Title: An assessment of the 1996 Beef NRC: Metabolizable protein supply and demand and effectiveness of model performance prediction of beef females within extensive grazing systems Authors
Submitted to: Journal of Animal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 4, 2013
Publication Date: N/A
Interpretive Summary: Arid and semi-arid regions around the world provide abundant rangeland and other agricultural lands suited to grazing and forage production, favoring ruminant animals which have evolved into the establishment of cow-calf and ewe-lamb production systems which serve as primary sources of high quality animal based protein for consumers. Nutritional composition of rangeland forages in arid and semi-arid regions is highly variable both within and among years, with nutrient quality and quantity often limiting livestock performance. The beef NRC model provides nutritionists, managers, and producers the means to input forage nutrient composition into the model and evaluate animal performance and implement management strategies to accomplish production goals. Within the context of beef cow-calf production systems, the 1996 beef NRC model functions well in situations where physiology or environmental demands are minimal or controlled (static) and is less accurate when physiology or environmental demands are elevated or inconsistent (dynamic). Therefore intent of the present work is to evaluate the 1996 beef NRC in both static and dynamic production environments in regards to MP supply and demand. Our objectives are: 1) to identify areas within the 1996 beef NRC that could be refined so that future beef NRC models would have greater precision predicting protein supply and demand for beef cattle production within extensive grazing systems, and 2) to document both strengths and weaknesses of the model in terms of predicting extensive range beef cow performance within arid and semi-arid environments in the western United States. In addition, this review establishes a need to develop a more robust model for predicting beef cow performance within specific environments to which cows are conditioned. Accomplishment of this goal should lead to improved animal production by informing livestock producers and land managers when strategic, least cost supplements/feeding protocols are needed to achieve economic and environmental production goals.
Technical Abstract: Interannual variation of forage quantity and quality driven by precipitation events influence beef livestock production systems within the Southern and Northern Plains and Pacific West which combined represents 60% (approximately 17.5 million) of total beef cows in the United States. The beef NRC is an important tool and excellent resource for both professionals and producers to use when implementing feeding practices and nutritional programs within these various production systems. Objectives include evaluating the 1996 beef NRC model in terms of effectiveness in predicting extensive range beef cow performance within arid and semi-arid environments in the western United States and identify model inefficiencies that could be refined to improve precision of predicting protein supply and demand. An important addition to the current beef NRC model would be to allow users to provide region specific forage characteristics and also be able to describe supplement composition, amount, and delivery frequency. Beef NRC models would then need to be modified to account for N recycling that occurs throughout a supplementation interval and the impact that this would have on microbial efficiency and microbial protein supply. The beef NRC should also consider the role of ruminal and postruminal supply and demand of specific limiting AA. Additional considerations should include the partitioning effects of nitrogenous compounds under different physiological production stages (e.g., lactation, pregnancy, and during periods of BW loss). Intent of information provided is to aid revision of the beef NRC by providing supporting material for changes and identifying gaps in existing scientific literature where future research is needed to enhance the predictive precision and application of the beef NRC models.