Malaysian Applied Biology Journal

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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


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