Vol. 9, Special Issue 10, Part W (2025)

The present study was conducted at the AICRP on Maize, Maize Improvement Project, Ambikapur (C.G.), during the Rabi 2024 season. The experiment aimed to investigate the genetic variability, correlation and path coefficient analysis of yield attributing traits in twenty-nine maize inbred lines. The experimental layout was a Randomized Complete Block Design (RCBD) with three replications. Analysis of variance revealed highly significant genetic divergence among genotypes for all traits, indicating substantial genetic diversity. Genetic variability analysis demonstrated moderate to high genotypic and phenotypic coefficients of variation, with plant height exhibiting highest genotypic coefficient of variation (17.00%) and heritability (90.53%), alongside greatest genetic advance (33.31%). Initial Plant Population (IPP) showed moderate genetic variability (GCV: 6.85%, PCV: 7.97%) with high heritability (73.81%) and genetic advance (12.13%), indicating effective selection potential. Yield-related traits including grain yield (GY) and 100-kernel weight (KW) demonstrated high heritability (91.27% and 98.32%) with genetic advance (22.31% and 30.55%), confirming suitability for improvement. Correlation analysis revealed grain yield exhibited highest positive correlations with initial plant population (IPP) (r = 0.606**), followed by days to maturity (DM) (r = 0.516**), number of leaves per plant (NLP) (r = 0.379*), ear height (EH) (r = 0.455*) and ear weight (EW) (r = 0.377*) showed significant correlations. Path coefficient analysis identified ear height (EH) with highest positive direct effect (1.268*), followed by number of leaves per plant (NLP) (0.686*) and initial plant population (IPP) (0.500**). These findings provide valuable insights for effective breeding programs, highlighting the complexity of maize breeding and the importance of comprehensive trait selection for genetic optimization.