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Bayesian principal component analysis of Nigerian indigenous normal feather chickens' body linear measurements


A.E. Sonubi
A.S. Adenaike
A.A. Dauda
T.P. Alao
B.O. Shonubi
O.A. Iyiola
T. J. Abayomi
C.O.N. Ikeobi

Abstract

The indigenous chicken is a store house of unique genes that  could be used in other parts of the world for improving other  breeds. This study was carried out using bayesian principal component analysis and aimed objectively at determining the effect of sex on Nigerian indigenous normal feather chickens' body dimension, describing their body shape, and predicting their body weights from body measurements using orthogonal  conformation traits derived from the principal components score. The parameters measured at 16 weeks of age were body weight, body length, breast girth, thigh length, shank length, shank diameter, keel length, wing length, wing span, and tail length on 233 randomly selected adult  chickens. Sexual dimorphism was observed in all the traits with higher values recorded for males. Bayesian correlations among body weight and biometric traits were positive (r = 0.09 to 0.651 and 0.017 to 0.579 in male and female chickens respectively). The descriptive statistics showed that the mean body weight was 1.8085 ± 0.263 kg for males and 1.403 ± 0.226 kg for females. The first two principal components (PCs) were extracted for the males, both PCs components account for 72.21%. For the females, three PCs were extracted and they  ccount for 77%. The first PC in each case accounted for the greatest percentage of the total variation. The use of orthogonal body shape characteristics derived from components' scores
was more appropriate than the use of original traits in body weight prediction as multicollinearity problems were eliminated. This led to simultaneous analysis of these body measurements rather than on individual basis. These components could be used as selection criteria for improving body weight of indigenous Nigerian chickens.


Keywords: Body weight, Body dimensions, Chickens, Orthogonal and biometric traits


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eISSN: 0331-2062