Crop modelling: Current status and opportunities to advance

Systems approaches are an appropriate means to meet the complex challenges facing managers of agricultural systems. Crop modelling can play a significant part in systems approaches by providing a powerful capability for scenario analyses. Crop modelling has developed extensively over the past 30 years and a diverse range of crop models are now available. It is argued, however, that the tendency to distinguish between, and separate, the so-called "scientific" and "engineering" challenges and approaches in crop modelling has constrained the maturation of modelling. It is considered that effective crop modelling must combine a scientific approach to enhance understanding with an applications orientation to retain a focus on prediction and problem-solving. The major issue in effective crop modelling is seen as how to achieve the appropriate balance between simplicity and complexity in combining the biology, physics, and prediction requirements for each specific task. Avoidance of unnecessary complexity and maintenance of transparency are considered as guiding principles