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.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Information technologies, such as the global positioning system and geographic information system, provide new opportunities for improving the efficiency of weed management, thereby resulting in a reduction in financial and environmental costs. Thus, an evaluation of data of systematic weed surveys carried out repeatedly at locations identified by geographical coordinates allows the establishment of relationships between weed associations and soil properties. Our quantitative survey targeted a 53-ha agricultural field at Baracska, Hungary, with a total of 122 sampling sites. Soil properties (pH, texture, organic carbon, humus, and macro- and microelement contents [altogether 24 parameters]) were determined and weeds (frequency and density for 27 species) were recorded at the sampling sites. A distinct negative association between the crop yield (tightly linked to levels of nitrogen, phosphorus, and potassium fertilizers in the soil) and the total weed density at the sampling sites was demonstrated by principal component analysis of our data, indicating a good management of the project area that successfully increased the crop plant's competitiveness with weeds.
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