Evaluation of ruminal outflow of protein and nitrogen fractions, and total and individual essential amino acid predictions, by nutritional models in dairy cattle

Abstract

The objective was to evaluate the fit statistics for the predictions of ruminal outflow of protein fractions and EAA by the NRC, National Academies of Sciences, Engineering, and Medicine (NASEM), Cornell Net Carbohydrate and Protein System (CNCPS), and NittanyCow (NC) models in lactating dairy cows. Sixty-seven studies published in English between 1984 and 2020 with 251 treatment means were used for analysis. Lactational performance (DMI, DIM, milk yield, milk fat and true protein, and BW data), dietary nutrient composition (CP, NDF, ether extract, and ash), and ruminal outflow of total AA, microbial N, nonammonia nonmicrobial N, and individual EAA determined by omasal or duodenal digesta-sampling techniques were extracted from publications and used in the analysis when available. Production and dietary nutrient composition data reported in the studies were used as inputs to predict ruminal outflows of those same variables using NRC, NASEM, CNCPS, and NC models. For all nutritional models, dietary concentration (% DM) of CP was identical or allowed to vary by 0.5 percentage units maximum to that reported in the studies. Fit statistics and performances of nutritional models were assessed using Lin's concordance correlation coefficient (CCC), root mean squared error (RMSE, g/d and % of observed), as well as mean and linear biases. Models performed similarly when predicting ruminal total AA outflow, with CCC ranging from 49% to 57% and RMSE ranging from 19% to 30% of observed. Predictions of ruminal microbial CP (MicP) and nonammonia nonmicrobial CP (NANMCP) outflows had CCC ranging from 43% to 60% and RMSE ranging from 24% to 34% of observed. Predictions of Lys, Met, and His had CCC ranging from 38% to 62% and RMSE ranging from 23% to 40% observed. Overall, model-fit statistics indicated superior performance of NRC, NASEM, and NC in predicting all individual EAA outflows compared with CNCPS (except for Leu in NC). NittanyCow and NASEM, respectively, demonstrated superior performance in predicting total AA compared with NCR and CNCPS. Additionally, NC was superior to NRC and NASEM, which in turn were superior to CNCPS, in predicting ruminal MicP outflow. Both NRC and NC were superior to NASEM and CNCPS in predicting ruminal NANMCP outflow. The NASEM model was outperformed by NRC, CNCPS, and NC in predicting ruminal nonammonia N outflow. Mean and observed biases of concern (i.e., >5.0% of observed) were identified across all models, and these biases should be considered by nutritionists when balancing and evaluating rations targeting individual EAA in high-producing dairy cows.