Exploring multivariate associations of yield and yield-associated traits in okra (Abelmoschus esculentus (L.) Moench) accessions in the Northwestern Region of India

Abstract

Evaluating genetic diversity simplifies the identification of superior genotypes, facilitating the development of high-yielding, resilient to climatic conditions and promoting effective crop improvement. The present study aimed to examine the divergence, correlation and path analysis across 55 okra (Abelmoschus esculentus (L.) germplasms for 17 traits during the summer season (March- July) of 2022. The experiment utilized randomized complete block design with three replications conducted in Phagwara, Punjab.  Analysis of variance suggested a sufficient amount of genetic variation was found among all genotypes. Using Mahalanobis D2 analysis, the samples were classified into seven clusters, the largest being cluster I, composing 34 germplasm. Only one germplasm was found in Clusters II, IV, V, VI, and VII. The inter-cluster distance was highest between clusters II and VII, whereas the intra-cluster distance was greatest in Cluster III. The number of fruits per plant had the highest percent contribution to the divergence, accounting for 49.63%. At both phenotypic and genotypic levels, there was a strong positive correlation (+) observed between fruit yield and various characteristics, including plant height, fruit length, number of fruits per plant, number of marketable fruits per plant, average fruit weight, and the number of pickings. Genotypic path analysis revealed that characteristics such as the first flowering node, days to first flowering, days to 50% flowering, plant height, inter-nodal length, number of nodes per plant, number of fruits per plant, marketable fruits per plant, and average fruit weight exhibited a positive and direct effect on fruit yield. When selecting this trait to improve yield in okra through breeding, it is essential to focus on specific characteristics that directly contribute to higher production. This research will help resilient okra varieties understand yield-influencing factors in Punjab environmental conditions.