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Evaluation of a mathematical model of rumen digestion and an in vitro simulation of rumen proteolysis to estimate the rumen-undegraded nitrogen content of feedstuffs

Published online by Cambridge University Press:  24 July 2007

U. Krishnamoorthy ,
C. J. Sniffen ,
M. D. Stern  and
P. J. Van Soest
U. Krishnamoorthy
Affiliation:
Department of Animal Science, Cornell University, Ithaca, NY 14853, USA
C. J. Sniffen
Affiliation:
Department of Animal Science, Cornell University, Ithaca, NY 14853, USA
M. D. Stern
Affiliation:
Department of Dairy Science, University of Wisconsin, Madison, WI 53706, USA
P. J. Van Soest
Affiliation:
Department of Animal Science, Cornell University, Ithaca, NY 14853, USA
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Abstract

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1. Twelve grain mixtures, one lucerne (Medicago sativa) hay and one maize silage which had been used in mixed diets for which dietary nitrogen undegraded in the rumen (UDN) had been estimated with duodenally-cannulated cows, were studied. Total N in the feeds was fractionated into pool A (N soluble in borate–phosphate buffer), pool B (total N–(pool A + pool C)) and pool C (acid-detergent-insoluble N or residual N after 24 h incubation in protease solution).

2. N solubilization in protease solution containing 6·6 units/ml (substrate-saturating enzyme concentration) indicated the presence of subfractions in pool B, with different rates of solubilization. Such subfractions were not detectable from in situ, Dacron bag, estimates of N solubilization.

3. UDN was estimated using a dynamic mathematical model and rate-constants obtained from N solubilization in protease solution or in situ.For three grain mixtures tested using the protease technique the model predicted UDN values of 7, 10 and 12% compared with values of 47, 66 and 59% estimated in vivo. The full range of experimental feeds was tested using the in situtechnique and UDN values predicted by the model were used to derive UDN values for twelve mixed diets. The latter values were significantly but not closely correlated with those determined in vivo (r2 0·41, P < 0·05).

4. An attempt was made to simulate rumen proteolysis in vitro by choosing a protease enzyme concentration (0·066 units/ml) providing a proteolytic activity similar to that of whole rumen fluid. The experimental samples of feed were subjected to simulated rumen proteolysis for 18 or 48 h to resemble the mean retention times in the rumen for grain mixtures and roughages respectively. The residual N at the end of incubation was considered as an estimate of UDN. The UDN values estimated from simulated rumen proteolysis and those determined in vivo for twelve mixed diets were in close agreement (r2 0·61, P < 0·01).

5. Simulated rumen proteolysis can serve as a simple, rapid and sensitive method to estimate UDN in a variety of feedstuffs.

Type
Research Article
Information
British Journal of Nutrition , Volume 50 , Issue 3 , November 1983 , pp. 555 - 568
Copyright
Copyright © The Nutrition Society 1983

References

Blackburn, T. H. (1968). Journal of General Microbiology 53, 37–51.CrossRefGoogle Scholar
Blaxter, K. L., Graham, N. McC. & Wainman, F. W. (1956). British Journal of Nutrition 10, 69–91.CrossRefGoogle Scholar
Broderick, G. A. (1978). Journal of Nutrition 108, 181–190.Google Scholar
Broderick, G. A. & Craig, W. M. (1980). Journal of Nutrition 110, 2381–2389.Google Scholar
Chalmers, M. I. & Synge, R. L. M. (1954). Journal of Agricultural Science, Cambridge 44, 254–262.Google Scholar
Chamberlain, D. G. & Thomas, P. C. (1979). Proceedings of the Nutrition Society 38, 138A.Google Scholar
Charney, J. & Tomarelli, R. M. (1947). Journal of Biological Chemistry 171, 501–505.CrossRefGoogle Scholar
Faichney, G. J. (1975). In Digestion and Metabolism in the Ruminant, pp. 277–291 [McDonald, I. W. and Warner, A. C. I. editors]. Armidale: University of New England.Google Scholar
Goering, H. K. & Van Soest, P. J. (1970). Forage Fiber Analysis (apparatus, reagents, procedures and some applications). Agricultural Handbook no. 379. Agriculture Research Service, USDA.Google Scholar
Hartnell, G. F. & Satter, L. D. (1979). Journal of Animal Science 48, 381–392.CrossRefGoogle Scholar
Hutton, K., Bailey, F. J. & Annison, E. F. (1971). British Journal of Nutrition 25, 165–173.CrossRefGoogle Scholar
Krishnamoorthy, U. (1982). Development of an in vitro technique to estimate rumen escape nitrogen in feedstuffs. PhD Thesis, Cornell University, Ithaca, NY.Google Scholar
Krishnamoorthy, U., Muscato, T. V., Sniffen, C. J. & Van Soest, P. J. (1982). Journal of Dairy Science 65, 217–225.Google Scholar
MacRae, J. C. (1975). In Digestion and Metabolism in the Ruminant, pp. 261–276 [McDonald, I. W. and Warner, A. C. I. editors]. Armidale: University of New England.Google Scholar
Mahadevan, S., Erfle, J. D. & Sauer, F. D. (1979). Journal of Animal Science 48, 947–953.Google Scholar
Mahadevan, S., Erfle, J. D. & Sauer, F. D. (1980). Journal of Animal Science 50, 723–728.CrossRefGoogle Scholar
Mathers, J. C. & Aitchison, E. M. (1981). Journal of Agricultural Science, Cambridge 96, 691–693.CrossRefGoogle Scholar
Matsubara, H. & Feder, J. (1970). In The Enzymes, 3rd ed, vol. III, pp. 721–791. [Boyer, P. D. editor]. New York and London. Academic Press.Google Scholar
Mertens, D. R. (1973). Application of theoretical mathematical models to cell wall digestion and forage intake in ruminants. PhD Thesis, Cornell University, Ithaca, NY.Google Scholar
Nugent, J. H. A. & Mangan, J. L. (1981). British Journal of Nutrition 46, 39–58.CrossRefGoogle Scholar
Ørskov, E. R. & McDonald, I. (1979). Journal of Agricultural Science, Cambridge 92, 499–503.CrossRefGoogle Scholar
Pichard, G. R. (1977). Forage nutritive value. Continuous and batch in vitro rumen fermentations and nitrogen solubility. PhD Thesis, Cornell University, Ithaca, NY.Google Scholar
Pichard, G. R. & Van Soest, P. J. (1977). Proceedings of the Cornell Nutrition Conference for Feed Manufactures, p. 91.Google Scholar
Pierce, W. C. & Haenisch, E. L. (1940). Quantitative Analysis, 2nd ed., p. 123. New York: John Wiley & Sons.Google Scholar
Poos, M., Klopfenstein, T., Britton, R. A. & Olson, D. G. (1980). Journal of Dairy Science 63, (Suppl. 1), 142.Google Scholar
Segel, I. H. (1976). Biochemical Calculations, 2nd ed. New York: John Wiley & Sons.Google Scholar
Smith, L. W., Goering, H. K., Waldo, D. R. & Gordon, C. H. (1971). Journal of Dairy Science 54, 71–76.Google Scholar
Sniffen, C. J., Krishnamoorthy, U., Van Soest, P. J., Muscato, T. V. & Robinson, P. H. (1979). Report on XV Conference on Rumen Function, Chicago, Illinois, pp. 30–31.Google Scholar
Stern, M. D., Rode, L. M., Prange, R. W., Stauffacher, R. H. & Satter, L. D. (1983). Journal of Animal Science 56, 194–205.CrossRefGoogle Scholar
Stern, M. D. & Satter, L. D. (1982). In Protein Requirements for Cattle: Symposium, pp. 57–71 [Owens, F. N. editor]. Oklahoma: Oklahoma State University.Google Scholar
Trop, M. & Birk, Y. (1970). Biochemical Journal 116, 19–25.Google Scholar
Van Soest, P. J., Sniffen, C. J., Mertens, D. R., Fox, D. G., Robinson, P. H. & Krishnamoorthy, U. (1982). In Protein Requirements for Cattle: Symposium, pp. 265–279 [Owens, F. N. editor]. Oklahoma: Oklahoma State University.Google Scholar
Waldo, D. R. & Glenn, B. P. (1982). In Protein Requirements for Cattle: Symposium pp. 296–309 [Owens, F. N. editor]. Oklahoma: Oklahoma State University.Google Scholar
Waldo, D. R. & Smith, L. W. (1972). Journal of Dairy Science 55, 125–129.CrossRefGoogle Scholar
Wang, C. H., Willis, D. L. & Loveland, W. D. (1975). Radiotracer Methodology in the Biological, Environmental and Physical Sciences, 32 pp. New Jersey: Prentice Hall.Google Scholar