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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 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.

Forage analysis information is used for developing rations, crop rotations and manure nutrient management plans in the Cornell University Nutrient Management Planning System (CuNMPS). The CuNMPS and other similar models use as inputs steady-state conditions on the farm (milk production, herd size, group dynamics, diets, feed composition, farm size and crop production). This steady-state assumption may result in nutrient management plans with large errors, which may introduce risks in income and production variability. One source of error in assuming steady-state conditions is variation in feed composition. The CuNMPS and other nutrient management planning models used to develop nutrient management plans typically rely on either historical forage analysis or infrequently measured compositional values. Methods for incorporating variance have been proposed; however, none have been implemented. The objectives of this study were to determine the amount of variation in a home-raised forage, how this variation affects predicted performance and nutrient excretion by lactating cows and whether this variation can be accounted for in a field-level model, such as the Cornell Net Carbohydrate and Protein System (CNCPS). Each load of maize (Zea mays) harvested for silage was sampled at harvest and analysed for neutral detergent fibre (NDF) and dry matter (DM) on a commercial 500-cow dairy farm. Averages (49.4 and 26.1% for NDF and DM, respectively) and standard deviations (4.52 and 3.59 units for NDF and DM, respectively) along with feeding error (±3% of formulated as fed amounts) were evaluated with the CNCPS (version 4.0). Results indicate that this range in NDF, DM and feeding error caused predicted variation in income over feed costs ($40,000 year-1), feed requirement (73 Mt DM maize silage year-1) and N and P excretion (110 and 37 kg year-1of N and P, respectively) per 100 cows annually. Accounting for this variation in current and future nutrient management models is required to optimize returns over feed costs, while decreasing nutrient excretion.

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: 3 (Page no: 37) Towards a more accurate representation of fermentation in mathematical models of the rumen. Author(s): Nagorcka, B. N. Gordon, G. L. R. Dynes, R. A.
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: 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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