Genetic variability, divergence, correlation and path analysis in okra (Abelmoschus esculentus) for yield improvement

Abstract

Genetic variability and trait association analyses are crucial for effective parent selection in okra (Abelmoschus esculentus (L.) Moench)  breeding programs. However, the lack of integrated information on variability, divergence and yield-related traits often limits precision in breeding decisions. To address this, the present study evaluated 25 okra genotypes along with Punjab-8 as a standard check during 2022 and 2023 using a Randomized Complete Block Design. Data on growth, yield, and quality traits were recorded and pooled analyses were conducted to estimate variability, correlations, path coefficients, principal component analysis and genetic divergence. Substantial variability was observed among genotypes for most traits. The genotype COHF N-2 was notable for early flowering, taller plants, and superior fruit weight and yield/plant. High phenotypic and genotypic coefficients of variation were recorded for mucilage content, first flowering node and fruit yield/plant. Most traits exhibited high heritability, suggesting that phenotypic selection would be effective. Correlation analysis indicated that pod number/plant and pod weight were positively associated with yield, while path coefficient analysis revealed a strong direct effect of seeds/pod on yield. Genetic divergence grouped the genotypes into four distinct clusters. The diverse and superior genotypes identified in this study can be effectively utilised in breeding programs aimed at yield improvement in okra.