An evaluation of Molly cow model predictions of ruminal metabolism and nutrient digestion for dairy and beef diets

Abstract

Model evaluation, as a critical process of model advancement, is necessary to identify adequacy and consistency of model predictions. The objectives of this study were (1) to evaluate the accuracy of Molly cow model predictions of ruminal metabolism and nutrient digestion when simulating dairy and beef cattle diets; and (2) to identify deficiencies in representations of the biology that could be used to direct further model improvements. A total of 229 studies (n = 938 treatments) including dairy and beef cattle data, published from 1972 through 2016, were collected from the literature. Root mean squared errors (RMSE) and concordance correlation coefficients (CCC) were calculated to assess model accuracy and precision. Ruminal pH was very poorly represented in the model with a RMSE of 4.6% and a CCC of 0.0. Although volatile fatty acid concentrations had negligible mean (2.5% of mean squared error) and slope (6.8% of mean squared error) bias, the CCC was 0.28, implying that further modifications with respect to volatile fatty acid production and absorption are required to improve model precision. The RMSE was greater than 50% for ruminal ammonia and blood urea-N concentrations with high proportions of error as slope bias, indicating that mechanisms driving ruminal urea N recycling are not properly simulated in the model. Only slight mean and slope bias were exhibited for ruminal outflow of neutral detergent fiber, starch, lipid, total N, and nonammonia N, and for fecal output of protein, neutral detergent fiber, lipid, and starch, indicating the mechanisms encoded in the model relative to ruminal and total-tract nutrient digestion are properly represented. All variables related to ruminal metabolism and nutrient digestion were more precisely predicted for dairy cattle than for beef cattle. This difference in precision was mostly related to the model's inability to simulate low forage diets included in the beef studies. Overall, ruminal pH was poorly simulated and contributed to problems in ruminal nutrient degradation and volatile fatty acid production predictions. Residual analyses suggested ruminal ammonia concentrations need to be considered in the ruminal pH equation, and therefore the inaccuracies in predicting ruminal urea N recycling must also be addressed. These modifications to model structure will likely improve model performance across a wider array of dietary inputs and cattle type.