Research article

Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model

Nadav S Bar¹ and Nicole Radde²

¹Department of Chemical Engineering, Norwegian University of Science and Technology, NO-7491, Trondheim, Norway

²Institute for Systems Theory and Automatic Control, University of Stuttgart, 70550 Stuttgart, Germany

author email corresponding author email

BMC Systems Biology 2009, 3:107doi:10.1186/1752-0509-3-107

Published:	10 November 2009

Abstract

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.