PATH COEFFICIENT ANALYSIS OF BODYWEIGHT AND MORPHOLOGICAL TRAITS OF NIGERIAN INDIGENOUS CHICKENS

In this study, body weight and eight biometric traits namely, comb height, comb length, beak length, body length, neck length, shank length, chest circumference and thigh circumference of 238 adult Nigerian autochthonous chickens were subjected to multivariate analysis. The birds reared under the traditional scavenging system, were randomly selected in Nasarawa State, north central Nigeria. The investigation aimed at determining the explanatory variables that most effectively influenced the body weight of indigenous chickens of both sexes using path coefficient technique. Sex-associated differences (P<0.05) were observed in all the studied traits, with superior values recorded for males. Phenotypic correlations between body weight and body dimensions in cocks ranged from 0.55-0.97. Correspondingly, a range of 0.46-0.85 was obtained in hens. The path analysis revealed that thigh circumference had the strongest direct effect on body weight of male chickens, followed by comb height and body length (path coefficient = 0.681, 0.325 and 0.193 respectively). However, the direct effects of comb length, beak length, shank length and chest circumference on body weight were non-significant. A different trend was observed in females, where the influence of comb height on body weight was greatest, followed by thigh circumference, body length, chest circumference and shank length (path coefficient = 0.289, 0.277, 0.249, 0.246 and 0.180 respectively). Comb length, beak length and neck length did not significantly influence body weight. The optimum linear model in males included forecast indices such as thigh circumference, comb height and body length, with a determination coefficient (R2) of 0.952 and determination coefficient of error of 0.048. The corresponding indices in female birds were, comb height, thigh circumference, body length, chest circumference, and shank length, with R2 value of 0.820 and determination coefficient of error of 0.180. These models could be useful in weight estimation in the field and for selection purposes.