Estimation of Correlation and Path Coefficient Analysis for Quantitative Characters in Okra (Abelmoschus esculentus L. Moench) Genotypes

Abstract

The purpose of the present study was to evaluate the genetic variability and parameters such as genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability, genetic advance, as well as perform correlation and path analyses on 20 different okra genotypes, including one check variety. The experiment was conducted during the kharif season of 2022 at the experimental farm of the Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences in Prayagraj, Uttar Pradesh. A randomized block design with three replications was employed for the study. Thirteen characteristics were observed and recorded, which includes: days to first flowering, days to 50% flowering, length of mature fruit (cm), diameter of fruit (cm), average fruit weight (gm), internodal length (cm), number of nodes on the main stem, number of primary branches, plant height (cm), number of fruits per plant, number of seeds per fruit, seed index (gm), and fruit yield per plant (gm). Azad Bhindi-1 exhibited the highest mean performance in terms of fruit yield per plant among all the genotypes. The PCV values were consistently higher than the corresponding GCV values for all traits, indicating the influence of environmental factors on trait expression. Fruit yield per plant and number of primary branches displayed the highest GCV and PCV values. The number of primary branches exhibited both high heritability and genetic advance. The correlation analysis revealed a positive and significant association between number of fruits per plant and fruit yield per plant at both the genotypic and phenotypic levels. The traits with the highest positive direct effects on fruit yield per plant were obsereved for average fruit weight and plant height, as determined through genotypic and phenotypic path analysis. These identified traits can serve as effective selection criteria for strategizing an efficient breeding programme to enhance fruit yield in okra.