This analysis identifies stable soybean genotypes across varied environments, suggesting optimal breeding strategies.
Background: Soybean breeding program face challenges due to genotype-by-environment interaction (GEI), where genotypes exhibit varying performance across different environments, complicating the identification of stable, high-yield cultivars. This study aimed to elucidate GEI’s impact on soybean yield and identify genotypes with superior adaptation and yield stability across diverse environments. Methods: Fifty genotypes were evaluated over three years in a randomized block design with three replications per environment, assessing yield components and other agronomic traits. Stability performance was analyzed using general linear methods, GGE biplot, AMMI analysis and ASV rank analysis. Result: The GGE biplot explained 75.10% of the total variation (PC1: 30.93%, PC2: 44.8%), while the AMMI model’s first two interaction principal component axes (IPCA1: 59.3%, IPCA2: 40.7%) explained the GEI variation. AMMI analysis identified G26 (JS 22-88) and G39 (JS 22-101) as the most stable, high-performing genotypes, whereas GGE biplot analysis identified G9 (JS 22-71).
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Soni et al. (2025) studied this question.
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