Faith, E.A Principal Component and Correlation Analyses of Body Weight and Biometric Traits of Noiler Chickens
Abstract
This study was designed to evaluate principal components and phenotypic correlations between body weight and biometric traits of Noiler chickens on deep litter system of management. The study was conducted at the Poultry Unit of the Teaching and Research Farm of the Livestock Complex of College of Agriculture, Science and Technology Lafia, Nasarawa State. A total of one hundred and forty (140), six (6) weeks old Noiler chickens comprising of sixty cocks (60) and eighty hens (80) were procured from various brood and sell farmers in Lafia. Traits measured were Body weight (BW), body length (BL), breast circumference (BC), thigh circumference (TC), foot length (FL), total leg length (TLL) and wing length (WL) on bi-weekly basis for two months. Pearson’s correlation coefficient was employed to determine the relationships between body weight and biometric traits. Mean values of all the traits for male Noiler chickens were higher compared to their female counterparts. The value for Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy obtained for the male (0.85), female (0.83) and Bartlett test of Sphericity (0.00) were significant at chi-square of 1362.34 (male) and 1548.17(female). Two principal components PC1 and PC2 were extracted for male and female. PC1 (Eigenvalue male and female = 4.87 and 4.30) accounted for 69.4% and 61.9% and PC2 (Eigenvalue male and female = 0.72 and 1.08) accounted for 10.33% and 15.42% of total variance. In males, foot length (0.87) and body length (0.89) had larger proportion of variance for PC1 and PC2 while in females, thigh circumference (0.90) and body length (0.93) had larger proportion of variance for PC1 and PC2 and these traits could be of importance and useful for selection in genetic improvement programmes. There was positive correlation between body length and thigh circumference (male) and body length and foot length (female). Correlation may be useful as selection criterion because correlated variables are more likely to be governed by the action of the same gene.
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