| Autor: |
Vikram, T. Harish, Haritha, T., Satyanarayana, H. N., Swapna, M., Jayalakshmi, V. |
| Předmět: |
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| Zdroj: |
Electronic Journal of Plant Breeding; Mar2023, Vol. 14 Issue 1, p296-302, 7p |
| Abstrakt: |
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 five 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 identified first 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 sufficient divergence among the genotypes for the traits studied. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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