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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Nasal isolation of Mannheimia haemolytica and Pasteurella multocida as predictors of respiratory disease in shipped calves


Three hundred ninety five calves were purchased from sale barns and delivered to the Willard Sparks Beef Research Center. Nasal swabs were collected to determine if presence of Mannheimia haemolytica and Pasteurella multocida in the upper respiratory tract (URT) can facilitate diagnosis of bovine respiratory disease (BRD). Samples were collected at arrival and at treatment for BRD. Clinically healthy control calves were sampled at time of treatment of sick calves. M. haemolytica was more commonly isolated from calves at treatment than at time of arrival or from control calves. M. haemolytica was more common in calves requiring treatment than in those never treated. Need for treatment and number of treatments were negatively associated with average daily gain, supporting the accuracy of diagnosis. These results suggest that URT sampling, when combined with clinical diagnosis, may assist in providing greater diagnostic accuracy, improving ability to evaluate risk factors, interventions, and treatments. (C) 2014 Elsevier Ltd. All rights reserved.

  • US
  • Oklahoma_State_Univ_Stillwater (US)
Data keywords
    Agriculture keywords
      Data topic
        Document type

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

        Institutions 10 co-publis
        • Oklahoma_State_Univ_Stillwater (US)
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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.