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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Site-specific management units in a commercial maize plot delineated using very high resolution remote sensing and soil properties mapping


The joint use of satellite imagery and digital soil maps derived from soil sampling is investigated in the present paper with the goal of proposing site-specific management units (SSMU) within a commercial field plot Very high resolution Quickbird imagery has been used to derive leaf area index (LAI) maps in maize canopies in two different years. Soil properties maps were obtained from the interpolation of ion concentrations (Na, Mg, Ca. K and P) and texture determined in soil samples and also from automatic readings of electromagnetic induction (EMI) readings taken with a mobile sensor. Links between the image-derived LAI and soil properties were established, making it possible to differentiate units within fields subject to abiotic stress associated with soil sodicity, a small water-holding capacity or flooding constraints. In accordance with the previous findings, the delineation of SSMUs is proposed, describing those field areas susceptible of variable-rate management for agricultural inputs such as water or fertilizing, or soil limitation correctors such as gypsum application in the case of sodicity problems. This demonstrates the suitability of spatial information technologies such as remote sensing and digital soil mapping in the context of precision agriculture. (C) 2010 Elsevier B.V. All rights reserved.

  • FR
  • ES
  • Inra (FR)
  • CSIC_Spanish_Natl_Res_Council (ES)
  • CITA_Aragon_Agrifood_Res_&_Technol_Ctr_Aragon (ES)
Data keywords
  • information technology
Agriculture keywords
  • agriculture
Data topic
  • sensors
Document type

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

Institutions 10 co-publis
  • Inra (FR)
  • CSIC_Spanish_Natl_Res_Council (ES)
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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.