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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Soybean oil content QTL mapping and integrating with meta-analysis method for mining genes


Oil content of soybean was a valuable quantitative trait controlled by multiple genes. Eleven QTLs were detected by both CIM and MIM method with the population crossed between Charleston and Dong nong594 in recent 3 years (2007, 2008, 2009). Combining the QTLs collected over the past 20 years, an integrated map of oil-content major QTLs in soybean was established using soymap2, which was published in 2004, as a reference. Using the software BioMercator ver.2.1, QTLs were projected from their own maps onto the reference map. In total, ninety-eight QTLs were integrated into soymap2. A meta-analysis method was used to narrow down the confidence interval, and 20 consensus QTLs and their corresponding markers were obtained. Using a local version of GENSCAN, 10,137 sequences in the consensus QTL intervals were predicted. With BLAST, these predicted genes were compared to the International Protein Index database to mine the related genes. The results offer a basis for gene mining and molecular breeding in soybean.

  • CN
  • NE_Agr_Univ (CN)
Data keywords
  • ontology
Agriculture keywords
    Data topic
    • big data
    • semantics
    Document type

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

    Institutions 10 co-publis
    • NE_Agr_Univ (CN)
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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.