Genotype × Environment Interaction Analysis for Yield Stability of Hybrid Cotton Across Production Environments Through Multiple Biometrical Tools

Abstract

The expected gains in the productivity and sustainability of cotton cultivars across environmental spectra may face many challenges. To address this issue, a set of 572 cotton accessions, including 284 F1 hybrids along with their parental lines and checks, were evaluated and compared across multiple test environments. Popular biometrical tools viz; best linear unbiased prediction (BLUP), additive main effects and multiplicative interaction (AMMI) and genotype main effects and genotype × environment interaction effects (GGE) were utilized for reliable estimation graphical depiction of GEI effects. The first two interaction coordinates as principal components in BLUP, AMMI, and GGE biplots explained the maximum proportion of GEI regarding seed cotton yield. The contrasting environments did not cluster together, thus revealing their varying influences on the genotypes. A set of 44 F1 hybrids featuring higher stability, 46 with higher adaptability, and 5 F1 hybrids exhibited higher stability, adaptability, and highest seed cotton yield across the investigated environments simultaneously. F1 hybrids of cotton were concluded as more stable and adaptable regarding seed cotton yield across environments. Accordingly, switching from line to hybrid breeding could enable a cotton breeding program to address the broader issue of growing this crop in a wide range of target environments.

Keywords

• lmm
• blup
• ammi
• gge
• adaptability
• gei