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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Autofluorescence spectroscopy for early diagnosis of "cancer eye" - art. no. 64301K


We report an in-vitro autofluorescence spectroscopic study of cow eye tissue to explore the applicability of the approach in discriminating early stage "cancer eye" from normal squamous eye tissues. Significant differences were observed in the autofluorescence signatures between the "cancer eye" and normal eye tissues. The spectral differences were quantified by employing a probability-based diagnostic algorithm developed based on recently formulated theory of Relevance Vector Machine (RVM), a Bayesian machine-learning framework of statistical pattern recognition. The algorithm provided sensitivity and specificity values of 97 +/- 2 % towards cancer for the training set data based on leave-one-out cross validation and a sensitivity of 97 +/- 2 % and a specificity of 99 +/- 1 % towards cancer for the independent validation set data. These results suggest that autofluorescence spectroscopy might prove to be a quantitative in-vivo diagnostic modality for early and accurate diagnosis of "cancer eye" in veterinary clinical setting, which would help improve ranch management from both economic and animal care standpoint.

  • US
  • Vanderbilt_Univ (US)
Data keywords
  • machine learning
Agriculture keywords
    Data topic
    • big data
    • modeling
    Advanced Biomedical and Clinical Diagnostic Systems V
    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.