Genetic Diversity Studies in 29 Accessions of Okra (Abelmoschus spp L.) Using 13 Quantitative Traits
HM Amoatey, GYP Klu, EK Quartey, HA Doku, FL Sossah, MM Segbefia, JK Ahiakpa
Journal of Experimental Agriculture International · pp. 217–225 · Published 4 Oct 2014
10.9734/AJEA/2015/12306Abstract
Aims: Twenty nine (29) local and exotic lines (accessions), of okra (Abelmoschus spp L.) were evaluated for variation in phenotypic traits. Study Design: They were laid out in a Randomised Complete Block Design (RCBD) with four replications and evaluated based on 13 quantitative characters. Place and Duration of Study: Research farm of the Biotechnology and Nuclear Agriculture Research Institute (BNARI), Ghana Atomic Energy Commission (GAEC), Department of Nuclear Agriculture and Radiation Processing, Graduate School of Nuclear and Allied Sciences, University of Ghana, between June 2011 and July 2012. Methodology: The accessions were grown in the field, each on a subplot measuring 3.5 m x 2.5 m, with seeds sown at a spacing of 0.70 m x 0.50 m. Data were collected using the International Plant Genetic Resources Institute (IPGRI) Descriptor List for okra. Results: The accessions exhibited significant variation in all quantitative traits studied. Block coefficients of variation were extremely low, implying that results obtained are reliable and repeatable over replications. Cluster analysis based on Canberra, Furthest Neighbour Similarity Matrix grouped the accessions into two major clusters and subsequently into four sub-clusters, with no duplications, based on the characters studied. Seven pairs of quantitative traits were positive and significantly correlated (P ≤ 0.05) while three were highly significantly associated (P ≤ 0.01). The highest correlation (r = 0.95) was between number of days to 50% flowering (NDFl) and number of days to 50% fruiting (NDFr). Conclusion: The pattern of clustering showed some degree of association between quantitative characters and geographic origin of the collections. Five Principal Components (PCs) accounted for 78.51% of the total variance, with PC1 recording 32.44%. Different traits contributed differently to total genetic variance.
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