Leveraging leaf spectroscopy to identify drought-tolerant soybean cultivars

Abstract

• Breeding for drought tolerance is becoming a necessity for most of the main crops, including soybean. • Phenotyping for physiological traits is considered unfeasible in breeding strategy focuses on abiotic stress tolerance. • Spectroscopy data can be used for high-throughput phenotyping methodology for hard-to-measure traits. • PLSR models successfully predicted physiological parameters at leaf-level. • Hyperspectral data can be used as a selection methodology for physiological traits in soybean cultivars under drought conditions. Understanding cultivars' physiological traits variations under abiotic stresses is critical to improve phenotyping and selections of resistant crop varieties. Traditional methods of accessing physiological traits in plants are costly and time consuming, which prevents their use in breeding programs. Spectroscopy data and statistical approaches such as partial least square regression could be applied to rapidly collect and predict several physiological parameters at leaf-level, allowing phenotyping several genotypes in a high-throughput manner. We collected spectroscopy data of twenty soybean cultivars planted under well-watered and drought conditions during the reproductive phase. At 20 days after drought was imposed, we measured leaf pigments content (chlorophyll a and b, and carotenoids), specific leaf area, electrons transfer rate, and photosynthetic active radiation. At 28 days after drought imposition, we measured leaf pigments content, specific leaf area, relative water content, and leaf temperature. Partial least square regression models accurately predicted leaf pigments content, specific leaf area, and leaf temperature (cross-validation R 2 ranging from 0.56 to 0.84). Discriminant analysis using 54 wavelengths was able to select the best-performance cultivars regarding all evaluated physiological traits. We showed the great potential of using spectroscopy as a feasible, non-destructive, and accurate method to estimate physiological traits and screening of superior genotypes.

Plant phenotyping relevance

葉スペクトロスコピーとPLSRを用いて生理形質を非破壊・高スループットに推定する手法を開発・適用し、予測性能も評価しているため、フェノタイピング手法が中心である。

Code and data availability

公開論文であることは確認できましたが、現在の公式API・許可済み取得経路では本文を自動取得できませんでした。

No evidence-backed public reproduction asset is currently recorded.