Identification of Diverse Maize Inbred Lines using Molecular and Phenotypic Genetic Divergence Analysis

Abstract

The experiment was carried out during rabi (September, 2018–January, 2019) season under water deficit experimental fields at Annamalai University, Tamil Nadu, India to evaluate the performance of maize inbreds under water deficient conditions and to identify potential diverse inbreds for hybridization programme. Ten quantitative characters were studied for variability studies, whereas genetic diversity was observed at both molecular and phenotypic levels. The genotype, G₃₄ showed the highest mean for single plant yield (SPY) (135.6 g), this was followed by G₁₁, G₃₂, G₃₈ and G₄₈. While the genotypes G₂₀ and G₅₀ showed early days to 50% tasseling (DT) and silking (<55 days). High heritability and genetic advance as per cent of mean was observed for the traits leaf area, number of kernels cob^-1 and SPY, showing the action of additive gene action. Path analysis showed that SPY had positive direct effects from days to DT, plant height, leaf area, cob length, number of kernels and test weight. Cluster analysis based on Mahalanobis (D²) diversity analysis partitioned the 52 genotypes into 5 clusters, whereas mean Euclidean distance based molecular clustering using the six markers partitioned the selected fourteen genotypes into six clusters. Overall based on both these diversity analyses the genotypes G₃₄, G₂₀, G₁₆, G₄₈, G₅₀, G₄₀ and G₃₄ can be selected and used as parents in future hybridization programme to get superior high yielding hybrids.