An evaluation of postabsorptive protein and amino acid metabolism in the lactating dairy cow

Citation
Md. Hanigan et al., An evaluation of postabsorptive protein and amino acid metabolism in the lactating dairy cow, J DAIRY SCI, 81(12), 1998, pp. 3385-3401
Citations number
84
Categorie Soggetti
Food Science/Nutrition
Journal title
JOURNAL OF DAIRY SCIENCE
ISSN journal
00220302 → ACNP
Volume
81
Issue
12
Year of publication
1998
Pages
3385 - 3401
Database
ISI
SICI code
0022-0302(199812)81:12<3385:AEOPPA>2.0.ZU;2-#
Abstract
The current protein system utilized in the US was formulated in 1985 with m inor modifications in 1989 and has gained widespread acceptance. However, s ome of the assumptions that were adopted by the National Research Council ( NRC) appear to be inconsistent with observational data. The marginal effici ency of conversion of absorbed protein to milk protein was assumed by NRC t o be 70% until the requirement for absorbed protein was met and was 0% ther eafter. The mean marginal efficiency observed for abomasal casein infusions reported in the literature and collected at the Purina Mills Research Cent er was 21%. Sorting the data into protein-sufficient and protein-deficient classes did not support the assumptions of 70% marginal efficiency in a def icient state and 0% marginal efficiency in the sufficient state. Analyses o f nitrogen balance data and abomasal flow data and the work of Van Straalen et al. (77) indicated that energy status of the animal plays a role in det ermining the response to absorbed protein. Such a consideration was not inc luded in the NRC model. The adoption of equations that describe metabolism at the organ level as opposed to the animal level would allow direct use of organ level data for parameterization and may provide better predictions. Simple representations of digestion and absorption, splanchnic metabolism, and mammary metabolism of amino acids or protein in aggregate are described . These representations could be used to improve the current system and cou ld serve as a bridge to adoption of more complex models.