Analysis of genotype environment interaction and yield stability of elite maize hybrids using integrated parametric and non-parametric biometric approaches
DOI:
https://doi.org/10.68603/15.02.314Keywords:
Maize, Mega-environment, Multi trait stability index, Stability, Yield Introduction Maize (Zea mays L.) is globally significant, serving as a vital source of human food, livestock feed, and industrial raw material. Its global production consistently ranks highest among cereals, reflecting its paramount role in agricultural economies worldwide (Shrestha et al., 2024; Sleper and Pohler, 2024). The relentless pursuit of higher and more consistent yields is fundamental to maize breeding programs, driven by escalating population growth and the pervasive threats of climate change (Ma et al., 2024). Breeding efforts, while successful in increasing the genetic yield potential, face an inherent, complex challenge: the Genotype Environment (G×E) interaction (Van Eeuwijk et al., 2024). This interaction refers to the differential ranking or magnitude of genotypic performance across varying environmental conditions, making the selection of superior, widely-adapted genotypes a probabilistic and intricate process (Eeuwijk et al., 2023; Kambiranda et al., 2024). Therefore, a successful breeding strategy must move beyond simply selecting the highest mean yielding genotype and instead focus on hybrids that exhibit yield stability,Abstract
Maize (Zea mays L.), ubiquitously known as the “Queen of Cereals” due to its exceptional genetic yield potential, stands as a pillar of global food security and the industrial bio-economy. However, achieving consistent genetic gain is inherently challenged by the Genotype Environment (G×E) interaction, which complicates the selection of broadly adapted and stable hybrids for cultivation across diverse agro-climatic zones. Stability and adaptability of thirteen elite maize hybrids were evaluated across six distinct environments which are representative of major Kharif maize growing regions. The combined ANOVA revealed highly significant effects (P < 0.001) for genotype (G) and environment (E), whereas the genotype × environment (G×E) interaction was comparatively small and statistically non-significant (P = 0.36), although multivariate analyses were subsequently used to explore genotype response patterns across environments. Environment Aurangabad (AUR) recorded the highest mean yield (11.66 t/ha), while VRN recorded the lowest (5.42 t/ ha), indicating strong environmental influence. The first two AMMI interaction principal component axes (IPCA1 and IPCA2) together explained 79.2% of the G×E interaction sum of squares. GGE biplot analysis suggested the presence of distinct environmental sectors, indicating differential genotype adaptation across the test locations. Crucially, the multi-trait stability index (MTSI) identified VMAH 236 as the most desirable hybrid, combining high mean grain yield with broad stability, positioning it as a promising candidate for advanced multi-location evaluation and possible commercial release. GAJA 031 and VMAH 322 emerged as the subsequent stability leaders. These findings provide an empirical basis for stratified maize breeding and targeted hybrid deployment in the face of climatic variability.
