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A Relational Database as Decision Support System in Chemical Weed Control

Published online by Cambridge University Press:  12 June 2017

Lucia Stigliani,
Giuseppe Santospirito,
Nicola Cardinale and
Cosimo Resina
Lucia Stigliani
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Giuseppe Santospirito
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Nicola Cardinale
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Cosimo Resina
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
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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.

Keywords

Computerherbicide optimization

Information

Type
Research
Information
Weed Technology , Volume 10 , Issue 4 , December 1996, pp. 781 - 794
Copyright
Copyright © 1996 by the Weed Science Society of America 

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References

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