Principal Component and Cluster Analysis of Fibre Yield in Roselle (Hibiscus sabdariffa L.)

Genetic diversity plays an important role in crop improvement, because the segregants between lines of diverse origin generally display an improved performance than those between closely related parental genotypes. Sixty genotypes of roselle (Hibiscus sabdariffa L.) were evaluated to study genetic divergence of fibre yield contributing quantitative characters by using principal component and cluster analysis. Principal component analysis (PCA) identified four principal components with eigen values more than one which contributed 73.859 percent of cumulative variance. The first principal component (PC₁-) contributed maximum towards variability with significant loading of plant height, fibre length per plant, and fibre yield per plant. The plot of PC₁and PC₂ showed characters differentiation of genotypes according to their cluster membership for each cluster. The mean scores of genotypes were used as input for clustering in order to group the genotypes into various clusters. Hierarchical clustering procedure (complete linkage dendrogram) was followed to group the genotypes into 8 clusters, the clustering pattern of genotypes was to be independent of their eco-geographical origin. The comparative study of PCA and Complete Linkage Dendrogram indicated the similarity in the clustering pattern, resulted to clustering of divergent genotypes into different clusters against the geographical origin. The genotypes REX-1, ER-1, AHS-188, AMV-5, AMV-4, AHS-161, HS-4270, AR-104, JRRM-9-2 and R-83 in the different clusters if inter crossed may generate wider variability for sustainable improvement of fibre yield.