Metabolic models of ruminant metabolism: recent improvements and current status

The NC-1009 regional research project has two broad goals of quantifying the properties of feeds and the metabolic interactions among nutrients that influence nutrient availability for milk production and that alter synthesis of milk, and using those quantitative relationships to challenge and refine computer-based nutrition systems for dairy cattle. The objective of this paper was to review progress in modeling. Significant progress has been made in model refinements over the past 10 yr as exemplified by the most recent NRC model (2001) and work on the Molly model of Baldwin and colleagues (1987). These models have different objectives but share many properties. The level of aggregation of the NRC model (2001) does not allow detailed analyses of specific metabolic reactions that affect nutritional efficiency. The Baldwin model is aggregated at the pathway level and is therefore amenable to assessment with a broad range of biological measurements. Recent improvements to that model include the addition of an ingredient based input scheme, use of in situ data to set ruminal protein degradation rates, and refinement of the representation of mammary cell numbers and activity. Although the Baldwin model appears to be appropriate structurally, several parameters are known to be inadequate. Predictions of ruminal N metabolism and total-tract starch digestions have similar accuracy as the NRC model. However, the NRC more accurately predicts total-tract fiber digestion and both models significantly overpredict total-tract lipid digestion. These errors contribute to overpredictions of weight retention when simulating full lactations with the Baldwin model and may result in performance prediction errors with the NRC model. Limitations remain in the descriptions of metabolism and metabolic regulation of the splanchnic, viscera, adipose tissue, body muscle, and mammary tissue. Integration of genetic control mechanisms can expand these efforts to assist genetic selection as well as feeding management decisions.