Swotting up on Genetic Divergence of Cucumber (Cucumis sativus L.)

Evaluation of 19 diverse genotypes of cucumber was carried out in a randomized block design for studying genetic divergence. Presence of wide genetic diversity, among the 19 genotypes studied was confirmed by using the powerful tool of Mahalanobis D2 statistic. Based on the interactions in genetic distances 19 genotypes of cucumber got grouped into five separate clusters inferring that the genetic divergence between them was quite plentiful. The mode of distribution of genotypes into various clusters, from different eco-geographical regions viz. Purvanchal and Bihar, was at random indicating that geographical distribution and genetic diversity were not related and geographical distribution of the cultivars did not significantly contribute to genetic divergence. A random pattern of distribution of genotypes into five clusters was observed from different geographical locations, also demonstrating that geographical isolation may not be the only factor causing genetic diversity. Lack of parallelism between genetic diversity and geographical distance stipulates that forces other than geographical origins, such as spontaneous variation, natural and artificial selection, exchange of genetic stocks and genetic drift are liable for genetic diversity. Among the five clusters, the maximum number of genotypes was found in cluster II, this implies that it contributed maximum to the genetic divergence. Cluster IV and Cluster V was found to be mono genotypic. Such random clustering pattern will help in broadening the existing genetic base and may produce novel genotypes with seamlessly unknown combinations. The highest intra-cluster distance was observed for cluster III (737.77) and the lowest for cluster IV and V (0.00). The maximum distance at inter-cluster level was observed between cluster III and V (3598.79) which may serve as a potential genotype for hybridization programme. Among the five clusters, cluster II, cluster IV and cluster V had high mean value for many characters studied. The exploitation of intercrossing the genotype of these clusters may result in an enlargement of a spectrum of variability facilitating the selection for profitable yield. Ranking D2 value revealed that contribution of average fruit weight was highest towards genetic divergence (47.37 %) followed by test weight (39.18 %), fruit length (5.85 %), fruit yield in kg/plant (2.34 %) and number of fruits per plant (1.75 %). Hence, these characters could be exploited for further improvement by phenotypic selection.