Background: Okra [Abelmoschus esculentus (L). Moench] is one of the indigenous genetic resources of western Ethiopia. However, only a few studies were carried out to assess its genetic diversity and performance throughout the country, and specifically, no research was conducted to assess the diversity of okra genotypes from/within a regional state. Therefore, this study was conducted to determine the genetic divergence of 36 okra genotypes of which 33 okra genotypes were collected from different areas of Benishangul Gumuz Regional State, 3(three) checks, of 2 introduced and 1(one) released varieties were evaluated for 24 quantitative traits at MARC in 2018/19 using simple lattice design (6 x 6) that will mainly use as input in improvement.
Results: The results from the study revealed that four principal components (PC1 to PC4) with eigenvalues ranged from 1.83 to 7.58 which accounted for a total of 71.34% cumulative contributions of which the PC1 and PC2 had a larger contribution of 31.591 and 18.397%, respectively, while PC3 and PC4 contributed 13.754 and 7.596%, respectively. The genetic distance of genotypes ranged from 2.83 to 12.24 with mean, standard deviation, and coefficient of variation 6.73, 1.63, and 24.18(%), respectively. All the 36 genotypes were grouped in 13 distinct clusters consisting of 11 (30.56%) in cluster I to seven clusters in which genotypes are solitarily clustered. Among clusters, cluster VII had the highest fruit yield by leading the other seven clusters greater than overall cluster means.
Conclusions: Itâ€™s concluded that, the results observed in this study was the presence of a wide genetic variation and the possibility of improving fruit yield through selection of genotypes having higher yield and/or crossing between distant clusters for improving of fruit yield among genotypes collected from Benishangul Gumuz Regional State.
Keywords: Clustering Analysis, Genetic Distance, Genetic Divergence, Principal Component