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Teepu Patel

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Open access Jul 2026

Identification of stable and high-yielding maize genotypes using BLUP-based stability and multi-trait selection indices across diverse environments

Maize (Zea mays L.) is one of the most important cereal crops worldwide and serves as a major source of food, feed, and industrial raw material; however, identification of high-yielding and stable maize genotypes across diverse environments is a key objective of maize improvement programs. A total of 60 maize genotypes were evaluated across four environments [summer 2023 (E1), winter 2023 (E2), summer 2024 (E3), and winter 2024 (E4)] in an alpha lattice design with two replications, comprising six incomplete blocks with 10 entries per block. Subsequently, 15 morphological and yield-related traits were assessed to identify superior and stable maize genotypes across environments. A pooled analysis of variance revealed highly significant effects of genotypes, environments, and genotype × environment interaction for all traits. Broad-sense heritability was high for grain yield (92.40%), biological yield (97.10%), cob yield (92.60%), and plant height (99.20%), whereas anthesis silking interval showed low heritability (12.70%), indicating strong environmental influence. Grain yield exhibited strong positive genotypic correlations with cob yield, biological yield, plant height, kernels per ear, ear length, seed index, and ear diameter. Factor analysis under MGIDI identified three factors explaining 76.06% of total variation, representing yield components, partitioning efficiency, and ear morphology traits. Based on 15% selection intensity, nine genotypes were selected with predicted genetic gains ranging from −0.523% for anthesis–silking interval (indicating a desirable reduction in ASI) to 50.6% for grain yield. The highest coincidence index was observed between MGIDI and FAI-BLUP (66.67%). Genotypes G26 and G27 were consistently selected across all indices, indicating superior performance and stability. These genotypes are promising candidates for multi-location evaluation and can serve as potential parents in hybridization programs aimed at improving grain yield and adaptability in maize.

Dharmendra Kumar, P. Bisen, V. J. Singh et al. · 0 citations