Exploiting genotype × environment interaction for selection of soybean genotypes tolerant to pre-germination anaerobic stress

Abstract Water is essential for crop growth; however, excess moisture during early establishment severely impairs plant survival and productivity. In soybean, flooding at the pre-germination stage can result in substantial stand loss. In this study, 50 soybean genotypes were evaluated for pre-germination anaerobic stress tolerance across four contrasting agro-climatic regions of India (Umiam, New Delhi, Dharwad and Kota) over 2 years, constituting eight environments. Germination percentage under controlled flooding (3–5 cm water for 9 days after sowing) was analyzed using combined ANOVA, AMMI analysis, regression stability parameters (bi and S 2 di), Wricke’s ecovalence, Shukla’s stability variance, AMMI-based stability measures (ASTAB and ASI), and WAASB (weighted average of absolute scores from BLUP-based AMMI) and also confirmed using laboratory-based biophysical trait testing. Variance partitioning revealed that genotypic effects accounted for the largest proportion of phenotypic variation, followed by G × E interaction, whereas main effects of location and year were comparatively small. AMMI and GGE analyses captured most interaction variance within the first two principal components, enabling clear identification of broadly and specifically adapted genotypes. These findings provide a robust framework for identifying stable soybean donors in a balanced multi-environment testing trial for waterlogging-prone environments. Following stability metrics and decision-support visualization (ViTSel), genotype EC471920 exhibited high germination per cent and moderate stability, indicating broad adaptation. Genotype EC472119 was the ideal genotype with reasonably good tolerance and high stability. Genotype EC471972 showed greater environmental responsiveness.