Assessing the stability and adaptability of wheat genotypes in well-watered and rainfed conditions using AMMI, BLUP, GGE biplot and MTSI approaches

This study aimed to analyze genotype × environment interaction (GEI), assess yield stability and adaptability, and identify superior Iranian wheat genotypes using multiple statistical approaches. A total of 266 genotypes, comprising 86 cultivars and 180 landraces, were evaluated under rainfed (S2017-2020) and well-watered (N2016-2020) conditions using a lattice design with two replications. The Additive Main Effects and Multiplicative Interaction (AMMI) model revealed significant effects of genotype, environment, and GEI on grain yield (GY), with the first three principal components accounting for 81.1% of the variation in GEI. Based on AMMI1 and AMMI2 biplots, genotypes 90 (625047), 231 (Moghan3), 153 (627423), 234 (Naz), and 82 (624944) were identified as both stable and high-yielding. The WAASB (Weighted Average of Absolute Scores from the BLUP interaction matrix) analysis further confirmed that genotypes 90 (625047), 204 (Dayhim), 153, 241 (Pishgam), 235 (Neishabour), and 207 (Falat) exhibited the highest stability. These findings were corroborated by GSI-based AMMI and BLUP-based stability parameters. A significant correlation between WAASB and the Multi-Trait Stability Index (MTSI) facilitated the selection of overlapping genotypes: 204 (Dayhim), 138 (627066), 126 (626904), 139 (627072), 107 (626261), 8 (621704), and 58 (624381) as superior and stable performers. The GGE biplot method identified genotype 11 (621908) as the best performer in the main mega-environment, while genotypes 178 (628088), 186 (Alvand), and 45 (623507) excelled in different environments. Additionally, GGE "ideal genotype" analysis highlighted genotypes 90 (625047), 224 (Koohdasht), 108 (626358), 137 (627057), 24 (623136), 194 (BAM), 240 (Parsi), 199 (Chamran2), and 144 (627356) as top performers. Overall, genotypes 90 (625047), 204 (Dayhim), and 153 (627423) were consistently recognized across methods as high-yielding and stable, making them strong candidates for wheat improvement programs aimed at enhancing grain yield stability in diverse Iranian environments.