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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Towards Automatic Estimation of the Body Condition Score of Dairy Cattle Using Hand-held Images and Active Shape Models


The Body Condition Score (BCS) is considered a critical value for dairy farms, since its observation can be used to optimize milk production. Usually, the BCS is calculated by human experts after visual inspection in a time-consuming and subjective process. There are already some papers where this process is almost automated using image processing on some kinds of pictures and, in this work, the first steps towards a fully automated method based on pictures taken with common photographic cameras are described. Active Shape Models (ASM) are used to obtain a set of features that describe the back shape of cows and those features feed a classifier that computes the BCS. We show that the BCS can be estimated using only a set of angles from the back view with an error similar to that calculated between scores of two experts. To obtain those angles automatically is the hardest step in this process, but we have already achieved reasonable results on that point too.

  • ES
  • Univ_Coruna_UDC (ES)
Data keywords
  • machine learning
Agriculture keywords
  • cattle
  • farm
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.