Prediction of Body Weight from Body Measurements in Bali Cattle of Indonesia Using Regression Analysis
Prediction of Body Weight from Body Measurements in Bali Cattle of Indonesia Using Regression Analysis
Rosidi Azis1, Gatot Ciptadi2, Sri Wahjuningsih2, Dwi Nur Happy Hariyono3, Yuli Arif Tribudi4, Veronica Margareta Ani Nurgiartiningsih2*
ABSTRACT
Live body weight (BW) is an economically important trait in a production system which helps in the selection of animals for breeding. This study aimed to estimate the relationship between BW and some body measurements (BMs) such as hip height (HH), body length (BL), and chest girth (CG) at weaning, and to detect the best-fitted regression model for the prediction of BW in Bali cattle. Data from 535 (275 males and 260 females; aged six months) of Bali cattle were collected from the Bali Cattle Breeding Center during the period 2018-2020. The Pearson correlation (r) between BW and BMs was determined, and the simple and multiple regression analysis were performed in a Matlab R2021a. The quality of fit of the models was evaluated using the coefficient of determination (R2) and root mean squared error (RMSE). The results showed that BW had a positively high significant correlation (P < 0.01) with HH (r = 0.756), BL (r = 0.754), and CG (r = 0.877). The stepwise regression results showed that the model using three predictors (BW = -159.57+0.44HH+0.69BL+1.38CG) was the best-fitted model (R2 = 0.814; RMSE = 0.834) for the prediction of BW, followed by using BL+CG, HH+CG, CG, HH+BL, HH, and BL. The correlation results imply that BW might be improved by the enhancement of HH, BL, and CG. In conclusion, the BW could be predicted accurately using the combination of HH, BL, and CG. The findings might benefit farmers in Bali cattle breeding through the estimation of BW from BMs.
To share on other social networks, click on any share button. What are these?
