Durum wheat, a vital crop in Mediterranean regions, faces substantial production challenges due to drought stress, necessitating the identification of resilient and high-yielding varieties for sustainable agriculture. This study assessed 26 durum wheat genotypes (22 elite breeding lines and four national checks) across five locations and one limited-irrigation site in Iran during three growing seasons (2021-2024). The additive main effects and multiplicative interaction model (AMMI) and genotype plus genotype-by-environment (GGE) biplot models were applied to analyze genotype × environment (G×E) interactions and identifying high-performing and stable genotypes across variable environments. Using factorial regression model, climatic factors driving G×E interactions for grain yield were identified. Combined ANOVA revealed that genotype, environment, and their interactions significantly contributed to yield variability. Both AMMI and GGE analyses detected pronounced crossover G×E interactions, highlighting differential adaptability among genotypes. The GGE biplot's "which-won-where" function identified breeding lines G17, G24, G14, and G19 as top performers under drought conditions. GGE biplot ranked G24, G17, G22, and G21 as high-yielding and stable genotypes across environments, while AMMI prioritized G17, G19, G14, and G24 for balanced productivity and stability. Both models consistently highlighted elite breeding lines G24 (developed by ICARDA) and G17 (developed by CIMMYT) as optimal choices for adoption by farmers. Test locations in Kermanshah and Ilam exhibited strong discriminatory power over multiple years. Factorial regression attributed 65.7% of G×E interaction variance to March, April, May, and November rainfall, combined with January and April temperatures. These findings provide critical insights for developing climate-resilient durum wheat varieties, supporting sustainable cultivation amid evolving climatic conditions.
Mohammadi et al. (Mon,) studied this question.