Classification of promising okra (Abelmoschus esculentus) genotypes based on principal component analysis

Genetic diversity in 20 okra genotypes was determined using multivariate analysis. various relationships were noticed among the attributes in the correlation studies. positive significant correlations for plant height (ph) with number of branches (nb), days to 50% flowering (df) with days to first harvest (dfh), pod yield per plant (py) with pod yield per plot (pyp), number of pods per plant (np) with py and pyp (p ≤0.001) and for np with ph and nb (p ≤0.01) were found, while pod weight (pw) was negatively correlated with np (p ≤0.001). analysis of the extracted components, component patterns and eigen values revealed that the first two principal components together accounted for 62.83% of the variance. the first component was found to be heavily loaded with pw, pod diameter (pd) and dfh in a positive direction, and np, py, pyp, ph and nb in a negative direction. cluster analysis revealed that the selected genotypes could be grouped clearly into two groups accommodating 18 genotypes. the matrix obtained from this principal component analysis revealed that the genotypes pb-57 and hrb-9-2 were in isolated positions in the third and fourth quadrants in the principal space.