Mathematical modelling in agricultural science

Summary A simple initial classification of types of models is given and the essential role of models in science, especially in agricultural science, is reviewed. Empirical models are contrasted with mechanistic models, and these are related to the levels of aggregation considered, and crucially, to the difference between description and understanding. Examples of mechanistic models to simulate aggregated biochemical systems and to interpret experimental data, with reference to nutrition and metabolism in animals, are presented. Requirements for successful modelling in an agricultural context are discussed, followed by consideration of the problems and promise of linking the modelling viewpoint into a biological research programme. Finally, the ranges of possible objectives and potential contributions of mathematical modelling in agricultural science are explored.