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Taking Weed Management Decisions Into the 21st Century

Christy Sprague Christy Sprague
Assistant Professor
Department of Crop Sciences
(217) 333-4424; csprague@illinois.edu
Jeff Bunting

Jeff Bunting
Graduate Research Assistant
Department of Crop Sciences
(217) 333-4424; bunting@illinois.edu


Weed management can be one of the most challenging decisions that growers and crop consultants face from year to year. Good weed management tactics need to take into account efficacy, economics, and environmental stewardship. Each year, growers face new herbicides, name changes, and premixes. The sheer number of products available on the market adds to the confusion. Computer models are well suited to process these large quantities of information and may help facilitate the weed management decision process.

A farm advisor using WeedSOFT for weed management recommendations

Figure 1. A farm advisor using WeedSOFT for weed management recommendations.

Computers can aid in making weed management decisions in several ways. In the simplest form, many universities display their weed management recommendations either on CDs or online. However, several computer models can actually process field information to generate a list of viable weed management options for a particular field. Initial development of these models focused on herbicide efficacy, often with consideration of treatment cost, crop rotation, and soil properties. These interactive computer models often are referred to as “herbicide efficacy” models. More comprehensive computer models feature cost/benefit analysis of various weed management strategies based on treatment cost and predicted crop loss. These models are “bioeconomic” or “threshold-based” models.

In the Midwest, two computer programs currently are used for weed management decisions: WeedMAK II and WeedSOFTSM. WeedMAK II is interactive software that uses a herbicide efficacy model to help growers with weed management decisions. The recommendations generated from this software are based on inputs of crop, weed type, and soil type. Decisions are based on the effectiveness for specific weeds along with the estimated cost per acre for the herbicide treatment. WeedMAK II is supported through the University of Kentucky and carries recommendations that are based on Kentucky herbicide efficacy information.

WeedSOFTSM is another decision-support system used in the Midwest. This interactive software was developed in Nebraska and uses a bioeconomic (threshold-based) model. Over the last few years, there has been an effort to regionalize WeedSOFTSM in a number of the midwestern states. Earlier this year, the first Illinois version of WeedSOFTSM was released to the public. Two modules are incorporated in Illinois’ version of WeedSOFTSM: ADVISOR and WeedVIEW. WeedVIEW is a picture database that offers detailed photographs of more than 35 weed species to help aid in weed identification. However, the heart of WeedSOFTSM is ADVISOR. It is the diagnostic and analytic decision-support component of the software.

ADVISOR works by analyzing the user-defined crop, soil moisture, climate, and numbers and types of weeds. These contributing conditions assist the user in the selection of optimal weed control treatments. ADVISOR incorporates soil-applied, postemergence, and sequential programs to strategize a weed management plan. ADVISOR ranks the list of allowable weed control options in descending order of percentage of maximum yield potential or in descending order of net gain. ADVISOR accomplishes this task by calculating expected yield loss for a given weed population through a series of equations, taking into account expected crop yield, the weed species’ competitive ability, crop competitiveness, and herbicide efficacy. Through these calculations, ADVISOR also can determine the dollars lost if the field is not treated.

These computer programs are decision-support systems, not decision makers. These programs narrow down the various weed management strategies from which a grower can choose, hopefully making the vast amounts of weed management information manageable.

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College of Agriculture, Consumer and Environmental Sciences
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