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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Big Data Analytics for Empowering Milk Yield Prediction in Dairy Supply Chains


Accurate prediction of daily milk production is a crucial aspect of the dairy industry. During the past decades, although many models using various data analytic techniques have been proposed in literature to address the milk prediction problem, these models have yet to be widely applied in daily operations. Dairy producers need to predict milk yield at individual cow and group level. Given the increasing amount of milk production information collected every year, difficulty also arises from analyzing big data. To address challenges in dairy supply chains and help dairy producers, especially small-scale producers, make use of data analytics in milk supply decision-making, a targeted effort to develop a feasible and cost-effective tool, Milk Yield Prediction and Analysis Tool (PAT), is launched. This tool allows dairy producers to use various prediction models to discover insight into milk production and forecast future milk yield at both the individual cow and the group level. This paper provides a detailed discussion on the design of this tool and demonstrates how big data analytics can be applied in a cost-effective manner.

  • SG
    Data keywords
    • big data
    Agriculture keywords
    • supply chain
    Data topic
    • big data
    • 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.