EVALUATION OF DIFFERENT FORMULAS FOR WEIGHT ESTIMATION IN BEETAL, TEDDI AND CROSSBRED (BEETAL X TEDDI) GOATS
M. Moaeen-ud-Din, N. Ahmad, A. Iqbal* and M. Abdullah
Dept. of Livestock Production, University of Veterinary and Animal Sciences Lahore, Pakistan
* Department of Livestock Management, University of Agriculture, Faisalabad, Pakistan
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ABSTRACT
The objectives of the present study were to evaluate the fitness of two different formulas for weight estimation of Beetal, Teddi and Crossbred goats and determination of the best fitted regression equation. Data on body weight and body measurements were collected from Livestock Production Research Institute (LPRI) Bahadar Nagar Okara (100 each Bettal, Teddi and Crossbred animals). The correlation coefficients between body weights body weight and body length + chest girth of Beetal goat were positively and significantly correlated (0.408 and 0.287) while non-significant with body height (0.091). The correlation coefficients for different body measurements ranged between 0.578 to 0.900 and 0.318 to 0.376 for Teddi and Crossbred goats, respectively which were significantly correlated with body weight (P<0.01). Simple and multiple regression models were fitted with body weight as dependant variable and height at withers, chest girth and body length as independent variables. Total variation in body weight accounted by three body measurements in case of Beetal goat was 21.0 percent while 12.4 percent in case of crossbred animals. The model constructed with given data was the best fitted multiple regression model with chest girth, body length and height at wither as independent variables (R2 = 0.210, MSE = 19(18.032). This suggests that weight could be estimated more accurately by combination of two or more measurements. It was concluded that the body weight of Teddi could be estimated with the formulae mentioned in literature but in Crossbreds and Beetal body weight can be estimated with some modifications formulae.
Key words: Body weight, Correlation, Goat breeds, Prediction and Regression |
