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Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum.

Plant phenomics (Washington, D.C.) · 8 Apr 2022 · 10.34133/2022/9768502

Abstract

Sorghum, a genetically diverse C 4 cereal, is an ideal model to study natural variation in photosynthetic capacity. Specific leaf nitrogen (SLN) and leaf mass per leaf area (LMA), as well as, maximal rates of Rubisco carboxylation ( V cmax ), phosphoenolpyruvate (PEP) carboxylation ( V pmax ), and electron transport ( J max ), quantified using a C 4 photosynthesis model, were evaluated in two field-grown training sets ( n = 169 plots including 124 genotypes) in 2019 and 2020. Partial least square regression (PLSR) was used to predict V cmax ( R 2 = 0.83), V pmax ( R 2 = 0.93), J max ( R 2 = 0.76), SLN ( R 2 = 0.82), and LMA ( R 2 = 0.68) from tractor-based hyperspectral sensing. Further assessments of the capability of the PLSR models for V cmax , V pmax , J max , SLN, and LMA were conducted by extrapolating these models to two trials of genome-wide association studies adjacent to the training sets in 2019 ( n = 875 plots including 650 genotypes) and 2020 ( n = 912 plots with 634 genotypes). The predicted traits showed medium to high heritability and genome-wide association studies using the predicted values identified four QTL for V cmax and two QTL for J max . Candidate genes within 200 kb of the V cmax QTL were involved in nitrogen storage, which is closely associated with Rubisco, while not directly associated with Rubisco activity per se . J max QTL was enriched for candidate genes involved in electron transport. These outcomes suggest the methods here are of great promise to effectively screen large germplasm collections for enhanced photosynthetic capacity.

Plant phenotyping relevance

トラクター搭載ハイパースペクトルセンシングとPLSRにより光合成関連形質を推定し、独立試験でモデル性能を評価している。形質取得法の開発・検証と大規模スクリーニングへの応用が中心である。

abstractPartial least square regression (PLSR) was used to predict V cmax ( R 2 = 0.83), V pmax ( R 2 = 0.93), J max ( R 2 = 0.76), SLN ( R 2 = 0.82), and LMA ( R 2 = 0.68) from tractor-based hyperspectral sensing.
abstractFurther assessments of the capability of the PLSR models for V cmax , V pmax , J max , SLN, and LMA were conducted by extrapolating these models to two trials of genome-wide association studies
abstractThese outcomes suggest the methods here are of great promise to effectively screen large germplasm collections for enhanced photosynthetic capacity.

Code and data availability

The authors state that all phenotypic data used to develop the PLSR models (ground truth Vcmax, Vpmax, Jmax, SLN, LMA and associated hyperspectral measurements) is publicly available via a UQ eSpace DOI. Genotypic marker data is only available upon request and is not a phenotyping asset. No author analysis code or URLs

Datasetpublic

All phenotypic data used to develop the models presented in this manuscript is available here: https://doi.org/10.48610/acbe0df .

Open resource ↗10.48610/acbe0df · lines:488-522

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