Application of Regression Tree Methodology in Predicting the BodyWeight of Uda Sheep

This study aimed at evaluating the relationship between body weight and nine morphometric traits (withers height, rump height, body length, face length, rump length, chest circumference, head width, shoulder width and rump width) of Uda sheep using regression tree technique. The data for the study were generated from 499 Uda rams randomly selected from different herds in Nasarawa State, north-central Nigeria. Pearson’s moment correlation (r) between body weight and morphometric traits ranged from moderate to high values (r = 0.43-0.76; P≤0.01). Based on the importance of the independent variables in predicting the body weight of sheep, five body measurements namely; chest circumference, shoulder width, rump width, body length and face length were found to be more efficient. Thus, they were the variables entered to obtain the optimal regression tree. Among these five variables, chest circumference was found to be the primary splitting variable; and together with face length accounted for about 62% of the variation in body weight. The regression tree analysis indicated that animals with chest circumference > 87.45cm or ≤ 94.05cm and face length > 28.85cm could be expected to have higher body weights. This information could be exploited by livestock producers for management, selection and genetic improvement of Uda sheep.