Free access | Research Article

Genetic parameters estimation and evaluation of yield and yield attributing traits of rice genotypes under reproductive drought stress condition

Bigyan Khatri Chhetri, Sagar Lamichhane, Pratit Khanal, Subarna Sharma Acharya, Nav Raj Adhikari, Koshraj Upadhyay

Published on: 31 Dec 2022 | DOI: | Volume: 9, Issue: 4 | Pages: 44-56 |

In order to determine the degree of genetic divergence and to assess yield and yield components of rice under reproductive drought stress conditions, a field screening of eleven genotypes was carried out at a farmer's field in Sundarbazar, Lamjung. This was done using a randomized complete block design with three replications. Significant variations between all genotypes for all tested parameters were found by the analysis of variance, indicating the presence of genetic variability as well as the possibility of future improvement through selection. Phenotypic coefficient of variance was higher than genotypic coefficient of variance for all traits under study and difference between them was found low, meaning less influence of environment in the expression of these characters and selection could be effective on the basis of phenotype independent of genotype for the improvement of these traits. Moderate to high estimates of GCV, PCV, heritability and genetic advance as percent of mean was found for all traits studied. Chlorophyll content, leaf area and filled grains per panicle showed positive and significant association with grain yield. Three principal components were extracted based on eigen value accounting 84% of total variation. Eleven rice genotypes were clustered into three groups where cluster 3 was found to be superior for yield and yield attributing traits. Eight genotypes yielded more than that of check variety where highest yield was recorded by Sukhadhan-4. Rice genotypes under study showed enough genetic diversity hence, indirect selection of traits like flag leaf area, filled grains per panicle, harvest index, plant height, SPAD value and thousand grain weights will be effective for increasing yield.