Determination of Interrelationships and Hierarchical Clustering Analysis among Yield Attributing Biometrical Traits of Okra [Abelmoschus esculentus (L.) Moench] in Coastal Ecosystem

Background: Okra [Abelmoschus esculentus (L.) Moench] is India’s major vegetable crop accounting for 60% of exports. The present study aims the determination and utilization of character association analysis and Wards hierarchical cluster analysis for genetic divergence to identify segregants for genetic improvement in okra. Methods: In the field investigation were carried at Sivapuri Village, Chidambaram, Tamil Nadu, India, in the summer of 2020-2021. The observations for 20 biometrical traits were recorded on five randomly selected plants and recorded data from each replication was subjected to statistical analysis. Result: The improvement in fruit yield plant-1 will be efficient if the selection is based on fruiting period, plant height, No. of branches plant-1, first fruiting node, fruit length, No. of fruits plant-1, No. of marketable fruits plant-1, No. of pickings plant-1 and average fruit weight based on character association analysis. Wards hierarchical cluster analysis grouped the 60 genotypes into 10 clusters and among that cluster IV contains highest number (15) of genotypes followed by cluster VI (13). cluster VIII recorded the highest mean values for all the fruit yield related characters.