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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Utilisation of agricultural databases for statistical evaluation of yields of barley and wheat in relation to soil variables and management practices


The objective of this study was to utilise existing databases for evaluating effects of soil and management factors on the yields of barley and wheat in Norway. In a multiple regression model, 17% and 19% of the variation of barley and wheat yield, respectively, was explained by 15 significant predictors. The highest-ranking predictors for barley yield were percent area of wheat ( indicating more favourable climatic condition), irrigation, pH and silt. Other significant predictors were agricultural education, CV pH, man-hours on farm, ( pH)(2), loam, 1n P-AL, 1n area of farm, number of fields, ( 1n P-AL)(2), ( 1n area)(2\) and percent grass area. For wheat yield, the highest-ranking predictors were irrigation, percent winter wheat, pH and ln area of farm. Other significant predictors were CV pH, 1n P-AL, ( pH)(2), loam, number of fields, ( 1n P-AL)(2), man-hours per ha, percent grass area, agricultural education, other grain and ( 1n area)(2).

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    Data keywords
    • agricultural database
    Agriculture keywords
    • agriculture
    • farm
    Data topic
    • information systems
    • knowledge transfer
    • modeling
    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.