This analysis reveals the influence of genotype and salicylic acid on biochemical traits in soybean, suggesting tailored agronomic approaches.
This study investigates the complex genotype × treatment × environment (G×T×E) interactions driving soybean seed biochemical trait expression under salicylic acid (SA) application and water stress conditions. Using a comprehensive dataset of 55,450 observations across 13 agronomic and biochemical traits, six soybean genotypes were subjected to factorial combinations of SA (250 mg and 400 mg) and water stress (5%, 70%, and ambient field capacity). Trait responses were quantified via machine learning sensitivity analysis, three-way ANOVA, and structural equation modeling (SEM). Results reveal that genotype exerted the dominant influence across traits, followed by water stress and SA, with several traits chlorophyll concentrations, sugars, and protein contents exhibiting strong three-way interaction effects. Notably, genotypes G3 and G5 showed superior biochemical plasticity and yield stability, while G6 prioritized stress resilience at the expense of productivity. Moderate drought induced beneficial hormetic shifts in biochemical traits, and SA treatments enhanced pigment and protein expression in a genotype-dependent manner. Findings provide mechanistic insight and a scalable framework for genotype-tailored agronomy and biochemical trait optimization in soybeans.
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Fornkwa et al. (2025) studied this question.
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