EVALUATION OF HIGH YIELDING AND BETTER QUALITY RICE VARIETIES USING PRINCIPAL COMPONENT ANALYSISNeha Sohgaura, D. K. Mishra, G. K. Koutu, S. K. Singh, Vikas Kumar and Pradeep Singh
Improved grain yield and grain quality are two important objectives of rice breeding programmes in developing countries. An investigation was started on 61 rice RILs population derived from a cross between two contrasting cultivars, JNPT 100 (Tropical japonica) and HMT (indica) to dissecting yield and quality related inter-componental traits. Principal component Analysis (PCA) was adopted to obtain precise information and to rank genotypes based on combination of phenotypic traits. On the basis of PCA analysis, only 5 principal components exhibited more than 2 eigen value, showed about 74.17% variability were selected. The C1 showed 23.62% while PC2, PC3, PC4 and PC5 exhibited 17.75%, 14.73%, 10.81% and 7.26% variability respectively among the lines for the traits under study. From the first five PCs it was clear that the PC1 was highly related to quality attributing traits hereas PC3 and PC4 were highly resembled to yield attributing traits. The second PC shared few traits regarding yield and quality thus, a good breeding programme can be initiated by selecting the RILs from these PCs to improve yield and quality traits. Principal component scores suggested that out of 61 RILs under study, RIL 7-47 followed by 7-16, 7-38, 7-35, 7-39, 7- 22, 7-41, 7-31, 7-10 and 7-26 performed well for yield traits whereas RIL 7-18 followed by 7-36, 7-38, 7-19, 7- 17, 7-37, 7-55, 7-13, 7-2 and 7-16 exhibited better performance for quality traits. RIL 7-36, 7-38 and 7-16 were the best for both yield and quality traits and thus can be recommended directly for cultivation programme. However, all these RILs might be utilised for crossing programme to develop superior hybrids governing high yield and quality traits.
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