• Acronym: DSS-IWM
  • Title: Design and customization of an innovative Decision Support System (DSS) for Integrated Weed Management (IWM)

  • Countries involved: DE, DK, ES
  • Total budget: € 414,891 



Intelligent weed control can reduce herbicide use

Weeds cost money. However, controlling weeds using herbicides also costs money, in addition to time, labour and risks to the environment.

Decision support systems (DSS) that can assist farmers and farm advisors in treating weeds in crops at precisely the right times with the most efficient products and in the right amounts can contribute to reducing herbicide consumption markedly.  Therefore, a new DSS will provide both economic and significant environmental benefits.

Scientists from Germany, Denmark and Spain are therefore collaborating on a project entitled DSS-IWM that seeks to design and customise an innovative online decision support system for weed control in maize and winter wheat. The system’s longevity will be guaranteed by long-term support. The three-year project has four partners and a total budget of € 414,891.

The project partners aim to develop the online system so that it can support reliable decisions based on local conditions. The system will consider thresholds for weed densities and include economic calculations of treatment costs.

Spraying with herbicides is not the only solution to combating weeds. The system will also be able to offer mechanical options wherever possible in keeping with the principles of integrated pest management. With the aid of integrated pest management, including intelligent use of herbicides, the decision support system will facilitate management of herbicide resistance.

The scientists will not be starting from scratch, as there are already decision support systems in Europe. However, there are knowledge gaps, and the project aims to address some of these. Dose-response functions need to be validated under field conditions in maize and winter wheat. Specific tools, such as resistance management and economic calculations, will be added to the decision support system. The project partners will also select and improve the best test version or strategy for practical applications. 


For more information about the project
please contact: 

Dr. Arnd Verschwele
Julius Kühn-Institut, Germany
E-mail: arnd.verschwele@julius-kuehn.de

Project website: dss-iwm.julius-kuehn.de