1Department of Genetics and Plant Breeding, Agricultural College, ANGRAU, Bapatla, Andhra Pradesh-522 101, India
2Agricultural College Farm, ANGRAU, Bapatla, Andhra Pradesh-522 101, India
3RARS, LAM, Guntur, ANGRAU, Andhra Pradesh, 522 034, India
4Biochemistry, Agricultural College, ANGRAU, Bapatla, Andhra Pradesh-522 101, India
5RARS, Nandyal, ANGRAU, Andhra Pradesh, 518 501, India
*E-Mail: harishvikram2908@gmail.com
Online published on 17 April, 2023.
Principal component analysis and hierarchical cluster analysis are the best tools to measure the degree of divergence and to suggest the parents for future crop improvement programmes. A study was done using 64 chickpea genotypes including desi and kabuli types provided from RARS, Nandyal. Research was conducted at Agricultural College Farm, Bapatla during Rabi 2021–22 in 8×8 square lattice design. Data was collected for 13 quantitative traits from fve randomly selected and six biochemical traits were also estimated. Windostat version 9.3 statistical software was used for analysis of the data. Principal component analysis identifed frst six principal components with eigen value more than one and they accounted for 76.54% of cumulative variance. Using ward's method, 64 genotypes were grouped into six clusters. Maximum inter cluster distance was found between cluster IV and cluster V followed by Cluster II and Cluster IV. Maximum intra cluster distance was observed within cluster IV followed by Cluster V. These studies revealed sufcient divergence among the genotypes for the traits studied.
Chickpea, Genetic diversity, Hierarchical cluster, PCA