Varietal Evaluation and Genetic Variability in Rice (Oryza sativa L.) Genotypes of the Mid-Hill Region of Nepal

Date Received: Mar 28, 2020

Date Published: Nov 27, 2020

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Laxmi, P. J., Subarna, S., Ankur, P., & Bishnu, P. K. (2020). Varietal Evaluation and Genetic Variability in Rice (Oryza sativa L.) Genotypes of the Mid-Hill Region of Nepal. Vietnam Journal of Agricultural Sciences, 3(2), 580–592. https://doi.org/10.31817/vjas.2020.3.2.02

Varietal Evaluation and Genetic Variability in Rice (Oryza sativa L.) Genotypes of the Mid-Hill Region of Nepal

Laxmi Pd. Joshi (*) 1 , Subarna Sharma 1 , Ankur Poudel 1   , Bishnu Pd. Kandel 2

  • Corresponding author: bkandel33@gmail.com
  • 1 Institute of Agriculture and Animal Science, Lamjung Campus, Lamjung 33600, Nepal
  • 2 Institute of Agriculture and Animal Science, Tribhuvan University, Kirtipur 44618, Nepal
  • Keywords

    Cluster analysis, genetic advance, GCV, heritability, PVC

    Abstract


    The objectives of this study were to identify promising rice genotypes and evaluate the genetic variance and effectiveness of selection of the rice varieties for several yield attributing traits. A varietal trial of fifteen rice genotypes was laid out in a randomized complete block design (RCBD) with three replications in a farmer’s field in Sundarbazar, Lamjung, Nepal during the rainy season of 2018. Analysis of variance indicated that all the genotypes showed significant variation for all the traits considered. The phenotypic coefficient of variation (PCV) was higher than the genotypic coefficient of variation (GCV) for all the characteristics being studied indicating the presence of environmental influence on the traits. High heritability coupled with high genetic advance as a percent of the mean was found for days to physiological maturity, number of tillers per m2, plant height, leaf area, effective tillers per m2, flag leaf area, test weight, grains per panicle, filled grains per panicle, harvest index, grain yield, and straw yield indicating that additive gene interaction is present in their inheritance. Direct selection can be effective for yield improvement in the populations through selection of these traits. Cluster analysis based on eighteen traits grouped the fifteen rice genotypes into four clusters. Cluster I was the largest and consisted of five genotypes. Radha 11, NR 119, and Sukhadhan-5 were the top performing genotypes having yield potentials of 5.78, 5.49, and 4.89 tons per ha, respectively.