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
Precision agriculture is a management concept depending on information technologies related to within-field variability. Site-specific plant production requires the use of technologies, such as global positioning systems, sensors, and information management tools to assess variations in soil, crop canopy and micro-climate. Crop protection is an important production factor, which at present is applied in high-input cropping systems homogeneously in the field despite of site-specific heterogeneity in the incidence and distribution of weeds, pests and pathogens. The spatial and temporal heterogeneity of pests in the field is assessed using remote sensing techniques linked to global positioning systems. The generation and management of information on pest incidence with high spatial resolution and its conversion into precise control systems will enable a targeted and resource-preserving integrated pest management system under high productivity conditions, which is economically successful, environmentally sound and socially acceptable. The recording of disease-related weather data and the assessment of spatial heterogeneity of micro-climate in the field as well as the detection of disease specific symptoms with remote and near range sensors (multispectral and hyperspectral cameras, thermography, chlorophyll fluorescence etc.) have the potential to make crop protection more precise in space and time. Innovative approaches are discussed in detail.
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