Combining multiple stability and adaptation models to analyze genotype-by-environment interactions for selection of stable barley genotypes with high yield performance

Abstract

Analyzing genotype-by-environment interaction (GEI) is crucial in multi-environment trials before introducing new barley varieties for cultivation under diverse regional conditions. This study evaluated novel barley genotypes across five Iranian locations during the 2022–2024 cropping seasons, assessing traits such as days to heading, maturity, grain-filling period, plant height, 1000-kernel weight, and grain yield. Combined analysis of variance revealed significant effects of genotype (G), environment (E), and GEI. Substantial phenotypic variation was observed across genotypes. The additive main effects and multiplicative interaction (AMMI) model partitioned GEI into six interaction principal component axes (IPCA). Based on IPCA1 scores and mean yield, genotypes G1, G2, G3, and G5 were identified as both high-yielding and stable. The AMMI-based stability metrics and best linear unbiased prediction (BLUP) identified genotypes G14 and G16 as the most stable, with broad adaptability across environments. These findings were reinforced by complementary metrics integrating AMMI and BLUP: weighted average of absolute scores and yield balance, and weighted average of absolute scores and yield scenarios. The genotype plus genotype-by-environment biplot analysis defined three mega-environments in Iran's barley-growing regions—Gonbad (north), Ahvaz, and Darab (south)—highlighting key targets for breeding efforts. Genotype G3 showed strong performance in the northern environment, while G4 was better adapted to southern conditions. Genotypes G14 and G16, due to their consistent performance across sites, are recommended for cultivation under variable or harsh climatic conditions. These insights support targeted selection and breeding of barley varieties adapted to Iran's diverse agroecological zones.