PREDICTION OF BODY WEIGHT OF NIGERIAN NON-DESCRIPT GOATS FROM MORPHOMETRIC TRAITS USING CLASSIFICATION AND REGRESSION TREE MODEL

Abstract

This study was conducted to evaluate the relationship between body weight and eleven (11) morphometric traits (body weight, body length, height at withers, rump height, chest girth, hind leg, fore leg, head length, ear length, neck length, and tail length) of non-descript goats using classification and regression tree technique. The data were generated from 120 non-descript goats randomly selected from different herds in three LGA areas of Kaduna State, North West Nigeria. Pearson’s moment correlation (r) between body weight and morphometric traits ranged from low to high values (r = 0.21-0.97; P≤0.05, P≤0.01). Based on the importance of the independent variables in predicting the body weight of goats, six body measurements namely; chest girth, body length, rump height, height at withers, head length and neck length were found to be more efficient. Thus, they were the variables entered to obtain the optimal regression tree. Among these six variables, chest circumference was found to be the primary splitting variable; and together with neck length accounted for about 84.20% of the variation in body weight. The regression tree analysis indicated that animals with chest circumference > 60.00cm and neck length >15cm could be expected to have higher body weights. This information could be exploited by livestock producers and researchers for determining the feed amount, drug dose, and market price of an animal, management, selection and genetic improvement of Nigerian non-descript goats.