Fisher information and crop model parameters

Probability and logistic functions have proven quite useful in our work on mathematical models of crop growth and yields over the last fifteen years. Articles have been written in which the models have been applied to differe nt crops on a variety of soils at various locations around the world, and f or which model parameters have been evaluated. At first glance this work ap pears to be an attempt to model the plant system. However, upon further exa mination it becomes clear that what is being modeled is information about t he system and not the physical system directly. In this article we examine the models in the framework of Fisher information and identify the key para meters for the probability and logistic models.