Salim Et Al

Salim et al

Greener Journal of Agricultural Sciences

Vol. 11(2), pp. 70-79,

ISSN: 2276-7770

Copyright ©2021, the
copyright of this article is retained by the author(s)








Genetic variation
and diversity analysis of rice (Oriza
L.) based on quantitative traits for crop improvement



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.
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

Korea-Africa Food & Agriculture Cooperation
Initiative (KAFACI) Rep
ublic of Korea. Email: khkang@ korea. kr






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@



Genetic; variation; Cluster; Principal component analysis; diversity.









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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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