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Genetic Diversity Studies in Drought Tolerant Rice (Oryza sativa L.) Genotypes

Background: Assessing the genetic diversity and relationship among breeding materials isan invaluable aid for any crop improvement programme. Principal component analysis (PCA) is a multivariate statistical technique attempt to simplify and analyze the inter relationship among a large set of variables in term of a relatively a small set of variables or components without losing any essential information of original data set.
Methods: The present investigation was carried out to study the genetic diversity and relationship among the sixty five rice genotypes including popular rice varieties of Tamil Nadu, drought tolerant rice varieties, aerobic rice genotypes and land races. These genotypes were raised at Rice Research Station, Tiruvallur, during kharif, 2015 in randomized block design with three replications under aerobic condition. Data on eight yield and yield attributing traits were recorded and subjected to principal component analysis and association analysis. Result: In principal component analysis, PC1accounted for 22.91% and PC2 accounted for 19.53% of the total variation. The traits panicle length, no. of grains per panicle, plant height, days to 50% flowering, no of productive tillers per plant from the first two principal components accounted for major contribution to the total variability. Cluster analysis grouped the genotypes into six discrete clusters. The association analysis revealed that the traits viz., no. of productive tillers/plant, panicle length and hundred seed weight had positive association with higher direct effect on plot yield which could be used as selection criteria for developing high yielding rice varieties. The results of the present study have revealed the high level of genetic variation existing in the genotypes studied and explains the traits contributing for this diversity.
