What question did this study set out to answer?

The study aims to evaluate barley genotypes for high yield and stability across various environmental conditions.

June 1, 2026BMC Plant Biology0 citationsOpen Access

Integrating AMMI, Bayesian-AMMI, BLUP, and GGE biplot models to improve the identification of high-yielding and stable barley genotypes

APAlireza Pour‐AboughadarehAgricultural Research & Education Organization HZHassan ZaliAgricultural Research & Education Organization AGAhmad GholipourAgricultural Research & Education Organization

Key Points

The study aims to evaluate barley genotypes for high yield and stability across various environmental conditions.
Conducted multi-environment trials at five sites in Iran from 2023 to 2025.
Utilized AMMI, Bayesian-AMMI, BLUP, and GGE biplot models for data analysis.
Evaluated genotypes based on multi-trait stability index (MTSI) and other stability parameters.
Genotype G4 demonstrated the highest multi-trait stability index (MTSI) score of 1.914, indicating excellent performance.
Genotype G4 exhibited strong yield response and stability across environments, outperforming others in tests.
Validation using stability Mahalanobis distance confirmed G4's superior stability and environmental responsiveness.

Abstract

The evaluation of genotype-by-environment interaction (GEI) through multi-environment trials (METs) is an essential prerequisite in breeding improvement programs targeting wide adaptation. In this study, a panel of newly developed barley genotypes was examined under field conditions at five experimental sites across Iran’s warm climatic zone during the 2023–2025 growing seasons. The pooled analysis of variance clearly demonstrated that effects of genotype (G), environment (E), and GEI influenced all measured traits, including the number of days to heading (DH), days to physiological maturity (DM), grain filling period (GFP), plant height (PH), 1000-kernel weight (TKW), and grain yield (GY). Analytical outputs obtained from the additive main effects and multiplicative interaction (AMMI) model, as well as the best linear unbiased prediction (BLUP) approach, highlighted the substantial contribution of genotype × environment interaction to variation in grain yield. Insights from genotype–trait (GT) biplot analysis indicated that TKW and GFP were positively associated with GY. When genotypes were ranked using the multi-trait stability index (MTSI), G5 (1.689), G4 (1.914), G20 (2.380), and G14 (2.508) achieved the highest scores, reflecting superior performance and stability across test environments. A comprehensive evaluation strategy integrating classical AMMI, BLUP, Bayesian AMMI, and genotype-by-environment (GGE) biplot methodologies was employed to identify genotypes that combine productivity with stability. Across all derived stability parameters, including the weighted average of absolute scores (WAAS) and its yield-weighted counterpart (WAASY), genotype G4, derived from the pedigree Sahra/3/Bda/Rhn-03//ICB-107766, consistently outperformed other candidates. This genotype exhibited a robust yield response, high stability, and broad environmental responsiveness. Independent validation using the stability Mahalanobis distance (SM) index and Y × WAASY biplot visualization further substantiated these findings. In conclusion, genotype G4 represents a strong candidate for subsequent validation trials and potential varietal release in the warm agroecological regions of Iran and other areas with comparable climatic conditions.

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