e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Will Decision-Support Systems Be Widely Used for the Management of Plant Diseases?


Decision-support systems (DSSs) are interactive computer-based systems that help decision makers solve unstructured problems under complex, uncertain conditions. Experimental use of DSSs has resulted in improved disease suppression and lowered risks of crop damage. In many cases, it has also led to the use of smaller quantities of active substances, as compared with standard spraying practices. Hundreds of DSSs have been developed over the years and are readily available and affordable. However, most farm managers do not use them as part of their integrated pest management (IPM) practices. Since the mid-1980s, the author of this paper, together with numerous colleagues, has developed DSSs and decision rules for the management of diseases in a variety of crops, including extensive crops, such as wheat, sunflower, and pea; semi-intensive crops, such as pear, chickpea, cotton, and tarragon; and intensive crops, such as tomato, potato, cucumber, sweet pepper, carrot, and grapevine. Some of these systems were used widely, but others were not. This experience may allow us to draw general conclusions regarding the use of DSSs and decision rules. Possible explanations for the widely varying acceptance rates are presented, and the effects of anticipated changes in the agribusiness sector on the future use of DSSs are discussed.

  • IL
    Data keywords
      Agriculture keywords
      • farm
      Data topic
      • decision support
      Document type

      Inappropriate format for Document type, expected simple value but got array, please use list format

      Institutions 10 co-publis
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        e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
        Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.