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International Journal of Morphology

On-line version ISSN 0717-9502

Abstract

YAKUBU, A  and  OKUNSEBOR, S. A. Morphometric Differentiation of Two Nigerian Fish Species (Oreochromis niloticus and Lates niloticus) Using Principal Components and Discriminant Analysis. Int. J. Morphol. [online]. 2011, vol.29, n.4, pp.1429-1434. ISSN 0717-9502.  http://dx.doi.org/10.4067/S0717-95022011000400060.

Morphological differences between two close fish populations were investigated in Doma Dam, north central Nigeria using principal component and discriminant analyses. The purpose was to identify the two species correctly and assign them into distinct genetic groups. To achieve this, seven morphometric measurements (body weight, standard length, total length, head length, body depth, dorsal fin length and caudal fin length) were made on each of the studied 252 fish specimens (153 Oreochromis niloticus and 99 Lates niloticus). The analysis of variance showed that significantly (P<0.05) higher values were recorded for Lates niloticus in all the body traits examined, except dorsal fin length. From the principal component analysis, the differences between the species resulted mainly from dorsal fin length, body weight, caudal fin length and head length. The stepwise discriminant analysis revealed that standard length, dorsal fin length and caudal fin length were the three most discriminating variables useful to distinguish clearly the two species at mature age. These three variables with strong discriminating power correctly classified 98.0% of individuals from the sample of known-fish populations. The classification accuracy was cross-validated using split-sample method, and indicated a 97.6% success rate (98.0% of Oreochromis niloticus and 97.0% of Lates niloticus were correctly assigned). The results can provide a sound scientific basis for the effective management and sustainable exploitation of the genetic resources of the two species under subtropical conditions.

Keywords : Fish; Genotypes; Conservation; Morphological traits; Multivariate analysis; Nigeria.

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