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International Journal of Poultry Science
  Year: 2018 | Volume: 17 | Issue: 11 | Page No.: 560-567
DOI: 10.3923/ijps.2018.560.567
Morphological Characterization of Nigerian Chicken Genotypes Using Multivariate Analyses
A.A. Musa, S.E. Abdulmalik, A.J. Shoyombo, O.M. Akinsola and T. Usman

Abstract:
Background and Objective: Nigerian indigenous chickens play a vital role in food security. This study aimed to determine the relationship between morphometric traits, predict body weight and classify three Nigerian indigenous chicken genotypes using multivariate analyses. Methodology: Data were obtained from a total of 808 randomly selected, matured and extensively reared Nigerian indigenous chickens, comprised of 490 normal feathered (NF), 170 frizzle feathered (FF) and 148 naked neck (NN) genotypes. Results: The phenotypic correlation between the morphometric traits ranged from 0.08-0.74, -0.11-0.76 and 0.03-0.77 for NF, FF and NN, respectively, with breast girth and tibia length being the most correlated to body weight. Three principal components from the factor analysis of morphometric traits explained about 75-84% of the total variance across genotypes. Regression models using original morphometric traits as predictors explained 44-65% of the variation in body weight across the genotypes, while orthogonal traits explained 29-62%. The discriminant analysis revealed some intermingling between the NF and NN genotypes, while NF and FF were almost distinct. Conclusion: We concluded that some morphometric traits could serve as markers for body weight but are genotype specific. The intermingling between NF and NN suggests that there is unrestricted gene flow and intermingling between NF and NN, which may pose a threat regarding genetic conservation.
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How to cite this article:

A.A. Musa, S.E. Abdulmalik, A.J. Shoyombo, O.M. Akinsola and T. Usman, 2018. Morphological Characterization of Nigerian Chicken Genotypes Using Multivariate Analyses. International Journal of Poultry Science, 17: 560-567.

DOI: 10.3923/ijps.2018.560.567

URL: https://scialert.net/abstract/?doi=ijps.2018.560.567

 
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