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Modelling nutrient utilization in farm animals.

Book cover for Modelling nutrient utilization in farm animals.

Description

This book presents edited and revised versions of papers presented at the Fifth International Workshop on Modelling Nutrient Utilization in Farm Animals, held at the University of Cape Town, Cape Town, South Africa, 25-28 October 1999. There are 31 chapters and 6 sections entitled ruminal metabolism, absorption and metabolism, growth and development, ruminant production in various situations, nutr...

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Chapter 3 (Page no: 37)

Towards a more accurate representation of fermentation in mathematical models of the rumen.

Most mathematical models of the rumen make use of empirical stoichiometric equations to predict the production of fermentation products in the rumen. These models are based on a one, two and three microbial group representation of the total rumen microbial population. The prediction of total VFA concentration by these models is considered to be satisfactory but the predictions of the molar proportions of different VFAs are considered to be inaccurate. A number of possible reasons for this have been suggested, including an inadequate representation of VFA absorption and the effects of pH. We believe the main reason for this lies in the fact the fermentation stoichiometries used by all the models are dependent only on substrate and are otherwise independent of the different microbial groups. Therefore we attempted to improve the predictions of the VFA proportions by developing a new set of fermentation stoichiometries which are dependent both on substrate and the different fermentation pathways characterizing the different microbial groups. We collected information from the literature concerning the range of substrates and biochemical pathways for fermentation, by 16 different microbial groups present in the rumen. This information was used to define the preferred substrates and a stoichiometry for fermentation for each group. A weighted combination of these stoichiometries was then formed using information about their cellular size and relative numbers in the total microbial population to finally obtain stoichiometries representing the fermentation of a range of substrates by three microbial groups, namely, the amylolytic bacteria, cellulolytic bacteria and protozoa. The rumen model of Dijkstra was then modified to incorporate a new submodel for fermentation. Input parameters to classify diets as roughage, concentrate or mixed are no longer used. We evaluated the modified model using several of published data sets. The fermentation submodel resulted in an immediate and significant improvement in the predictions of the VFA proportions.

Other chapters from this book

Chapter: 1 (Page no: 11) The role of thermodynamics in controlling rumen metabolism. Author(s): Kohn, R. A. Boston, R. C.
Chapter: 2 (Page no: 25) Modelling lipid metabolism in the rumen. Author(s): Dijkstra, J. Gerrits, W. J. J. Bannink, A. France, J.
Chapter: 4 (Page no: 49) Simple allometric models to predict rumen feed passage rate in domestic ruminants. Author(s): Cannas, A. Soest, P. J. van
Chapter: 5 (Page no: 63) Ruminal metabolism of buffersoluble proteins, peptides and amino acids in vitro. Author(s): Udén, P.
Chapter: 6 (Page no: 73) Models to interpret degradation profiles obtained from in vitro and in situ incubation of ruminant feeds. Author(s): López, S. France, J. Dijkstra, J. Dhanoa, M. S.
Chapter: 7 (Page no: 87) Modelling production and portal appearance of volatile fatty acids in dairy cows. Author(s): Bannink, A. Kogut, J. Dijkstra, J. France, J. Tamminga, S. Vuuren, A. M. van
Chapter: 8 (Page no: 103) Modelling energy expenditure in pigs. Author(s): Milgen, J. van Noblet, J.
Chapter: 9 (Page no: 115) Aspects of modelling kidney dynamics. Author(s): Robson, B. Vlieg, M.
Chapter: 10 (Page no: 127) Evaluation of a representation of the limiting amino acid theory for milk protein synthesis. Author(s): Hanigan, M. D. France, J. Crompton, L. A. Bequette, B. J.
Chapter: 11 (Page no: 145) Multiple-entry urea kinetic model: effects of incomplete data collection. Author(s): Zuur, G. Russell, K. Lobley, G. E.
Chapter: 12 (Page no: 163) Evaluation of a growth model of preruminant calves and modifications to simulate shortterm responses to changes in protein intake. Author(s): Gerrits, W. J. J. Togt, P. L. van der Dijkstra, J. France, J.
Chapter: 13 (Page no: 175) Simulation of the development of adipose tissue in beef cattle. Author(s): Sainz, R. D. Hasting, E.
Chapter: 14 (Page no: 183) A simple nutrient-based production model for the growing pig. Author(s): Boisen, S.
Chapter: 15 (Page no: 197) Second-generation dynamic cattle growth and composition models. Author(s): Oltjen, J. W. Pleasants, A. B. Soboleva, T. K. Oddy, V. H.
Chapter: 16 (Page no: 211) Modelling interactions between cow milk yield and growth of its suckling calf. Author(s): Blanc, F. Agabriel, J. Sabatier, P.
Chapter: 17 (Page no: 227) A mechanistic dynamic model of beef cattle growth. Author(s): Hoch, T. Agabriel, J.
Chapter: 18 (Page no: 241) Modelling nutrient utilization in growing cattle subjected to short or long periods of moderate to severe undernutrition. Author(s): Witten, G. Q. Richardson, F. D.
Chapter: 19 (Page no: 253) An integrated cattle and crop production model to develop whole-farm nutrient management plans. Author(s): Tylutki, T. P. Fox, D. G.
Chapter: 20 (Page no: 263) Modelling nutrient utilization by livestock grazing semiarid rangeland. Author(s): Richardson, F. D. Hahn, B. D. Schoeman, S. J.
Chapter: 21 (Page no: 281) Using the cornell net carbohydrate and protein system model to evaluate the effects of variation in maize silage quality on a dairy farm. Author(s): Tylutki, T. P. Fox, D. G. McMahon, M. McMahon, P.
Chapter: 22 (Page no: 289) Challenge and improvement of a model of post-absorptive metabolism in dairy cattle. Author(s): McNamara, J. P. Phillips, G. J.
Chapter: 23 (Page no: 303) A rodent model of protein turnover to determine protein synthesis, amino acid channelling and recycling rates in tissues. Author(s): Johnson, H. A. Baldwin, R. L. Calvert, C. C.
Chapter: 24 (Page no: 317) Modelling relationships between homoeorhetic and homoeostatic control of metabolism: application to growing pigs. Author(s): Sauvant, D. Lovatto, P. A.
Chapter: 25 (Page no: 329) Model for the interpretation of energy metabolism in farm animals. Author(s): Chudy, A.
Chapter: 26 (Page no: 347) Linear models of nitrogen utilization in dairy cows. Author(s): Kebreab, E. Allison, R. Mansbridge, R. Beever, D. E. France, J.
Chapter: 27 (Page no: 353) Isotope dilution models for partitioning amino acid uptake by the liver, mammary gland and hindlimb tissues of ruminants. Author(s): Crompton, L. A. France, J. Bequette, B. J. Maas, J. A. Hanigan, M. D. Lomax, M. A. Dijkstra, J.
Chapter: 28 (Page no: 361) The conversion of a scientific model describing dairy cow nutrition and production to an industry tool: the CPM dairy project. Author(s): Boston, R. C. Fox, D. G. Sniffen, C. Janczewski, E. Munson, R. Chalupa, W.
Chapter: 29 (Page no: 379) The utilization of prediction models to optimize farm animal production systems: the case of a growing pig model. Author(s): Bailleul, P. J. dit Bernier, J. F. Milgen, J. van Sauvant, D. Pomar, C.
Chapter: 30 (Page no: 393) A pig model for feed evaluation. Author(s): Danfær, A.

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