Character Association and Path Coefficient Analysis to Determine Interrelationships among Grain Yield and its Components in Maize Genotypes (Zea mays L.)

Abstract

Aim: A study was carried out to evaluate the magnitude of correlation between grain yield and its various contributing characters. Methodology: 39 genotypes of maize, comprising 31 hybrids and 8 parents, were assessed using randomized block design with three replications. The data recorded on twelve quantitative characters including days to 50 percent tasseling, days to 50 percent silking, days to maturity, plant height (cm), ear height (cm), ear length (cm), ear diameter (cm), number of kernel rows per ear, number of kernels per row, 100 kernel weight, shelling percentage and grain yield per plant. Results: The results of this study showed higher genotypic correlation coefficient for all the characters studied compared to the corresponding phenotypic correlation coefficient. This suggests that, despite the strong inherent association between the traits under study, environments’ influence masked its expression. Ear diameter was found to have a strong and significant positive correlation with grain yield per plant at phenotypic (0.9016) and (0.9540) genotypic level followed by ear length (0.8976, 0.9360), number of kernels per row (0.8905, 0.9247), plant height (0.8399, 0.8697), 100 seed weight (0.8070, 0.8544), ear height (0.7170, 0.7550) and number of kernel rows per ear (0.3240, 0.3901). Days to 50% silking and days to 50% tasselling, however, exhibited significant negative association with grain yield, while days to maturity showed non-significant negative. In path coefficient analysis the maximum positive direct effect on grain yield per plant was found by the ear diameter (0.3505), followed by the 100 seed weight (0.2362), ear length (0.2273), number of kernels per row (0.1827), days to 50% silking (0.1269), and shelling percentage (0.1223). Conclusion: The strong correlation of ear diameter, 100 seed weight, ear length and number of kernels per row (0.2971) with grain yield per plant appears to be mostly due to their high direct effects. Therefore, improving yield could be achieved through direct selection for these attributes.