A simulation model to predict body weight gain in lambs fed high-grain diets

- A simulation model was developed to predict the average daily gain in lambs fed high-grain diets.
- The model is simple because predicts gain based on digestibility, crude protein, NDF, and body weight.
- The results with this model are similar to those obtained with other published models.
- The gain can be predicted in finishing lambs with an acceptable accuracy and precision according to the developed model.

A simulation model was developed to predict the average daily gain (ADG) in lambs fed high-grain diets. The model is deterministic and is based on the energy intake estimated from the digestibility of the ration as well as based on the California Net Energy System. The model was evaluated using data from eight experiments (28 treatments), with diets containing 50-72% grain. The ADG estimated with the model (244 ± 44 g/d) was similar to the observed ADG (249 ± 44 g/d; t test, P = 0.70). The model was described by the following equation: Y = 40.96 + 0.85X (r2 = 0.74; P < 0.001), with an ADG residual value of −4.6 ± 23 g. A statistical evaluation indicated a mean bias value of 4.6, a root mean square error of prediction of 23, and a concordance correlation coefficient of 0.86. The results indicate that the gain can be predicted in finishing lambs with an acceptable accuracy and precision according to the developed model, with an underestimation of 1.85%.