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Modelling of nutrient partitioning in growing pigs to predict their anatomical body composition. 2. Model evaluation

Published online by Cambridge University Press:  09 March 2007

V. Halas*
Affiliation:
University of Kaposvár, Faculty of Animal Science, Department of Animal Nutrition, P. O. Box 16, H-7400 Kaposvár, Hungary
J. Dijkstra
Affiliation:
Animal Nutrition Group, Wageningen University and Research Centre, Zodiac, Marijkeweg 40, 6709 PG Wageningen, The Netherlands
L. Babinszky
Affiliation:
University of Kaposvár, Faculty of Animal Science, Department of Animal Nutrition, P. O. Box 16, H-7400 Kaposvár, Hungary
M. W. A. Verstegen
Affiliation:
Animal Nutrition Group, Wageningen University and Research Centre, Zodiac, Marijkeweg 40, 6709 PG Wageningen, The Netherlands
W. J. J. Gerrits
Affiliation:
Animal Nutrition Group, Wageningen University and Research Centre, Zodiac, Marijkeweg 40, 6709 PG Wageningen, The Netherlands
*
*Corresponding author: Dr Veronika Halas, fax +36 82 313 562, email halas@mail.atk.u-kaposvar.hu
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Abstract

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The objective of the present paper was to evaluate a dynamic mechanistic model for growing and fattening pigs presented in a companion paper. The model predicted the rate of protein and fat deposition (chemical composition), rate of tissue deposition (anatomical composition) and performance of pigs depending on nutrient intake. In the model evaluation, the predicted response of the pig to changes in model parameters and to changes in nutrient intakes is presented. As a result of the sensitivity analysis, changes in the maintenance energy requirements and the fractional degradation rate of muscle protein had the greatest impact on tissue deposition rates. The model was also highly sensitive to changes in the maximum velocity and steepness parameter of the lysine utilisation for muscle protein synthesis. The model was further tested by independent published results. The model successfully predicted the response of pigs to a wide range of variation in nutrient composition. Consequently, the model can be applied to develop feeding strategies to optimise pig production. It also enables prediction of the slaughter performance and the meat quality.

Type
Research Article
Copyright
Copyright © The Nutrition Society 2004

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