Genetic diversity assessment of extant cotton varieties based on principal component analysis (pca) and cluster analysis of enlisted dus traits

Morphological characterization of 47 tetraploid cotton varieties cultivated in different zones of India was carried out over two seasons. The lay out followed randomized block Design and evaluation was done using 36 DUS descriptors in two replications. The visual characters showed uniform expression within the variety for two consecutive years indicating that they were uniform and stable in expression. Eleven out of 37 traits were monomorphic among the varieties. The remaining 26 characters were used for Principal Component Analysis to find the contribution of traits towards total variability. The PCA identified a total of 10 Components with Eigen values more than 1 contributing to a cumulative 77.74% variability. The first component (PC1) exhibited maximum variability and highly correlated with traits such as leaf shape and petal spot which are also included in the grouping characters of DUS test guideline. The scatter diagram drawn using first two principle components with highest variability as well as the hierarchical cluster analysis performed using all the ten components distinctly classified genotypes in a consistent manner. The grouping of genotypes was attributed to relatively high contribution from few characters or variables which had high positive loadings, distributed among first two components rather than small contribution from each character.