Prediction of body weight of growing dairy buffaloes from body volume.

Abstract

Among body measurements, body weight (BW) is one of the most important within the buffalo production system, due to its association with economic characteristics. In previous research, we have shown that body volume (BV) is an effective predictor of BW in lactating adult water buffalo. As there are no equations to predict BW through BV for growing dairy buffaloes (young animals), we hypothesized that equations should be developed to meet this need. BW, body length (BL) and heart girth (HG) data were collected in 160 growing dairy buffaloes raised in commercial farms in southern Mexico, with body volume (BV) then estimated from BL and HG. The ratio between BV and BW was determined by linear, quadratic and allometric equations. The goodness-of-fit of the regression models was evaluated using the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the coefficient of determination (R²), the mean square error (MSE) and the root MSE (RMSE). After this, the k-folds cross-validation was performed to indicate a better fit. Our results showed that the growing dairy buffaloes presented a BW of 256.6 ± 96.82 kg and a BV of 155.3 ± 74.87 dm3. High and positive correlation were observed among all variables studied. All parameters (R2, MSE, RMSE, AIC and BIC) used to evaluate the regression equations showed that the quadratic regression model was more effective than the linear and allometric models for estimating BW using BV. The criteria for evaluating and validating models showed that the quadratic model presented a better predictive performance. Based on these findings, we conclude that body volume data to estimate body weight of growing dairy buffaloes were best fitted using the quadratic regression model.