CompoCow: a predictive model to estimate variations in body composition and the energy requirements of cull cows during finishing

International audience

英语. Cull cows account for a large part of beef consumption in France and are a significant proportion of farm income for dairy (0·10) and beef systems (up to 0·30). On-farm observations highlight considerable variations in cull cow phenotypes in terms of age, frame size, health, physiological status and body condition. Consequently, an important issue for producers of cull cows is the management of feed supply during the finishing period to obtain a satisfactory condition score and conformation prior to slaughter. New feeding recommendations for cull cows should consider live weight and live weight gain, age, frame size and body condition score (BCS) to estimate the energy requirements. A predictive model, called CompoCow, was developed for this purpose. The present paper describes the CompoCow model by summarizing developments from previous modelling approaches and outlining the assumptions and equations used in the model. CompoCow combines a growth model for the cow during its productive period (3–8 years old) and a model for the finishing period (in days) and was parameterized for Charolais, Limousine and Holstein breeds. Sensitivity analysis highlighted that the outputs of the model were mainly sensitive to initial body weight and expected body weight gain of the animal. The proportion of lipid in live weight gain was related to body weight, BCS and frame size of the animal. The model also accounts for the higher proportion of lipid in live weight gain in Holstein than in Charolais cows. The model was applied to data from Charolais cows. It showed that the proportion of variability explained by CompoCow for energy requirements was higher than the proportion obtained with previous INRA recommendations, 0·78 and 0·67, respectively. CompoCow does not rely on mechanistic relationships, but it appears robust as it accounts correctly for the effects of age and BCS on the requirements.