A meta-analysis to evaluate the accuracy of the Cornell Net Carbohydrate and Protein System model for prediction of energy and protein variables from dairy cow calorimetry studies

摘要

The accurate prediction of metabolisable energy balance (ME) and metabolisable protein balance (MP) in dairy cattle rations using ration modelling programs supports animal health, productivity and environmental management. The purpose of this study was to investigate the accuracy of the Cornell Net Carbohydrate and Protein System (CNCPS) version 6.55 ration modelling program using the AMTS platform for prediction of net energy (NE) and MP balances from respiration calorimetry (RC) in individual lactating Holstein cows from the Beltsville Agricultural Research Centre. As these predictions are normally based on averages of cow groups, this gave a unique opportunity to assess the accuracy of these parameters with individual cow data. Further, reducingdietary protein can reduce nitrogen-losses in manure and urine and increase nitrogen (N) utilization (Colmenero and Broderick, 2006). Thus, accurate predictions using ration models to balance ME and MP will advance animal health and productivity and economic and environmental sustainability.