Computer technology is an integral part of crop production in many ways. From the field to the farm office, it supports all aspects of crop and soil management systems. Crop modeling was one of the early applications of computers in crop production, but recent developments in technology and services have made it a more practical tool for many decision-making processes.

A model is actually the integration of our knowledge (or at least our current understanding) of how the crop/soil/climate/management system works, with all of its interactions. We all have a concept of how it should work in our head as we grow a crop. The trick is writing that model down — or putting it together in a computer program that simulates the crop growth.

I first became involved with crop modeling in the early 1970s as a graduate student at Purdue University working on a National Science Foundation research project studying crop and weather interactions, and the influence of water and temperature stresses on the corn crop.

As I continued my work on weather and corn interactions, it became evident that crop modeling was a good tool to use in integrating all of the information about the crop, soil, weather and management that affects crop growth and yield.

In the years that followed, an evolution of large-scale projects demonstrated the science of crop modeling. But the cost of collecting the vast amounts of weather, soils and other databases, along with the massive computer requirements, made them impractical for applications at the farm level.

Fast-forward 30 years and we now have the computer power in a laptop or a handheld system to do the computations, and massive databases of weather information are available on the Internet. Large data warehouse services can handle the crop management metadata needed. In short, crop models are now potentially viable tools for production management decisions.

As farmers continue to build their on-farm databases from crop records over a number of years, and their precision ag retailers assist in reaching these goals, data becomes an important tool for making better-informed crop and soil management decisions.

Records of production inputs and practices, crop yields, scouting and on-farm weather all add value as new resources for the farmer and his adviser in planning for the future.

This data can be used with a variety of models to predict responses to decisions farmers make. They can also be used to evaluate effects of decisions for previous years — also valuable in making decisions.

Simple models like growing degree models to predict maturity dates for corn, insect development models, disease predictions or water use models may be the first ones used by a farmer.

The power of laptop computers, handheld tablets and smartphones now make it possible to have such tools readily available in the field. On-board computer technology linked to sensors and controllers of various types also make it possible to link automated models to collected data to help enhance on-the-go machine automation.

As these precision technologies develop further, modeling and simulation will become more common tools for farmers and their precision advisers. We can benefit greatly from proper use of models in making better-informed crop management decisions.

But we need to keep in mind, a comment from an early crop modeling researcher in the mid-1970s. “A model gives you a great black-and-white image of the growing crop. If you want a color picture, you need to grow the crop.”