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Simplified estimation of forage degradability in the rumen assuming zero-order degradation kinetics

Published online by Cambridge University Press:  08 December 2008

M. S. DHANOA
Affiliation:
Institute of Grassland and Environmental Research (IGER)†, Plas Gogerddan, Aberystwyth, Ceredigion, SY23 3EB, UK
S. LÓPEZ*
Affiliation:
Instituto de Ganadería de Montaña (IGM), Universidad de León – Consejo Superior de Investigaciones Científicas (CSIC), Departamento de Producción Animal, Universidad de León, E-24071 León, Spain
R. SANDERSON
Affiliation:
Institute of Grassland and Environmental Research (IGER)†, Plas Gogerddan, Aberystwyth, Ceredigion, SY23 3EB, UK
J. FRANCE
Affiliation:
Centre for Nutrition Modelling, Department of Animal and Poultry Science, University of Guelph, Guelph, ON, N1G 2W1, Canada
*
*To whom all correspondence should be addressed. Email: s.lopez@unileon.es

Summary

In the present paper, a simplified procedure using few in situ data points is derived and then evaluated (using a large database) against reference values estimated with the standard nylon bag first-order kinetics model. The procedure proposed involved a two-stage mathematical process, with a statistical prediction of some degradation parameters (such as lag time) and then a kinetic model derived by assuming degradation follows zero-order kinetics to determine effective degradability in the rumen (E). In addition to the estimation of washout fraction and discrete lag, which is common to both procedures, the simplified procedure requires measurement of dry matter losses at one incubation time point only. Thus, interference of the animal rumen will be much reduced, which will lead to increased capacity for feed evaluation. Calibration of the zero-order model against the first-order model showed that suitable estimates of E can be obtained with disappearance at 24, 48 or 72 h as the single incubation end time point. The strength of the calibration is such that an end incubation time point as low as 24 h may be sufficient, which may reduce substantially the total incubation time required and thus the impact on the experimental animal. Relevant regression equations to predict reference values of parameters such as lag time or E are also developed and validated.

Type
Modelling Animal Systems Paper
Copyright
Copyright © 2008 Cambridge University Press

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Footnotes

Merged into The Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University.

References

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