A Relational Database as Decision Support System in Chemical Weed Control

Abstract

Decision making in weed control is complex and time-consuming. Moreover, the structure of the available information does not facilitate the comparison of different herbicides. Indeed, information format can be the limiting factor in the performance of sophisticated computer programs intended to supply appropriate advice on weed control treatments. A relational database for decision support on chemical weed control has been developed. It uses a detailed structure by subdividing the information where possible. The database includes programs for entering, updating, and printing data, as well as programs for retrieving information and giving treatment advice. The information access on herbicides is organized around searches based on a specific crop and multiple weed species at their respective growth stages. Optimization of the selected herbicides is carried out and supplies the lowest number of herbicides controlling all the chosen weeds. Information on critical parameters for herbicide application such as varietal restrictions, rotational crops, and compatibility with other products is also interactively available.

Response of weeds and crop yield to herbicide dose decision-support guidelines

“…Satisfactory effects on weeds may also often be obtained when herbicides are used at lower doses than normally recommended, and currently a number of different types of decision-support systems are available for helping crop advisors and farmers choose the optimal herbicide dose (Buhler et al 1997;Forcella et al 1996;Shaw et al 1998;Stigliani et al 1996).…”

“…Undesirable consequences of weed control failure may be reduced by using some sort of support system for decisions. During the last 15 to 20 yr, several decision-support systems for chemical weed control have been presented, and most are computer based (e.g., Hoffman et al1999;Murali et al 1999;Stigliani et al 1996). Some of these systems have been validated in the field for 1 yr or more, but the validation has seldom included long-term effects on the weed flora or on crop yield in a specific field.…”

Integration of a Cropping Systems Simulation Model and a Relational Database for Simple Farm‐Scale Analyses

“…Relational databases are useful tools to organize and integrate data about specific aspects of reality (Garcia-Molina et al, 2002). Examples of their application in agriculture include the storage and management of experimental data (e.g., van Evert et al, 1999a(e.g., van Evert et al, , 1999bScott and Lord, 2003;Zuliani et al, 2003), soil data (e.g., Wö sten et al, 1999;Ali et al, 2004), crop quality data (Haley et al, 1999), and pest and weed management information (Stigliani et al, 1996;Xia et al, 2003).…”