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Crop modeling with simple simulation models (SSM)
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06 February 2026

Models can be effective tools, and in many cases essential tools, to understand and predict the development, growth, and yield of crops in response to variation in environment, plant genetics, and management. Criteria for such effective models are that they are transparent and robust. The family of Simple Simulation Models (SSM) meets these criteria to a large extent by rigorously seeking simplicity in describing functional relationships. The approach was to use conservative relationships and summary expressions at a single explanatory level to output explanation at the next higher level. As described in this chapter, relationships are generally simulated on a daily time step for a canopy to give seasonal crop growth. In addition to describing the fey functions in SSM, examples are presented showing the robustness of the model and uses to which it has been applied.
TECHNOLOGY & ENGINEERING / Agriculture / Agronomy / Crop Science, TECHNOLOGY & ENGINEERING / Agriculture / Sustainable Agriculture
- 1 Introduction
- 2 The history of simple simulation models (SSM)
- 3 Basic principles underpinning SSM
- 4 SSM critical functions
- 5 Genetic parameter inputs to SSM
- 6 Environmental inputs and model outputs
- 7 Software and programming
- 8 Examples of SSM use
- 9 Future developments
- 10 Conclusions
- 11 Appendix: definition of necessary parameters
- 12 References