Multi-trait selection in yellow kernel maize (Zea mays L.) genotypes using multi-trait genotype-ideotype distance index - Sondarava, P M; Patel , M B; Borkhatariya, T H; Parmar, D J; Akbari, K M; Ghetiya, R L (Plant Science Today, 2025)
The production of food crops is greatly influenced by maize, which is essential to global food security. Genetic variation and selection are key components in maize breeding that maximize genetic gain and productivity. The present study, 238 maize genotypes were investigated for fourteen quantitative traits to identify diverse and desirable genotypes for future breeding and varietal development programs. Significant genotypic effects were observed for grain yield and its attributes and other agronomic traits, indicating potential for genotype selection. Multivariate PCA analysis revealed that the first four PCs (70.1 % of total variation) effectively captured the considerable diversity within traits. Key traits such as flowering time, plant height, ear height, ear characteristics, and grain yield were essential in distinguishing between the genotypes analyzed. A recently introduced multi-trait-ideotype distance index (MGIDI) was used to predict the selection gain and identify the effectively performed genotypes by considering multiple traits. The MGIDI predicts significant desired genetic gains across all characteristics. Strengths and weaknesses of selected genotypes based on MGIDI provided insights into their overall suitability and factor contributions. The genotypes G32, G76, G163, G212, and G169 were identified as performing better using the MGIDI method, considering their strengths and weaknesses for the traits analyzed. MGIDI is a powerful tool that can help breeders effectively select the most desirable genotypes in maize.