The developed python script with detailed annotations can be retrieved from github (https://github.com/and-jonas/stb_placl).
Open resource ↗and-jonas/stb_placl · pdf-page:8 lines:1-43Unverified paper record
In-field detection and quantification of Septoria tritici blotch in diverse wheat germplasm using spectral-temporal features
bioRxiv · 10 Jun 2019 · 10.1101/664011
Abstract
Hyperspectral remote sensing holds the potential to detect and quantify crop diseases in a rapid and non-invasive manner. Such tools could greatly benefit resistance breeding, but their adoption is hampered by i) a lack of specificity to disease-related effects and ii) insufficient robustness to variation in reflectance caused by genotypic diversity and varying environmental conditions, which are fundamental elements of resistance breeding. We hypothesized that relying exclusively on temporal changes in canopy reflectance during pathogenesis may allow to specifically detect and quantify crop diseases whilst minimizing the confounding effects of genotype and environment. To test this hypothesis, we collected time-resolved canopy hyperspectral reflectance data for 18 diverse genotypes on infected and disease-free plots and engineered spectral-temporal features representing this hypothesis. Our results confirm the lack of specificity and robustness of disease assessments based on reflectance spectra at individual time points. We show that changes in spectral reflectance over time are indicative of the presence and severity of septoria tritici blotch (STB) infections. Furthermore, the proposed time-integrated approach facilitated the delineation of disease from physiological senescence, which is pivotal for efficient selection of STB-resistant material under field conditions. A validation of models based on spectral-temporal features on a diverse panel of >300 wheat genotypes offered evidence for the robustness of the proposed method. This study demonstrates the potential of time-resolved canopy reflectance measurements for robust assessments of foliar diseases in the context of resistance breeding.
Plant phenotyping relevance
時系列ハイパースペクトル反射からコムギ葉病害の存在・重症度を推定する特徴量と手法を開発し、多様な遺伝子型で検証しており、植物表現型取得が研究の中心である。
abstractwe collected time-resolved canopy hyperspectral reflectance data for 18 diverse genotypes on infected and disease-free plots and engineered spectral-temporal features representing this hypothesis.
abstractA validation of models based on spectral-temporal features on a diverse panel of >300 wheat genotypes offered evidence for the robustness of the proposed method.
abstractThis study demonstrates the potential of time-resolved canopy reflectance measurements for robust assessments of foliar diseases in the context of resistance breeding.
Code and data availability
保存済みの本文根拠を更新済みルールで再検証し、公開資産2件を確認しました。
The analysis was implemented using a custom-developed R-Script (https://github.com/and-jonas/rfe).
Open resource ↗and-jonas/rfe · pdf-page:13 lines:1-41This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.