Genotype x Environment Interaction, and Stability Analysis of Bread Wheat (Triticum aestivum L.) Genotypes Using GGE Biplot Approach across Two Environments

Abstract

Wheat is vital for global food security, but improving stable, high-yielding varieties is challenged by genotype × environment interactions. Statistical tools like ANOVA and GGE biplot analysis help identify stable and widely adapted genotypes across different environments. The present study was conducted to evaluate the performance and stability of twenty-six wheat (Triticum aestivum L.) genotypes across two environmentsusing a randomized block design with three replications. The genotypes were selected from a larger set of 111 entries evaluated earlier. Combined ANOVA revealed significant differences among genotypes for most traits, indicating genetic variability. A significant genotype × environment (G×E) interaction was also observed for major yield-contributing traits, including grain yield per plant (GYP), grains per ear (GPE), and productive tillers (PT), justifying the use of GGE Biplot analysis. GGE Biplot analysis showed different genotype performance across environments. For grain yield per plant (GYP), genotypes G17 (HI8777) and G20 (RAJ4238) showed high mean performance along with better stability across environments, whereas genotypes G1 (HD3226) in Punjab (Environment 1) and G21 (HD3321) in Himachal Pradesh (Environment 2) showed adaptability in individual environments. For grains per ear (GPE), genotype G17 (HI8777) was identified as stable and high performing and G17 is superior performer in environment 1 and G26 (PBW550) in environment 2, for productive tillers (PT) genotype G4 (HS490) exhibited relatively better stability, while genotypes G16 (HI1620) in environment 1 and G10 (HPW360) in environment 2 and protein content showed non-significant G×E interaction and minimum variation across environments, indicating stable expression. Genotype G10 (HPW360) exhibited relatively consistent protein content across both environments.