A study was undertaken to evaluate the genetic parameters and correlation between the root and shoot traits in 50 upland rice genotypes of Manipur along with 3 checks for drought tolerance. The highest GCV and PCV values were recorded in Root fresh weight with 42% and 41.9% in controlled and 34% and 33.7% in stressed conditions. This was followed by Root dry weight (35.29% & 34.79% and 25.2% & 23.97%) in controlled and stressed conditions, respectively. The estimates of heritability were observed to be high in magnitude for all the characters. Heritability ranged from 80.32 per cent (number of tillers) and 99.7 per cent (root fresh weight) in controlled and 92.36 per cent (number of tillers) and 99.36 (shoot length) in stressed conditions. Correlation reveals highly positive and significant association at 0.01% in both controlled and stressed conditions. The large genetic variation found in this population can be exploited further to develop a few forward breeding high-yielding lines with better drought tolerance ability and used as drought donors in drought breeding programs.
The present experiment was carried out to estimate genetic diversity among 76 rice genotypes of Manipur and 4 checks using principal component analysis for submergence tolerance in the experimental field of College of Agriculture, Central Agricultural University, Imphal, Manipur. Principal component analysis was used to evaluate the variation and for estimation of relative contribution of various characters towards total variability. The results revealed that in submerged condition first four components were with Eigen values greater than one and it accounted for 73.09% of total explained variability. The first principal component (PC1) contributed maximum of 27.73% followed by PC2 with 17.27%, PC3 contributed 15.60% and PC4 had contributed 12.50% towards total variability. The characters viz., filled grains per panicle, spikelet per panicle, grain yield per plant and spikelet fertility percentage explained maximum variance in PC1. Thus, principal component analysis revealed wide genetic variability in the rice genotypes under study.
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