Genetic Architecture of Fodder Yield in Diverse Yellow Maize Germplasm

Maize (Zea mays L.), one of the most widely grown cereal crops in the world, is an essential ingredient in livestock feeding systems because of its high biomass productivity, palatability, and nutritional value. Thus, increasing fodder yield and biomass production in maize has emerged as a primary goal in crop improvement and breeding programs. This study investigated genetic variability and other aspects of the genetic architecture of fodder yield-related traits in yellow maize germplasm. Seventeen yellow maize germplasm lines were evaluated at the Demonstration Farm Unit-3, Phase-1, Integral University, Lucknow (Uttar Pradesh), India, during the Kharif season of 2025. The experiment was laid out in a randomized complete block design (RCBD) with three replications. 26 observations were recorded, covering phenological and morphological traits, biomass, yield, and quality traits. Data collected were subjected to statistical analysis, analysis of variance (ANOVA), estimation of parameters for genetic variability, heritability, and genetic advance, correlation studies, path coefficient analysis, and cluster analysis. The results of ANOVA analysis showed highly significant differences among maize genotypes for major traits, including plant height, number of leaves, leaf length, fresh stem weight, green fodder yield, dry matter yield (including grain), and harvest index. The heritability was found to be very high (≥ 90), and the genetic advance was also high for traits like green fodder yield, dry matter yield, fresh stem weight, harvest index, and leaf: stem ratio, which indicates the presence of additive gene action and a good scope of selection. Analysis of correlations among biomass traits indicated a significant positive association, particularly between fresh stem weight, green fodder yield, and dry matter yield (r ≈ 0.99); however, those for flowering traits were also high, with days to tasseling highly correlated with days to silking (r = 0.93). However, cluster analysis grouped these genotypes into three major clusters, which suggests high genetic diversity and their potential for effective breeding programs. The study reveals important traits related to biomass that can be used as efficient selection criteria in enhancing forage productivity and developing dual-purpose maize.