Animal Feed Science and Technology 112 (2004) 131–154 An integrated mathematical model to evaluate nutrient partition in dairy cattle between the animal and its environment E. Kebreab a,∗ , J.A.N. Mills b , L.A. Crompton b , A. Bannink c , J. Dijkstra d , W.J.J. Gerrits d , J. France a a Department of Animal and Poultry Science, University of Guelph, Guelph, Ont., Canada N1G 2W1 b School of Agriculture, Policy and Development, The University of Reading, Earley Gate, Reading RG6 6AR, UK c Institute for Animal Science and Health, P.O. Box 160, NL-8200 AD Lelystad, The Netherlands d Animal Nutrition Group, Institute of Animal Sciences, Wageningen University, Marijkeweg 40, 6709 PG Wageningen, The Netherlands Abstract In the past decade, a number of mechanistic, dynamic simulation models of several components of the dairy production system have become available. However their use has been limited due to the detailed technical knowledge and special software required to run them, and the lack of compatibility between models in predicting various metabolic processes in the animal. The first objective of the current study was to integrate the dynamic models of [Brit. J. Nutr. 72 (1994) 679] on rumen function, [J. Anim. Sci. 79 (2001) 1584] on methane production, [J. Anim. Sci. 80 (2002) 248] on N partition, and a new model of P partition. The second objective was to construct a deci- sion support system to analyse nutrient partition between animal and environment. The integrated model combines key environmental pollutants such as N, P and methane within a nutrient-based feed evaluation system. The model was run under different scenarios and the sensitivity of various parameters analysed. A comparison of predictions from the integrated model with the original sim- ulation models showed an improvement in N excretion since the integrated model uses the dynamic model of [Brit. J. Nutr. 72 (1994) 679] to predict microbial N, which was not represented in detail in the original model. The integrated model can be used to investigate the degree to which produc- tion and environmental objectives are antagonistic, and it may help to explain and understand the Abbreviations: AA, amino acid; ACSL, Advanced Continuous Simulation Language; AFRC, Agricultural and Food Research Council (UK); BW, body weight; DLL, dynamic link library; DM, dry matter; DMI, dry matter intake; DNA, deoxyribonucleic acid; DSS, decision support system; FA, fatty acids; GUI, graphical user interface; LCFA, long chain fatty acids; ME, metabolizable energy; MSPE, mean square prediction error; MTP, microbial true protein; RNA, ribonucleic acid; VFA, volatile fatty acids ∗ Corresponding author. Tel.: +1-519-824-4120 ext. 53660; fax: +1-519-836-9873. E-mail address: ekebreab@uoguelph.ca (E. Kebreab). 0377-8401/$ – see front matter © 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.anifeedsci.2003.10.009