T. Ezhilarasi, A. Mahalingam and N. Manivannan
Abstract
Principal component analysis and hierarchical clustering were carried out for 151 Indian sesame germplasm for five quantitative traits, viz., days to fifty percent flowering, days to maturity, plant height (cm), number of capsules per plant and seed yield per plant (g). Among five principal components, PC I and PC II alone recorded above 1 eigenvalue. The first two principal components accounted for 62.45% of cumulative total variations. PC I contributed the maximum variability of 40%, followed by PC II (21.68%) of the total variation. Days to fifty percent flowering and days to maturity had high and negative loading values in PC I. In the case of PC II, plant height had the highest and negative loading value. Among characters, days to flowering and maturity had a positive association with seed yield per plant. Similarly, plant height had a positive association with seed yield per plant. Hence these traits may be considered as selection indices for the improvement of seed yield. Sesame germplasm accessions were grouped into eight distinct clusters using the agglomerative clustering method. The hierarchical cluster analysis indicates that cluster I had the highest genotypic members (58) followed by cluster II (50 genotypes). Cluster IV holds 15 genotypes and Cluster V has 11 genotypes. Clusters III and VI had seven genotypes for each cluster. However, cluster VII holds only one genotype and cluster VIII has two genotypes. In the present study, the level of variability in sesame germplasm was found to be similar in both principal component analysis and hierarchical cluster method.