the Graft Interface of Arabidopsis thaliana by A Correlative Light Electron Microscopy Approach. →

Combining two different plants together through grafting is one of the oldest horticultural techniques. In order to survive, both partners must communicate via the formation of de novo connections between the scion and the rootstock. Despite the importance of grafting, the ultrastructural processes occurring at the graft interface remain elusive due to the difficulty of locating the exact interface at the ultrastructural level. To date, only studies with interfamily grafts showing enough ultrastructural differences were able to reliably localize the grafting interface at the ultrastructural level under electron microscopy. Thanks to the implementation of correlative light electron microscopy (CLEM) approaches where the grafted partners were tagged with fluorescent proteins of different colors, the graft interface was successfully and reliably targeted. Here, we describe a protocol for CLEM for the model plant Arabidopsis thaliana , which unambiguously targets the graft interface at the ultrastructural level. Moreover, this protocol is compatible with immunolocalization and electron tomography acquisition to achieve a three-dimensional view of the ultrastructural events of interest in plant tissues. Graphical abstract.

Why it matches plant phenotyping methods植物組織のグラフト界面を超微細構造レベルで特定・可視化するCLEMプロトコルが研究の中心であり、植物形態状態の画像計測手法に該当する。

abstractMoreover, this protocol is compatible with immunolocalization and electron tomography acquisition to achieve a three-dimensional view of the ultrastructural events of interest in plant tissues.

Fluorogenic properties of 4-dimethylaminocinnamaldehyde (DMACA) enable high resolution imaging of cell-wall-bound proanthocyanidins in plant root tissues →

Proanthocyanidins (PAs) are polymeric phenolic compounds found in plants and used in many industrial applications. Despite strong evidence of herbivore and pathogen resistance-related properties of PAs, their in planta function is not fully understood. Determining the location and dynamics of PAs in plant tissues and cellular compartments is crucial to understand their mode of action. Such an approach requires microscopic localization with fluorescent dyes that specifically bind to PAs. Such dyes have hitherto been lacking. Here, we show that 4-dimethylaminocinnamaldehyde (DMACA) can be used as a PA-specific fluorescent dye that allows localization of PAs at high resolution in cell walls and inside cells using confocal microscopy, revealing features of previously unreported wall-bound PAs. We demonstrate several novel usages of DMACA as a fluorophore by taking advantage of its double staining compatibility with other fluorescent dyes. We illustrate the use of the dye alone and its co-localization with cell wall polymers in different Populus root tissues. The easy-to-use fluorescent staining method, together with its high photostability and compatibility with other fluorogenic dyes, makes DMACA a valuable tool for uncovering the biological function of PAs at a cellular level in plant tissues. DMACA can also be used in other plant tissues than roots, however care needs to be taken when tissues contain compounds that autofluoresce in the red spectral region which can be confounded with the PA-specific DMACA signal.

Why it matches plant phenotyping methods植物組織中のプロアントシアニジンを高解像度で可視化・局在化する蛍光染色法を開発し、共焦点顕微鏡で検証・適用しているため、植物フェノタイピング手法が中心である。

abstractHere, we show that 4-dimethylaminocinnamaldehyde (DMACA) can be used as a PA-specific fluorescent dye that allows localization of PAs at high resolution in cell walls and inside cells using confocal microscopy

Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning →

Passion fruit is a tropical liana of the Passiflora family that is commonly planted throughout the world due to its abundance of nutrients and industrial value. Researchers are committed to exploring the relationship between phenotype and genotype to promote the improvement of passion fruit varieties. However, the traditional manual phenotyping methods have shortcomings in accuracy, objectivity, and measurement efficiency when obtaining large quantities of personal data on passion fruit, especially internal organization data. This study selected samples of passion fruit from three widely grown cultivars, which differed significantly in fruit shape, size, and other morphological traits. A Micro-CT system was developed to perform fully automated nondestructive imaging of the samples to obtain 3D models of passion fruit. A designed label generation method and segmentation method based on U-Net model were used to distinguish different tissues in the samples. Finally, fourteen traits, including fruit volume, surface area, length and width, sarcocarp volume, pericarp thickness, and traits of fruit type, were automatically calculated. The experimental results show that the segmentation accuracy of the deep learning model reaches more than 0.95. Compared with the manual measurements, the mean absolute percentage error of the fruit width and length measurements by the Micro-CT system was 1.94% and 2.89%, respectively, and the squares of the correlation coefficients were 0.96 and 0.93. It shows that the measurement accuracy of external traits of passion fruit is comparable to manual operations, and the measurement of internal traits is more reliable because of the nondestructive characteristics of our method. According to the statistical data of the whole samples, the Pearson analysis method was used, and the results indicated specific correlations among fourteen phenotypic traits of passion fruit. At the same time, the results of the principal component analysis illustrated that the comprehensive quality of passion fruit could be scored using this method, which will help to screen for high-quality passion fruit samples with large sizes and high sarcocarp content. The results of this study will firstly provide a nondestructive method for more accurate and efficient automatic acquisition of comprehensive phenotypic traits of passion fruit and have the potential to be extended to more fruit crops. The preliminary study of the correlation between the characteristics of passion fruit can also provide a particular reference value for molecular breeding and comprehensive quality evaluation.

Why it matches plant phenotyping methodsX線マイクロCTと深層学習による果実の3D形質取得・組織分割・自動測定システムを開発し、手動測定との精度検証も行っており、植物フェノタイピング手法が研究の中心である。

abstractA Micro-CT system was developed to perform fully automated nondestructive imaging of the samples to obtain 3D models of passion fruit.

A multivariate network analysis of ring- and diffuse-porous tree xylem vasculature segmented by convolutional neural networks →

The xylem network, the water conduction system in wood determines the ability of trees to avoid hydraulic failure during drought stress. The capability to withstand embolisms, disruptions of the water column by gas bubbles that contribute to hydraulic failure, is mainly determined by the anatomical arrangement and connectedness (topology) of xylem vessels. However, the quantification of xylem network characteristics has been difficult, so that relating network properties and topology to hydraulic vulnerability and predicting xylem function remains challenging. We studied the xylem vessel networks of three diffuse- ( Fagus sylvatica, Liriodendron tulipifera, Populus x canadensis ) and three ring-porous ( Carya ovata, Fraxinus pennsylvatica, Quercus montana ) tree species using volumetric images of xylem from laser ablation tomography (LATscan). Using convolutional neural networks for image segmentation, we generated three-dimensional, high-resolution maps of xylem vessels, with detailed measurements of morphology and topology. We studied the network topologies by incorporating multiple network metrics into a multidimensional analysis and simulated the robustness of these networks against the loss of individual vessel elements that mimic the obstruction of water flow from embolisms. This analysis suggested that networks in Populus x canadensis and Carya ovata are quite similar despite being different wood types. Similar networks had comparable experimental measurements of P50 values (pressure inducing 50% hydraulic conductivity loss) obtained from hydraulic vulnerability curves, a common tool to quantify the cavitation resistance of xylem networks. This work produced novel data on plant xylem vessel networks and introduces new methods for analyzing the biological impact of these network structures. Significance statement The resilience of fluid transport networks such as xylem vessels that conduct water in trees depends on both the structure of the network and features of the individual network elements. High-resolution reconstruction of xylem networks from six tree species provided novel, three-dimensional, structural data which enabled the xylem networks to be described using graph theory. Using an array of network metrics as multidimensional descriptors, we compared the xylem networks between species and showed relationships to simulated and experimental measures of drought resistance. In addition to providing insight on drought resistance, these approaches offer new ways for comparative analysis of networks applicable to many systems.

Why it matches plant phenotyping methodsCNNによる画像セグメンテーションで木部道管を三次元再構成し、形態・トポロジー形質を定量化する手法を開発・適用しており、植物フェノタイピングが中心。

abstractUsing convolutional neural networks for image segmentation, we generated three-dimensional, high-resolution maps of xylem vessels, with detailed measurements of morphology and topology.

Quantifying Gene Expression Domains in Plant Shoot Apical Meristems. →

The shoot apical meristem is the plant tissue that produces the plant aerial organs such as flowers and leaves. To better understand how the shoot apical meristem develops and adapts to the environment, imaging developing shoot meristems expressing fluorescence reporters through laser confocal microscopy is becoming increasingly important. Yet, there are not many computational pipelines enabling a systematic and high-throughput characterization of the produced microscopy images. This chapter provides a simple method to analyze 3D images obtained through laser scanning microscopy and quantitatively characterize radially or axially symmetric 3D fluorescence domains expressed in a tissue or organ by a reporter. Then, it presents different computational pipelines aiming at performing high-throughput quantitative image analysis of gene expression in plant inflorescence and floral meristems. This methodology has notably enabled the quantitative characterization of how stem cells respond to environmental perturbations in the Arabidopsis thaliana inflorescence meristem and will open new avenues in the use of quantitative analysis of gene expression in shoot apical meristems. Overall, the presented methodology provides a simple framework to analyze quantitatively gene expression domains from 3D confocal images at the tissue and organ level, which can be applied to shoot meristems and other organs and tissues.

Why it matches plant phenotyping methods植物メリステムの3D蛍光画像から遺伝子発現ドメインを定量抽出する計算画像解析パイプラインが研究の中心であり、植物の状態・発現空間を測定する方法論として適格。

abstractthere are not many computational pipelines enabling a systematic and high-throughput characterization of the produced microscopy images

Localizing Molecules in Plant Cell Walls Using Fluorescence Microscopy. →

Autofluorescence of plant tissues can be used as a label-free method to detect a range of phenolic-based cell wall components including lignin, suberin, and ferulate using widefield or confocal fluorescence microscopy. Likewise, fluorescently labeled antibodies can be used to localize specific carbohydrate molecules including arabinoxylan, β-1,4 galactan, glucomannan, glucuronoxylan, pectins, and xyloglucan. When combined, these two methods allow detailed study of topochemistry in different plant tissues for phenotyping of mutant varieties and plant biology studies. This article describes the protocols for fluorescent detection and imaging of molecules in plant cell walls using autofluorescence and immunofluorescence.

Why it matches plant phenotyping methods植物細胞壁成分を蛍光顕微鏡で検出・局在化するプロトコル自体が中心で、変異体のフェノタイピングへの利用を明示しているため。

abstractWhen combined, these two methods allow detailed study of topochemistry in different plant tissues for phenotyping of mutant varieties and plant biology studies.

Analysis of light penetration depth in apple tissues by depth- resolved spatial-frequency domain imaging →

Spatial-frequency domain imaging (SFDI) has been developed as an emerging modality for detecting early-stage bruises of fruits, like apples, due to its unique advantage of depth-resolved imaging feature, in comparison with the conventional imaging techniques under uniform or diffuse illumination. This paper presents theoretical and experimental analyses to determine the light penetration depth in apple tissues under spatially modulated illumination. First, light penetrating capacity of the demodulated direct component and amplitude component images was investigated to prove the performance of the constructed SFDI system. Simulation and practical experiments were then carried out to explore the maximum light penetration depths in ‘Golden Delicious’ apples, in terms of two critical parameters, i.e., image contrast, and ratio of peak-to-valley intensity. Finally, apple experiment for early-stage bruise detection using the estimated reduced scattering coefficient mapping was conducted to validate the results of light penetration depths. The results showed that the simulations produced comparable or a little larger light penetration depth in apple tissues (~ 2.2 mm) than the practical experiment (~ 1.8 mm, or ~ 2.3 mm). Apple peel further decreased the light penetration depth due to the high absorption properties of pigment contents. The apple bruise, located beneath the surface peel with the depth of about 0-1.2 mm, could be effectively detected by the SFDI technique. This study, to our knowledge, made the first effort to investigate the light penetration depth in apple tissues by SFDI, which would provide useful information for enhanced detection of early-stage apple bruising by selecting appropriate spatial frequency.

Why it matches plant phenotyping methodsSFDIによるリンゴ組織の光浸透深さを解析・検証し、赤化（打撲）という果実状態の検出に応用しており、画像取得・解析法が研究の中心である。

abstractThis paper presents theoretical and experimental analyses to determine the light penetration depth in apple tissues under spatially modulated illumination.

Extraction of plant parenchyma by computer image processing technology →

People are increasingly using different kinds of plant products, such as wood, but there are many kinds of wood and it is difficult to analyze and identify them, so how to use auxiliary equipment to analyze wood and achieve the goal of accurate wood identification without damaging the product itself has become one of the important problems to be solved in the field of wood research. The axial thin-walled tissue has important wood grain information and it is one of the important features for wood identification. In this paper, we studied the microscopic images of broadleaf wood, and obtained the microstructure images of wood cross-section by photographing, and extracted the complete axial thin-walled tissue morphology of wood by using computer image processing technology and other ways about computer vision. Firstly, the axial thin-walled wood images were de-noised to eliminate some noise effects, so as to facilitate the separation of the axial thin-walled wood; then the images were processed by mathematical morphology to successfully extract the axial thin-walled wood and duct morphology from the cross-sectional images of broadleaf wood; finally, the axial thin-walled wood was separated from the duct by calculating the area of the closed area.

Why it matches plant phenotyping methods木材横断面画像から軸方向柔組織と道管の形態・面積を抽出する画像処理手法が研究の中心であり、植物組織形態という観測可能な形質を取得している。

abstractextracted the complete axial thin-walled tissue morphology of wood by using computer image processing technology and other ways about computer vision

A robust and efficient automatic method to segment maize FASGA stained stem cross section images to accurately quantify histological profile. →

Background Grasses internodes are made of distinct tissues such as vascular bundles, epidermis, rind and pith. The histology of grasses stem was largely revisited recently taking advantage of the development of microscopy combined with the development of computer-automated image analysis workflows. However, the diversity and complexity of the histological profile complicates quantification. Accurate and automated analysis of histological images thus remains challenging. Results Herein, we present a workflow that automatically segments maize internode cross section images into 40 distinct tissues: two tissues in the epidermis, 19 tissues in the rind, 14 tissues in the pith and 5 tissues in the bundles. This level of segmentation is achieved by combining the Hue, Saturation and Value properties of each pixel and the location of each pixel in FASGA stained cross sectiona. This workflow is likewise able to highlight significant and subtle histological genotypic variations between maize internodes. The grain of precision provided by the workflow also makes it possible to demonstrate different levels of sensitivity to digestion by enzymatic cocktails of the tissues in the pith. The precision and strength of the workflow is all the more impressive because it is preserved on cross section images of other grasses such as miscanthus or sorghum. Conclusions The fidelity of this tool and its capacity to automatically identify variations of a large number of histological profiles among different genotypes pave the way for its use to identify genotypes of interest and to study the underlying genetic bases of variations in histological profiles in maize or other species.

Why it matches plant phenotyping methodsトウモロコシ茎断面の組織プロファイルを自動セグメンテーションし、組織形態を定量化する画像解析ワークフローの開発が中心であるため。

titleA robust and efficient automatic method to segment maize FASGA stained stem cross section images to accurately quantify histological profile.

On-field optical imaging data for the pre-identification and estimation of leaf deformities. →

Visually nonidentifiable pathological symptoms at an early stage are a major limitation in agricultural plantations. Thickness reduction in palisade parenchyma (PP) and spongy parenchyma (SP) layers is one of the most common symptoms that occur at the early stage of leaf diseases, particularly in apple and persimmon. To visualize variations in PP and SP thickness, we used optical coherence tomography (OCT)-based imaging and analyzed the acquired datasets to determine the threshold parameters for pre-identifying and estimating persimmon and apple leaf abnormalities using an intensity-based depth profiling algorithm. The algorithm identified morphological differences between healthy, apparently-healthy, and infected leaves by applying a threshold in depth profiling to classify them. The qualitative and quantitative results revealed changes and abnormalities in leaf morphology in addition to disease incubation in both apple and persimmon leaves. These can be used to examine how initial symptoms are influenced by disease growth. Thus, these datasets confirm the significance of OCT in identifying disease symptoms nondestructively and providing a benchmark dataset to the agriculture community for future reference.

Why it matches plant phenotyping methodsOCT画像と強度ベース深度プロファイリングを用いて葉の形態異常・病徴を定量推定し、閾値決定とベンチマークデータセット提供を行うことが研究の中心であるため。

abstractwe used optical coherence tomography (OCT)-based imaging and analyzed the acquired datasets to determine the threshold parameters for pre-identifying and estimating persimmon and apple leaf abnormalities using an intensity-based depth profiling algorithm.

Tailoring confocal microscopy for in-cell photophysiology studies →

Summary Photoautotrophs environmental responses have been extensively studied at the organism and ecosystem level. However, less is known about their photosynthesis at the single cell level. This information is needed to understand photosynthetic acclimation processes, as light changes as it penetrates cells, layers of cells or organs. Furthermore, cells within the same tissue may behave differently, being at different developmental/physiological stages. Here we describe a new approach for single-cell and subcellular photophysiology based on the customisation of confocal microscopy to assess chlorophyll fluorescence quenching by the saturation pulse method. We exploit this setup to: i. reassess the specialisation of photosynthetic activities in developing tissues of non-vascular plants; ii. identify a specific subpopulation of phytoplankton cells in marine photosymbiosis, which are consolidating metabolic connections with their animal hosts, and iii. testify to the link between light penetration and photoprotection responses inside the different tissues that constitute a plant leaf anatomy. Motivation Visualising photosynthetic responses in 3D is essential for understanding most acclimation processes, as light changes within photosynthetic tissues as it penetrates the absorbing/diffusing layers of the cells. To achieve this goal, we developed a new imaging workflow merging confocal microscopy and saturating pulse chlorophyll fluorescence detection. This method applies to samples characterised by increasing complexity and its simplicity will contribute to its widespread use in plant and microalgae photoacclimation studies.

Why it matches plant phenotyping methods共焦点顕微鏡と飽和パルス式クロロフィル蛍光検出を統合し、単細胞・組織内の光合成生理応答を取得する新規イメージング手法を開発しているため、植物フェノタイピング手法が中心である。

abstractHere we describe a new approach for single-cell and subcellular photophysiology based on the customisation of confocal microscopy to assess chlorophyll fluorescence quenching by the saturation pulse method.

Laser Ablation Tomography (LATscan) as a new tool for anatomical studies of woody plants →

Summary Traditionally, botanists study the anatomy of plants by carefully sectioning samples, histological staining to highlight tissues of interests, then imaging slides under light microscopy. This approach generates significant details; however, this traditional workflow is laborious and time consuming, and ultimately yields two-dimensional (2D) images. Laser Ablation Tomography (LATscan) is a high-throughput imaging system that yields hundreds of images per minute. This method has proven useful for studying the structure of delicate plant tissues, however its utility in understanding the structure of tougher woody tissues is underexplored. We report LATscan-derived anatomical data from several woody stems (ca. 20 mm) of eight species and compare these results to those obtained through traditional anatomical techniques. LATscan successfully allows the description of tissue composition by differentiating cell type, size, and shape, but also permits the recognition of distinct cell wall composition (e.g., lignin, suberin, cellulose) based on differential fluorescent signals on unstained samples. LATscan generate high-resolution 2D images and 3D reconstructions of woody plant samples, therefore this new technology is useful for both qualitative and quantitative analyses. This high-throughput imaging technology has the potential to bolster phenotyping of vegetative and reproductive anatomy, wood anatomy, and other biological systems such as plant-pathogen and parasitic plant associations.

Why it matches plant phenotyping methods木本植物組織の高速・高解像度画像化と3D再構成を行うLATscanを開発・従来法と比較検証しており、植物形態・解剖形質の取得法が中心である。

abstractLaser Ablation Tomography (LATscan) is a high-throughput imaging system that yields hundreds of images per minute.

Synchrotron XFM tomography for elucidating metals and metalloids in hyperaccumulator plants. →

Visualizing the endogenous distribution of elements within plant organs affords key insights in the regulation of trace elements in plants. Hyperaccumulators have extreme metal(loid) concentrations in their tissues, which make them useful models for studying metal(loid) homeostasis in plants. X-ray-based methods allow for the nondestructive analysis of most macro and trace elements with low limits of detection. However, observing the internal distributions of elements within plant organs still typically requires destructive sample preparation methods, including sectioning, for synchrotron X-ray fluorescence microscopy (XFM). X-ray fluorescence microscopy-computed tomography (XFM-CT) enables "virtual sectioning" of a sample thereby entirely avoiding artefacts arising from destructive sample preparation. The method can be used on frozen-hydrated samples, as such preserving "life-like" conditions. Absorption and Compton scattering maps obtained from synchrotron XFM-CT offer exquisite detail on structural features that can be used in concert with elemental data to interpret the results. In this article we introduce the technique and use it to reveal the internal distribution of hyperaccumulated elements in hyperaccumulator plant species. XFM-CT can be used to effectively probe the distribution of a range of different elements in plant tissues/organs, which has wide ranging applications across the plant sciences.

Why it matches plant phenotyping methods植物組織内の元素分布と構造を非破壊・三次元で取得するXFM-CT手法を導入し、ハイパーアキュムレーター植物で実証しており、植物表現型取得法が中心である。

abstractIn this article we introduce the technique and use it to reveal the internal distribution of hyperaccumulated elements in hyperaccumulator plant species.

Integrated PET and confocal imaging informs a functional timeline for the dynamic process of vascular reconnection during grafting. →

Grafting is a widely used agricultural technique that involves the physical joining of separate plant parts so they form a unified vascular system, enabling beneficial traits from independent genotypes to be captured in a single plant. This simple, yet powerful tool has been used for thousands of years to improve abiotic and biotic stress tolerance, enhance yield, and alter plant architecture in diverse crop systems. Despite the global importance and ancient history of grafting, our understanding of the fundamental biological processes that make this technique successful remains limited, making it difficult to efficiently expand on new genotypic graft combinations. One of the key determinants of successful grafting is the formation of the graft junction, an anatomically unique region where xylem and phloem strands connect between newly joined plant parts to form a unified vascular system. Here, we use an integrated imaging approach to establish a spatiotemporal framework for graft junction formation in the model crop Solanum lycopersicum (tomato), a plant that is commonly grafted worldwide to boost yield and improve abiotic and biotic stress resistance. By combining Positron Emission Tomography (PET), a technique that enables the spatio-temporal tracking of radiolabeled molecules, with high-resolution laser scanning confocal microscopy (LSCM), we are able to merge detailed, anatomical differentiation of the graft junction with a quantitative timeline for when xylem and phloem connections are functionally re-established. In this timeline, we identify a 72-hour window when anatomically connected xylem and phloem strands regain functional capacity, with phloem restoration typically preceding xylem restoration by about 24-hours. Furthermore, we identify heterogeneity in this developmental and physiological timeline that corresponds with microvariability in the physical contact between newly joined rootstock-scion tissues. Our integration of PET and confocal imaging technologies provides a spatio-temporal timeline that will enable future investigations into cellular and tissue patterning events that underlie successful versus failed vascular restoration across the graft junction.

Why it matches plant phenotyping methodsPETと共焦点顕微鏡を統合し、植物の接ぎ木接合部における血管再連結の時空間・機能状態を定量化する手法が研究の中心であるため、植物フェノタイピング手法として収録する。

abstractHere, we use an integrated imaging approach to establish a spatiotemporal framework for graft junction formation in the model crop Solanum lycopersicum (tomato)

Evaluation of near-infrared hyperspectral imaging for the assessment of potato processing aptitude. →

The potato ( Solanum tuberosum L.) is the world's fifth most important staple food with high socioeconomic relevance. Several potato cultivars obtained by selection and crossbreeding are currently on the market. This diversity causes tubers to exhibit different behaviors depending on the processing to which they are subjected. Therefore, it is interesting to identify cultivars with specific characteristics that best suit consumer preferences. In this work, we present a method to classify potatoes according to their cooking or frying as crisps aptitude using NIR hyperspectral imaging (HIS) combined with a Partial Least Squares Discriminant Analysis (PLS-DA). Two classification approaches were used in this study. First, a classification model using the mean spectra of a dataset composed of 80 tubers belonging to 10 different cultivars. Then, a pixel-wise classification using all the pixels of each sample of a small subset of samples comprised of 30 tubers. Hyperspectral images were acquired using fresh-cut potato slices as sample material placed on a mobile platform of a hyperspectral system in the NIR range from 900 to 1,700 nm. After image processing, PLS-DA models were built using different pre-processing combinations. Excellent accuracy rates were obtained for the models developed using the mean spectra of all samples with 90% of tubers correctly classified in the external dataset. Pixel-wise classification models achieved lower accuracy rates between 66.62 and 71.97% in the external validation datasets. Moreover, a forward interval PLS (iPLS) method was used to build pixel-wise PLS-DA models reaching accuracies above 80 and 71% in cross-validation and external validation datasets, respectively. Best classification result was obtained using a subset of 100 wavelengths (20 intervals) with 71.86% of pixels correctly classified in the validation dataset. Classification maps were generated showing that false negative pixels were mainly located at the edges of the fresh-cut slices while false positive were principally distributed at the central pith, which has singular characteristics.

Why it matches plant phenotyping methodsNIRハイパースペクトル画像とPLS-DAを用いてジャガイモ塊茎の加工適性を分類する測定・解析手法が研究の中心であり、検証データと分類精度も提示している。

abstractIn this work, we present a method to classify potatoes according to their cooking or frying as crisps aptitude using NIR hyperspectral imaging (HIS) combined with a Partial Least Squares Discriminant Analysis (PLS-DA).

The shape of aroma: measuring and modeling citrus oil gland distribution →

From preventing scurvy to being part of religious rituals, citrus are intrinsically connected to human health and perception. From tiny mandarins to head-sized pummelos, citrus capability of hybridization provides a vastly diverse array of fruit sizes and shapes, which in turn corresponds to a diversity of flavors and aromas. These sensory qualities are tightly linked to oil glands in the citrus skin. The oil glands are also key to understanding fruit development, and the essential oils contained by them are fundamental in the food and perfume industries. We study the shape of citrus based on 3D X-ray CT scan reconstruction of 163 different citrus samples comprising 58 different species and cultivars, including samples of all fundamental citrus species. First, using the power of X-rays and image processing, we are able to compare and contrast size ratios between different tissues, such as the size of the skin compared to the rind or the flesh. Second, we model the fruit shape as an ellipsoidal surface, and later we study and infer possible oil gland distributions on this surface using principles of directional statistics. We finally compare and contrast these overall fruit shape models along their gland distributions across different citrus species. This morphological modeling will allow us later to link genotype with phenotype, furthering our insight on how the physical shape is genetically specified in DNA.

Why it matches plant phenotyping methods3D X線CT、画像処理、形状モデリング、方向統計を中核として、柑橘果実の形態と油腺分布という植物形質を定量化しているため、フェノタイピング手法研究に該当します。

abstractWe study the shape of citrus based on 3D X-ray CT scan reconstruction of 163 different citrus samples comprising 58 different species and cultivars

NIR-based models for estimating selected physical and chemical wood properties from fast-growing plantations →

As a faster, reliable, and low cost technique, applicable to large samplings, near infrared (NIR) spectroscopy technology has been widely applied for high-throughput phenotyping in forest breeding programmes. The aim of this study was to develop multivariate models for estimating the chemical and physical properties of juvenile wood based on NIR signatures of milled wood. Moreover, two approaches, namely, external validation by clone and by age, were tested to validate the model for estimating extractive content. NIR spectra of wood specimens taken from three clones of Eucalyptus urophylla (one to six years old) grown in southern Brazil were used to calibrate and validate models for predicting the wood basic density, total extractives, ash content, holocellulose content, syringyl to guaiacyl ratio (S/G) and elementary components of the wood. PLS-R models were validated by an independent set of wood specimens and presented promising statistics for the estimating wood density (R2p = 0.768), extractives (R2p = 0.912), ash (R2p = 0.936) and carbon (R2p = 0.697) contents from NIR signatures measured in the milled wood of young trees. Furthermore, NIR models for estimating the extractive content of wood were validated using the clones or ages left out of the training sets. Most models presented satisfactory statistics (R2 > 90%) and could be applied to routine laboratory analyses or to select potential trees in Eucalyptus breeding programmes.

Why it matches plant phenotyping methodsNIRスペクトルから若齢ユーカリ木材の物理・化学形質を推定するモデルを開発し、クローン別・樹齢別に独立検証しており、森林育種向けの表現型取得手法が中心である。

abstracttwo approaches, namely, external validation by clone and by age, were tested to validate the model for estimating extractive content

Workflow for Phenotyping Sugar Beet Roots by Automated Evaluation of Cell Characteristics and Tissue Arrangement Using Digital Image Processing →

Background: Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sugar beet ( Beta vulgaris ). Sugar beet storage roots are characterized by heterogeneous tissue with several cambium rings surrounded by small-celled vascular tissue and big-celled sugar-storing parenchyma between the rings. This study presents a procedure for phenotyping heterogeneous tissues like beetroots by imaging. Results Ten Beta genotypes (nine sugar beet and one fodder beet) were included to establish a workflow for the automated histologic evaluation of cell characteristics and tissue arrangement using digital image processing written in the programming language R. The identification of cells has been validated by comparison with manual cell identification. Cells are reliably discriminated from intercellular spaces, and cells with similar morphological features are assigned to biological tissue types. Conclusions Genotypic differences in cell diameter and cell arrangement can straightforwardly be phenotyped by the presented workflow. The presented routine can further identify genotypic differences in cell diameter and cell arrangement during early growth stages and between sugar storage capabilities.

Why it matches plant phenotyping methodsデジタル画像処理とRによる根組織の細胞形態・配置の自動フェノタイピング手法を開発し、手動同定との比較で検証しているため、方法が研究の中心である。

abstractThis study presents a procedure for phenotyping heterogeneous tissues like beetroots by imaging.

Ultrasound Pulse Emission Spectroscopy Method to Characterize Xylem Conduits in Plant Stems →

Although it is well known that plants emit acoustic pulses under drought stress, the exact origin of the waveform of these ultrasound pulses has remained elusive. Here, we present evidence for a correlation between the characteristics of the waveform of these pulses and the dimensions of xylem conduits in plants. Using a model that relates the resonant vibrations of a vessel to its dimension and viscoelasticity, we extract the xylem radii from the waveforms of ultrasound pulses and show that these are correlated and in good agreement with optical microscopy. We demonstrate the versatility of the method by applying it to shoots of ten different vascular plant species. In particular, for Hydrangea quercifolia , we further extract vessel element lengths with our model and compare them with scanning electron cryomicroscopy. The ultrasonic, noninvasive characterization of internal conduit dimensions enables a breakthrough in speed and accuracy in plant phenotyping and stress detection.

Why it matches plant phenotyping methods植物茎内の木部導管寸法を超音波波形から非侵襲的に推定する手法を開発し、光学顕微鏡および電子顕微鏡と比較検証している。植物フェノタイピングへの応用が中心である。

abstractUsing a model that relates the resonant vibrations of a vessel to its dimension and viscoelasticity, we extract the xylem radii from the waveforms of ultrasound pulses and show that these are correlated and in good agreement with optical microscopy.

Phase separation-based visualization of protein-protein interactions and kinase activities in plants →

Protein activities depend heavily on protein complex formation and dynamic post-translational modifications, such as phosphorylation. Their dynamic nature is notoriously difficult to monitor in planta at cellular resolution, often requiring extensive optimization and high-end microscopy. Here, we generated and exploited the SYnthetic Multivalency in PLants (SYMPL)-vector set to study protein-protein interactions (PPIs) and kinase activities in planta based on phase separation. This technology enabled easy detection of inducible, binary and ternary protein-protein interactions among cytoplasmic, nuclear and plasma membrane proteins in plant cells via a robust image-based readout. Moreover, we applied the SYMPL toolbox to develop an in vivo reporter for SnRK1 kinase activity, allowing us to visualize tissue-specific, dynamic SnRK1 activation upon energy deprivation in stable transgenic Arabidopsis plants. The applications of the SYMPL cloning toolbox lay the foundation for the exploration of PPIs, phosphorylation and other post-translational modifications with unprecedented ease and sensitivity.

Why it matches plant phenotyping methods植物体内のタンパク質相互作用とキナーゼ活性を画像で可視化するSYMPL技術を開発し、植物の組織特異的・動的な生理状態を測定しているため、方法開発が中心である。

abstractThis technology enabled easy detection of inducible, binary and ternary protein-protein interactions among cytoplasmic, nuclear and plasma membrane proteins in plant cells via a robust image-based readout.

Multispecies, multisite, multi-age PLS regression models of chemical properties of eucalypts wood using Fourier Transformed near-Infrared (FT-NIR) spectroscopy →