Unveiling the Genetic Variability and Diversity in Rice Germplasm based on the Phenological Traits and Grain Quality Parameters
Parikh M.
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur-492012 (Chhattisgarh), India.
Kumar D.
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur-492012 (Chhattisgarh), India.
Gauraha D.
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur-492012 (Chhattisgarh), India.
Sharma B.
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur-492012 (Chhattisgarh), India.
Saxena R.R.
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur-492012 (Chhattisgarh), India.
Sahu P.K. *
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur-492012 (Chhattisgarh), India.
*Author to whom correspondence should be addressed.
Abstract
The present study aimed to explore genetic variability and diversity in rice germplasm based on the phenological traits and grain quality parameters. The foundation of crop improvement program lies in genetic diversity and variability which enable breeders to develop superior and desirable varieties. In this study, 50 rice germplasm accessions and seven check varieties (Dagaddesi, RRF 127, RRF 140, IR 64 Drought (DRR42), MTU 1010, Annada and Swarna) were evaluated at Indira Gandhi Krishi Vishwavidyalaya, Raipur, during the Kharif season 2021 by following the randomized complete block design with two replications. This study determine the available genetic variability & genetic diversity based on the 19 qualitative descriptor traits and 17 quantitative traits and to select the promising genotypes for further breeding programs. Analysis of variance revealed significant variation among the genotypes for all the studied quantitative traits. The traits number of effective tillers/ plants, number of filled grains/ panicle, biological yield, harvest index (%), and grain yield/plant have shown higher estimates of PCV, GCV, heritability, and genetic advance, indicating the presence of additive gene action and scope for their direct selection. Further, grain yield exhibited a strong positive correlation with days to 50% flowering, number of effective tillers, biological yield, filled grains per panicle, spikelet fertility percentage, paddy L/B ratio and brown rice L/B ratio, suggesting their importance in yield improvement. In addition, Agglomerative hierarchical cluster analysis grouped all the genotypes into seven clusters with a 63% dissimilarity index, with clusters II, IV, and VI identified as the most divergent and valuable for further hybridization to get promising segregants. The outcomes of the present study provide a strong foundation for developing improved rice cultivars by leveraging promising genotypes and key trait associations, opening new avenues for enhancing rice productivity and sustainability.
Keywords: Rice, germplasm, genetic variability, genetic diversity, cluster analysis