Journal ID : AMA-03-02-2022-11084
[This article belongs to Volume - 53, Issue - 02]
Total View : 462

Title : Principal component analysis for assessment of genetic diversity in rice under Humid South-Eastern plain of Rajasthan

Abstract :

The present investigation was carried out during Rabi 2019 at Agricultural Research Station, Ummedganj, Kota Rajasthan, India to determine level of variability among twenty five rice genotypes in randomised block design using principal component analysis. First three principal components exhibited more than one Eigen values and accounted for 83.91 percent of total variation. PC1 accounted 49.18 % of the total variability contributed by the traits like number of grains per panicle, 1000-grain weight, grain yield per plant and amylase content, whereas PC2 account 24.39 % of the total variation that was contributed by the traits viz. number of productive tillers per plant, days to 50 % flowering, number of grains per panicle, days to maturity and plant height. PC3 had the contribution from the characters like productive tillers per plant, 1000-grain weight and grain yield per plant. Thus, the results revealed vast genetic variation and the traits contributing for the variation in rice genotypes can be used for various breeding programmes for improvement in yield and quality. Cluster I consisted of 7 cultivars showed maximum mean grain yield. Maximum inter cluster distance was recorded between cluster VI and VII. Cluster I had the highest mean values for grain yield and number of productive tillers per plant. Cluster VI had the highest mean values for 1000-grain weight, 1000-grain weight and Panicle length that had significant positive correlation with grain yield. The cultivars from these clusters with desirable characters may be used as potential donor for future hybridization program to develop high yielders.

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