Development Of A Dynamic Rumen And Gastro-Intestinal Model In The Cornell Net Carbohydrate And Protein System To Predict The Nutrient Supply And Requirements Of Dairy Cattle
The high value of milk protein, increasing feed costs, and growing concern for the environment has made nitrogen utilization a central component in ration balancing on dairy farms. The Cornell Net Carbohydrate and Protein System (CNCPS) is a nutritional model that enables the formulation of diets that closely match predicted animal requirements. The CNCPS includes a library of approximately 800 different ingredients which provide the platform for describing the chemical composition of the diet. The objectives of this research were 1) to review and update the chemical composition of feeds in the feed library, 2) develop new capability within the model to predict nitrogen and amino acid supply and requirements and, 3) investigate the potential to improve nitrogen utilization in high producing dairy cows through using the new model to formulate diets precisely to animal requirements. The feed library was updated using a procedure that combined linear regression, matrix regression and genetic algorithm optimization to predict uncertain values. Each feed was evaluated and updated where required to be consistent with data from commercial laboratories. Amino acid profiles were also updated using contemporary datasets. A new, dynamic version of the rumen and gastro-intestinal (GIT) submodel was constructed in the system dynamics modeling software Vensim®. The new model included, among other things, estimations of protozoal growth, endogenous N transactions along the entire GIT and a new system to estimate N digestion in the small intestine. Relative to measured data, the model was able to predict the flows of microbial, un-degraded feed, and total non-ammonia N with a high degree of accuracy and precision (R2 = 0.97, 0.90 and 0.98, respectively). Lactating dairy cows fed diets formulated to be adequate in rumen N and EAA supply using the model were able to produce >40 kg milk on diets <15 % CP, utilize N with 38% efficiency and, partition 1.7 times more N to milk than urine. The study demonstrates that high levels of animal performance can be achieved, N utilization can be improved and the environmental impact of dairy production reduced through more precise predictions of N and AA requirements and supply.
Modelling; Dairy; Amino acid
Chase, Larry EugeneVan Amburgh, Michael E
Van Amburgh, Michael E; Ketterings, Quirine M.; Chase, Larry Eugene; Boisclair, Yves R; Roche, John R
Ph.D. of Animal Science
Doctor of Philosophy
dissertation or thesis