Evaluation of desi cotton (Gossypium arboreum L.) germplasm using qualitative descriptors and principal component analysis

Abstract

In the present study, a total of 155 desi cotton accessions (Gossypium arboreum L.) were evaluated using six qualitative traits in an augmented design. The distribution of genotypes categorized under the selected traits and their states were computed for all the genotypes. Principal Component Analysis (PCA) identified three principal components accounting for 56.91% of the variability in the arboreum germplasm with PC 1 contributing 20.51% and PC 2 contributing 18.62%. The results of the eigen vectors of six qualitative traits indicated that the traits namely anther colour, plant body colour and boll shape could serve as distinguishable morphological markers for characterization of G. arboreum genotypes. Correlation studies revealed significant positive association among the traits under study. Scatter plot between PC 1 and PC 2 showed the convex of the hull occupied by the genotypes namely DWDA 1701, NDLA 3086, JLA 0610, CAN 1038, RG5 21, HD 544, PA 778, GAM 261, FDK2 95, K 12 and CIsa 90 presenting their diverse nature among the genotypes. The clustering analysis separated 155 G. arboreum accessions into five major clusters and maximum genotypes were placed in Cluster V. Combined results of PCA and cluster analysis selected DWDA 1701, GAM2 60, TAS 130, CISA 1793 and RG 690 as promising genotypes with highest degree of divergence for future desi cotton breeding research.

Keywords

• desi cotton
• qualitative traits
• principal component analysis
• scatter plot
• cluster analysis