Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model
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- 作者：Nadav S Bar (1)
Nicole Radde (2) - 刊名：BMC Systems Biology
- 出版年：2009
- 出版时间：December 2009
- 年：2009
- 卷：3
- 期：1
- 全文大小：581KB
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Nicole Radde (2)
1. Department of Chemical Engineering, Norwegian University of Science and Technology, NO-7491, Trondheim, Norway
2. Institute for Systems Theory and Automatic Control, University of Stuttgart, 70550, Stuttgart, Germany
文摘
Background Feed composition has a large impact on the growth of animals, particularly marine fish. We have developed a quantitative dynamic model that can predict the growth and body composition of marine fish for a given feed composition over a timespan of several months. The model takes into consideration the effects of environmental factors, particularly temperature, on growth, and it incorporates detailed kinetics describing the main metabolic processes (protein, lipid, and central metabolism) known to play major roles in growth and body composition. Results For validation, we compared our model's predictions with the results of several experimental studies. We showed that the model gives reliable predictions of growth, nutrient utilization (including amino acid retention), and body composition over a timespan of several months, longer than most of the previously developed predictive models. Conclusion We demonstrate that, despite the difficulties involved, multiscale models in biology can yield reasonable and useful results. The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth. The model provides important improvements over existing models.