Knowledge of genotype × environment interactions (GEI) and yield stability is essential for developing new cultivars with improved adaptation to diverse environmental constraints. Soybean (Glycine max (L.) Merrill) is a major source of food, protein, and oil; therefore, enhancing its yield under varying conditions remains an important research priority. In this study, the stability of soybean genotypes for grain yield was evaluated across four regions of Iran in 2019. The effects of environment, genotype, and their interaction on grain yield were all significant. The environment and GEI components contributed the largest proportions to the total sum of squares, highlighting their strong influence on soybean performance and the importance of stability assessment. Consequently, several stability analyses were conducted to identify stable genotypes. A comprehensive set of stability parameters was employed, including environmental variance, coefficient of variability (CVi), Wricke’s ecovalence (Wi), Shukla’s stability variance (σ2i), coefficient of determination (Ri2), Eberhart and Russell’s joint linear regression, Tai’s regression analysis, deviation from regression (S2di), and the α and λ stability parameters in Tai’s model. Based on environmental variance and the methods of Roemer and Francis and Kannenberg, genotypes 16, 19, and 13 were identified as the most stable. According to Shukla’s stability variance (σ2i) and Wi, genotypes 19 and 16 were classified as both high-yielding and stable. Tai’s regression analysis placed genotypes 1, 16, and 19 within the stability zone. Among them, genotypes 16 and 19 were preferred due to their superior yields and were therefore considered stable genotypes. Overall, integrating the results of all stability parameters indicated that genotype 19 was the most stable and is recommended for cultivation across all regions. This study demonstrates the accuracy and effectiveness of multiple stability assessment methods in identifying stable soybean genotypes.
