A computer model to predict empty body weight in cattle from diet and animal characteristics

A computer model was developed to predict empty BW in cattle as a function of diet (forage NDF, physical form of forage [hay vs silage and pasture], proportion of dietary concentrates) and animal (full BW) characteristics. The model was empty BW = full BW * (1 - GFILL), where GFILL is gut fill expressed as a fraction of full BW. An equation obtained from published data (GFILL = .05354 + .329 * NDF) was used to provide a base prediction of GFILL from the fraction of NDF in the forage. Predicted GFILL was then corrected for full BW, physical form of forage, and fraction of concentrates using multiplicative factors obtained from published data. The model was evaluated with data from 11 published experiments. Several breeds of cattle, a wide range of forage types, and diets with 0 to 93% concentrates were represented in these data. Observed values for empty BW were compared to model-predicted values and to values predicted by systems published by the Agricultural Research Council (ARC) and National Research Council (NRC). Sums of squared deviations of predicted values from observed (n = 64) were 3,074, 37,327, and 25,920 for the model, ARC, and NRC systems, respectively. After fitting predicted empty BW values to observed values, proportion of concentrates and forage NDF accounted for a significant (P less than .01) amount of the residual variation with the ARC and NRC systems, but not for the model. This finding suggests that the model will predict empty BW more accurately than the ARC and NRC systems with diets similar to those used in the evaluation.