AMMI and GGE biplot-based evaluation of yield and protein percentage in nutrient-rich rice genotypes across diverse environments

Stable, high-yielding and nutritionally enriched rice genotypes are essential to ensure food and nutritional security under changing climatic conditions. In this study, 12 nutrient-rich rice genotypes, along with standard checks, were evaluated for grain yield and protein content across four diverse and contrasting environments in Chhattisgarh, India, during kharif season of 2024–25, using a randomized complete block design (RCBD) with two replications. Although based on a single year, the use of multiple test sites and robust genotype × environment (G × E) interaction analysis through additive main effects and multiplicative interaction (AMMI) and genotype (G) plus genotype × environment interaction (GE) biplot (GGE biplot) models enabled reliable genotype assessment. Combined analysis of variance (ANOVA) based on the AMMI model revealed significant effects of environmental factors and G × E interactions (GEIs) on both traits. In the GGE model, the first two principal components explained 91.6 % of the variation in yield and 81.5 % of the variation in protein content. The “which-won-where” biplot identified G9 as superior for yield across environments, while G9 and G3 excelled in protein content in E1 and E2 respectively. The most discriminating environment for yield was E3, whereas E1 and E3 were highly discriminating for protein content. The most representative environments were E1 for yield and E4 for protein content. The ideal environments identified were E4 for yield and E2 for protein content. Genotypes G9 and G3 emerged as promising candidates for commercial cultivation. These nutrient-rich lines may also serve as valuable parental material for breeding programs targeting enhanced yield and nutritional quality, contributing to the development and release of biofortified rice varieties.