DIGITAL IMAGING-BASED PHENOTYPING OF WHEAT KERNELS UNDER DROUGHT STRESS

Abstract

Drought stress significantly impairs wheat growth and productivity, primarily by affecting kernel development.Given their strong association with kernel yield and quality, kernel traits offer reliable means to assess genotypic responses to drought stress conditions.In this study, 70 diverse wheat (Triticum aestivum L.) genotypes were evaluated under two moisture regimes: well-watered (four irrigations) and drought stress (irrigation withheld after the first watering).At maturity, the following agronomic traits were recorded: number of days to 50% heading, number of days to 50% physiological maturity, number of kernels per spike, number of spikelets per spike, thousand kernel weight, and kernel yield per spike.Nine kernels from each genotype were photographed in horizontal and vertical orientations using a 3 cm scale.Kernel traits were measured using Image-J software and included: horizontal area, vertical area, horizontal perimeter, vertical perimeter, horizontal length, horizontal roundness, horizontal width, vertical thickness, vertical roundness, factor from density, aspect ratio, kernel volume, horizontal deviation from ellipse, and vertical deviation from ellipse.Analysis of variance (ANOVA) showed significant differences among genotypes for all traits.Principal component analysis (PCA) highlighted kernel volume and horizontal area as the most variable traits.Genotype G17 had the highest thousand kernel weight under drought, while G30 and G41 performed best under normal irrigation.Biplot analysis showed that kernel yield per spike, number of spikelets per spike and number of kernels per spike were positively associated with horizontal kernel traits (horizontal area, horizontal length, and horizontal deviation from ellipse).In contrast, thousand kernel weight was positively associated with vertical kernel traits (vertical area, vertical perimeter, vertical thickness, vertical roundness, and vertical deviation from ellipse).In conclusion, digital imaging effectively captures variation in kernel morphology.The identified relationships between kernel traits and yield components can help breeders select drought-tolerant genotypes using both conventional and image-based traits.

Plant phenotyping relevance

小麦種子形態をデジタル画像とImageJで多数の形質として抽出し、干ばつ応答および収量関連形質との関係を評価しており、画像ベースの表現型取得が研究の中心である。

Code and data availability

The article describes digital-imaging phenotyping of 70 wheat genotypes using a DSLR camera and Image-J, but contains no data availability statement, no public phenotype dataset, no deposited kernel images, and no author analysis code or workflow. All URLs in the text are license or reference citations, not paper-asset

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