ABSTRACT
Using simulation models, managers make planning and/or management decisions including the selection and optimum utilization of machinery, labor, and other farm resources to increase their profits. These models can be broadly classified into biological plant scale, field scale, and whole-farm models. The whole-farm models capture the operational constraints and behavior of a farm. Such models predict the performance of the farm in response to different management strategies under different climatic and soil conditions. Simulation models capture the dynamic behavior—the changes over time—of the system. These changes could constitute discrete events and/or continuous processes. The approaches used for whole-farm simulation models can be classified into two broad categories: algorithmic or procedural and object-oriented. The object-oriented approach to modeling can capture many of these operational requirements of a farm system, thus resulting in a more powerful model. Objects in the object-oriented paradigm are discrete entities that incorporate both data structure and behavior.
