Assessment of genotype by environment and yield performance of tropical maize hybrids using stability statistics and graphical biplots.

Abstract

Background: Enhancing maize grain yield in tropical regions faces significant challenges due to variability in agroclimate, soil conditions, and agroecosystems. Understanding genotype (G) by environment (E) interaction (GEI) in plant breeding is crucial for selecting and developing high-yielding genotypes adapted to diverse environments.

Methods: Ten maize hybrids, including eight candidates and two commercial varieties, were evaluated across ten environments in Indonesia using a randomized complete block design with three replications. The GEI effect and yield stability were assessed using stability statistics, additive main effects and multiplicative interaction model (AMMI), and genotype + genotype × environment (GGE) biplot methods.

Results and discussion: Analysis of variance revealed a significant GEI effect, indicating differences in hybrid responses for grain yield (GY), allowing for stability analysis. G01 showed the highest GY based on the best linear unbiased prediction (BLUP) across environments. Correlation analysis indicated strong associations between stability statistics (YS_i and S^{(6 )}) and GY, aiding in the selection of high-yielding hybrids. The integration of AMMI with the BLUP method, and weighted average of absolute scores (WAASB), enabled precise measurement of genotype stability. Overall, G01 (R0211), G04 (R0105), G05 (R0118), and G07 (R0641) emerged as high-yielding, stable hybrids based on stability statistics, AMMI, GGE biplot, and WAASB rankings. These hybrids offer promising candidates for maize genetic improvement programs in tropical regions.