Malaysian Applied Biology Journal

  • Increase font size
  • Default font size
  • Decrease font size


E-mail Print PDF
Malays. Appl. Biol. (2007) 36(1): 47–57


NASSIR, A.L.1* and ARIYO, O.J.2

1 Department of Crop Production,College of Agricultural Sciences, Olabisi Onabanjo University, PMB 2002, Ago-Iwoye, Ogun State, NIGERIA.
2 Department of Plant Breeding and Seed Technology, College of Plant Science, University of Agriculture, PMB 2240, Abeokuta, Ogun State, NIGERIA.
*E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it


Thirty rice genotypes from diverse geographical background were cultivated in the early rain season. The data collected were subjected to multivariate analysis to study the variability within the genotypes, and evaluate the efficiency of the methods at classifying entries for plant breeding purposes. The first three axes of factor and principal component analysis (PCA) captured 94% and 33.5% of the total variance among the entries. The two techniques jointly identified grain yield per plant, grain weight per panicle, final plant height and panicle number per plant as the characters contributing most to the variation. The first four axes of the canonical and discriminant analysis summarized 72% and 96% of the total variation and identified in addition to the above characters, leaf scald, leaf blade pubescence, tillering ability, brown rice shape, grain width and maturity as important characters for describing the variation within the genotypes. A joint use of methods was canvassed. Genotypes clustering did not follow a particular pattern. Entries from the same origin were grouped together while some from different origin also separated into different groups.

Key words: Principal component analysis, Factor analysis, Discriminant canonical analysis, Single linkage cluster analysis, Character hybridization


Anon, 1988. Standard evaluation system for rice. IRRI 3rd ed. Philippines 54 pp.

Ariyo, O.J. 1987. Multivariate analysis and the choice of parents for hybridization in okra (Abelmoschus esculentus) (L) (Moench). Theor. Appl. Genet., 74: 361 – 363.

Ariyo, O.J. 1990a. Effectiveness and relative discriminatory abilities of techniques measuring genotype x environment interac- tion and stability in okra (Abelmoschus esculentus (L) Moench) Euphytica, 7: 99 – 105.

Ariyo, O.J. 1990b. Measurement and classifica- tion of genetic diversity in okra (Abelomschus esculentus). Ann Appl. Biol., 116: 335– 341.

Ariyo, O.J. 1992. Factor analysis of vegetative and yield traits in okra (Hibiscus esculentus). Indian J. Agric. Sci., 60(12): 793 – 795.

Ariyo, O.J. 1993. Genetic diversity diversity in West African okra (Abelmoschus caillei) (L.) (Chev.) Stevels – Multivariate analysis of morphological and agronomic characteristics. Genetic Res. & Crop Evol., 40: 25 – 32.

Ariyo, O.J. and Odulaja, A. 1991. Numerical analysis of variation among accessions of okra (Abelmoschus esculentus (L.) Moench). Ann, of Botany, 67: 527-531

Bartual, R., Carbonell, E.A. and Green, D.E. 1985. Multivatariate analysis of a collection of soybean cultivars for southeastean Spain. Euphytica, 34: 113 –123.

Berdahl, J.D. Mayland, H.F, Asay, K.H. and Jefferson, P.G. 1999. Variation in agronomic and morphological traits among Russian wildrye accessions. Crop Sci., 39: 1890 – 1895.

Brown, J.S. 1985. Pathogenic variation among isolates of Rhynchosporium secalis from cultivated barley growing in Victoria, Australia. Euphytica 34: 129 – 133.

Cardi, T. 1998. Multivariate analysis of variation among Solanum commersonii (+) S. tuberosum somatic hybrids with different ploidy levels. Euphytica, 99: 35-41.

Cartel, R.B. 1965. Factor analysis: An intro- duction to essential I. The purpose of underlying models. Biometrics, 21: 190 – 235.

Courtois, B., Sinha, P.K., Prasad, K. and Carandang, S. 1997. Genetic diversity among upland rice varieties from India and Bangla- desh.Int. Rice Res. Notes, 22 (3): 8-9.

Daoyu, Z. and Lawes, G.S. 2000. Manova and discriminant analysis of phenotypic data as a guide for parent selection in kiwifruit (Actinidia deliciosa) breeding.Euphytica, 114: 51-157.

Flores, F., Gutrerrez, J.C., Lopez, J., Moreno, M.T. and Cubero, J.I. 1997. Multivariate analysis approach to evaluate a germplasm collection of Heydsarum coronarium L. Genet. Res. & Crop Evolut., 44: 545-555.

Gravois, K.A. and McNew, R. 1993. Genetic relationships among and selection for rice yield and yield components. Crop Sci., 33: 249-252.

Harman, H.H. 1967. Modern factor analysis. 2nd ed. University of Chicago press. Chicago.

Hedge, S.G. and Patil, C.S. 2000. Genetic divergence in rainfed rice. Karnataka J. of Agric. Sci., 13(3) 549-553.

Kato, T. 1997. Selection responses for the characters related to yield sink capacity of rice. Crop Sci., 37: 1472-1475.

Kato, T. and Takeda, K. 1996. Associations among characters related to yield sink capacity in space-planted rice. Crop. Sci., 36: 1135-1139.

Maguire, T.L. and Sedgley, M. 1996. Genetic diversity in Banksia and Dryandra (Protea- cese) with emphasis on Banksia cueata, a rare and endangered species. Heredity, 79: 394-401.

Nair, N.V., Balakrishnan, R. and Screenivasan, T.V. 1998. Variability for quantitative traits in exotic hybrid germplasm of sugarcane. Genet. Res. & Crop Evol., 45: 459-464.

Ojo, A.A. and Vange, T. 1997. Variability and heritability estimates of yield and yield components in some Nigerian lowland rice genotypes. IRRN/IRRI. 6p.

Padmavathi, N., Mahadevappa, M. and Reddy, O.U.K. 1996. Association of various yield components in rice. Oryza sativa L. Crop Res., 12(3): 353-357.

Ram, J. and Panwar, D.V.S. 1970. Intraspecific divergence in rice. The Ind. J. Genet.& Plant Breed., 30 (1): 1-10.

Rao, S.A., Khan, M.A., McNilly, T. and Khan, A.A. 1997. Cause and effect relations of yield and yield components in rice (Oryza Sativa L.) J. Genet. and Breed 51: 1-5.

Redona, E.D. and MacKilL, D.J. 1996. Genetic variation for seedling vigor traits in rice. Crop Sci., 36: 285-290.

Rezai, A. and Frey, K.J. 1990. Multivariate analysis of variation among wild oat accessions-seed traits. Euphytica 49: 111-119.

SAS Institute. 2000. SAS/STAT Software Release. Cary, NC, USA. SAS Institute Inc.

Sneath, P.H.A. and Sokal, R. 1973. Numerical taxonomy. W.H. Freeman. San Francisco. 537 pp.

Latest MABJ Issue

Vol 49(2) July 2020


Table of content

Latest news!

Malaysian Applied Biology is listed in the databases and indexed in Thomson Reuters Master Journal List, Elsevier, Mycite, Biosis, Zoological Records, UDLedge Life Science Index, CNKI, J-Gate and CABI.

Malaysian Applied Biology is indexed in Scopus since issue 41(1) 2012.

According to MyCite 2014 report, MABJ ranked 95 out of 142 Malaysian journals in terms of yearly impact factor.