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Title: NUTRIENT RECOMMENDATIONS FOR SHEEP: GAPS IN INFORMATION AND FUTURE APPROACHES

Author
item Freetly, Harvey

Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract Only
Publication Acceptance Date: 3/31/2001
Publication Date: 7/26/2001
Citation: Freetly, H.C. 2001. Nutrient recommendations for sheep: Gaps in information and future approaches [abstract]. Journal of Animal Science. 79(Suppl. 1):141.

Interpretive Summary:

Technical Abstract: Developing nutrient recommendations is an iterative process that involves taking available information, making a set of recommendations, testing the recommendations, and using the new information to refine the recommendations. The National Research Council last published its recommendations of sheep nutrient requirements in 1985. Given the elapsed time, the question has been raised, do those recommendations need to be refined? Changes in the demographics of the sheep industry have resulted in changes in the types of sheep raised and management used. Recommendations for the growing lamb do not take into consideration 1) decreases in maintenance energy with increased age, 2) the effect of previous nutrition on subsequent performance, 3) breed type differences, or 4) defined amino acid utilization. Recommendations for the ewe do not take into account 1) dynamic changes in body weight, 2) dynamic adjustments for gestation and lactation, 3) large litter sizes, and 4) defined amino acid utilization. Using the existing equations to predict nutrient recommendations for large lambs and ewes results in extending the input data beyond that used to parameterize the equations. Recommendations for mature rams are absent. Since the last recommendations were developed, a sparse amount of research has been conducted that addresses these deficiencies. This paucity of available research suggests that major changes in the system would be difficult to make. The mathematical structure of the system will determine what research needs to be conducted. A consensus on the structure of the next mathematical model will provide guidance to investigators in their experimental designs that will allow them to focus their resources on collecting the information required to parameterize the system.