Diversity and Multi-variate Analysis of Basmati and Non-Basmati Rice Genotypes over Two Seasons using Organo-leptic Traits

Abstract

Investigation on multi-variate analysis was done with Mahalanobis’ D2 statistic, Principal Component Analysis (PCA), genetic variability studies and Pearson’s correlation coefficient analysis among fifty-one rice genotypes over two consecutive seasons i.e., Kharif 2021 and Rabi 2021. It led to the clustering of the genotypes into ten clusters with maximum intra cluster distance found in cluster III and inter cluster distance between clusters III and X. PCA led to six principal components that had eigen values greater than one, explaining cumulative of 76.77% of the total variation. Based on the per se performance, D2 analysis and PCA, it was found that the genotypes, Improved white ponni, CO 52, VGD 1, BPT 5204, RNR 15048, Pusa Basmati 1121 and Pusa Basmati 1 were highly divergent due to the large genetic distance from the genotypes viz., TRY 3, TPS 5, Palawan, Azucena and Khao do ngoi for both grain yield and organoleptic traits indicating the possibilities for the potential use of these parents in future breeding programme aimed at improvement of grain yield and desirable organoleptic traits . Linear elongation ratio was positively correlated with amylose content, kernel length, L/B ratio and kernel length after elongation but negatively correlated with kernel breadth, kernel breadth after cooking, water uptake ratio and volume expansion ratio and hence indirect selection for longer grains and intermediate to high amylose content would improve LER inspite of the seasonal influence. These traits attribute to the selection of genotypes with desirable cooking quality that fetches premium price in the market in particular to that of non-basmati genotypes.