Genotype × environment interaction and multi-trait stability of cotton lint yield and fiber quality across irrigated and rainfed environments

Cotton, an essential textile fiber, significantly contributes to the global economy. However, its yield and quality vary significantly between irrigated and rainfed cultivation systems. Understanding the genotype (G) × environment (E) interaction (GEI) is critical for predicting cotton yield and quality. This study evaluated the GEI magnitude, patterns, and stability of 16 genotypes across 15 environments (five irrigated and ten rainfed). Multiple statistical models, including the random-effects model, additive main effects and multiplicative interactions (AMMI), genotype plus genotype-vs-environment interaction (GGE), and multi-trait stability index (MTSI), were employed. Results revealed that the environmental variance accounted for the majority of the total phenotypic variance across all traits, with the highest for lint yield (88.5%). Genotypic variance was higher for quality traits than for lint yield. The GEI variance was < 10% for all the traits except for the fiber quality index (Q-score). However, the G: GEI ratio indicated a stronger relative influence of GEI on lint yield than on quality traits. Seasonal weather variables were weakly associated with trait variation across environments, highlighting the need to examine a broader range of agro-ecological factors to identify mega environments. A notable trade-off was observed among the traits for the selection differential. For lint yield, the selection differential, considering both productivity and stability, was greater than that for productivity alone, underscoring the importance of balanced selection for yield and stability in selection programs. Genotypes DG 4530 B3XF and DG 3528 B3XF were identified as the most productive and stable in joint performance across lint yield and fiber quality traits. Our findings suggest that including stability evaluations in multi-trait selection helps breeders and agronomists identify genotypes that are both highly productive and resilient across diverse environments. • Genotypic effects were stronger for fiber quality traits, while GEI had a greater relative influence on lint yield. • Trait-specific adaptation was evident across lint yield and fiber quality among cultivars. • Cultivars exhibited the trade-offs between productivity and stability. • Random-effect, AMMI, GGE, and MTSI models are complementary to characterize GEI and select for productivity and stability.