Salim et al Greener Journal of Agricultural Sciences Vol. 11(2), pp. 70-79, 2021 ISSN: 2276-7770 Copyright ©2021, the copyright of this article is retained by the author(s) https://gjournals.org/GJAS Genetic variation and diversity analysis of rice (Oriza sativa L.) based on quantitative traits for crop improvement Salim Hassan Kafi1; Efisue Andrew Abiodun2*; Olasanmi Bunmi3 and Kang Kyung-Ho4 1 Life and Earth Sciences Institute, (Including Health and Agriculture), Pan African University University of Ibadan, Ibadan, Nigeria. Email: Kafy1158@ gmail. com 2* Department of Crop & Soil Science, University of Port Harcourt, Port Harcourt, Nigeria. Email: andyefisue@ yahoo. com 3 Department of Agronomy, Faculty of Agriculture, University of Ibadan, Ibadan, Nigeria. Email: bunminadeco@ yahoo. com 4 Korea-Africa Food & Agriculture Cooperation Initiative (KAFACI) Republic of Korea. Email: khkang@ korea. kr ARTICLE INFO ABSTRACT Article No.: 050621045 Type: Research The development of varieties is a continuous process and the success of the plant breeding depends upon the selection of suitable plants to be utilized. The effectiveness of selection depends basically upon the magnitude of genetic variability in the breeding material. This study was carried out at Africa Rice Center, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria. Two hundred and thirty-nine (239) lines of anther-culture derived from South Korea with an improved variety from Nigeria as check were established for their genetic variability and diversity analysis. The experiment was conducted using Alpha lattice design with four blocks each planted in 60 entries replicated tow times. The estimation of genotypic coefficient variance and phenotypic coefficient variance was found to be high (>20%) for grain yield, grain yield per plant, biomass, number of tillers, panicle weight, effective tillers, leaf area, leaf area index and number of grains per panicle. The broad sense heritability was highest for days to 50% flowering followed by plant height, 1000 grain weight, panicle length and number of tillers. The estimation of genetic advance was found to be highest for grain yield. Cluster analysis grouped the 240 accessions into four clusters (A, B, C and D), indicate wide genetic diversity among these groups. Principal component analysis showed that the first three components accounted for 64.78% of the total variation. Therefore, indicate the presence of large genetic variability, which is important as it gives wide range of selection. Among all genotypes UPN 632 and UPN 540 showed the best performance. Accepted: 10/05/2021 Published: 27/05/2021 *Corresponding Author Efisue A. Abiodun E-mail: andyefisue@ yahoo.com Keywords: Rice; Genetic; variation; Cluster; Principal component analysis; diversity. Return to Content View [Full Article – PDF] [Full Article – HTML] [Full Article – EPUB] Post-Publication Peer-review Rundown View/get involved, click [Peer-review] REFERENCES Allard, R. W. 1960. Principles of Plant Breeding. John Wiley and Son Inc., New York, USA. 485 Amegan, E., Efisue, A., Akoroda, M., Shittu, A. and Tonegnikes, F. 2020. Genetic Diversity of Korean Rice (Oryza Sativa L.) Germplasm for Yield and Yield Related Traits for Adoption in Rice Farming System in Nigeria. International Journal of Genetics and Genomics 8.1:19–28. https://doi.org/10.11648/j.ijgg.20200801.13 Ananadrao, S. D., Singh, C. M., Suresh, B. G. and Lavanya, G. R. 2011. Evaluation of rice hybrids for yield and yield component characters under North East Plain Zone. The Allahabad farmer. 67.1:63–68. Ariyo, O. 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