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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.

 

 

 

 

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Cite this Article: Salim HK, Efisue AA, Olasanmi B; Kang K (2021). Genetic variation and diversity analysis of rice (Oriza sativa L.) based on quantitative traits for crop improvement. Greener Journal of Agricultural Sciences 11(2): 70-79.

 

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