Predicting the body weight of crossbred Holstein × Zebu dairy cows using multivariate adaptive regression splines algorithm.

This study aimed to estimate live body weight from body measurements for Holstein × Zebu dairy cows ( = 156) reared under conditions of humid tropics in Mexico using multivariate adaptive regression splines algorithm (MARS) with several train-test proportions. The body measurements included withers height, rump height, hip width, heart girth, body length and diagonal body length. The data were divided into 65:35, 70:30 and 80:20 split data for training and testing sets, respectively.

Predicting body weight through biometric measurements in growing hair sheep using data mining and machine learning algorithms.

Determination of live weight, which is one of the most important features that determine meat production, is a very important issue for herd management and sustainable livestock. In this context, the necessity of finding alternative methods has emerged, especially in rural conditions, due to the difficulties to be experienced in finding the weighing tool. Especially for conditions with no weighing tool, it has been tried to establish relations between the information obtained from body measurements and live weight.

Using Post-Mortem Measurements to Predict Carcass Tissue Composition in Growing Rabbits.

The objective of this study was to determine post-mortem measurements for predicting carcass traits in growing rabbits. A total of 50 clinically healthy New Zealand White × Californian male rabbits with a body weight (BW) of 1351 ± 347 g between 60 to 80 days of age were used. Body weight was recorded 12 h before slaughtering.