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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decision_support system for nitrogen fertilization using fuzzy theory


During the last three decades there has been great concern about the impact of agriculture on the environment and its resources. Conventional agriculture is based on whole field and mostly empirical approaches to defining and applying agrochemical inputs, which poses certain limitations regarding the management of existing variability in agricultural land. In this paper, the design and application of a fuzzy decision_support system, concerning site specific nitrogen fertilization, is described. The system uses an easy but efficient way of solving the nitrogen equation under agricultural conditions and is based on knowledge elicitation and fuzzy logic methodologies. More specifically, the system is composed of two parts; a knowledge base and an analytical modular part which simulates nitrogen balance. The analytical part is built in a four level structure which consists of eleven fuzzy systems. The evaluation of the system presupposes the availability of 14 state variables that can be easily collected and refer to characteristics of the soil, weather and farming practices. The incorporated knowledge and the formulation of fuzzy rules were based on interviews with experts and on annotating scientific and technical bibliographic resources. A sensitivity analysis of the developed system was carried out in order to evaluate its robustness against errors or uncertainty in the state variables and further to assess and highlight the important variables. The application of the system using a set of point data, drawn from cotton fields in central Greece and stored in a Geographical Information System, is described in brief and the results show considerable variability in the recommended amount of nitrogen fertilizer among the reference sites. (C) 2011 Elsevier B.V. All rights reserved.

  • GR
  • Agr_Univ_Athens_AUA (GR)
  • Natl_Tech_Univ_Athens_NTUA (GR)
Data keywords
  • knowledge
  • information system
  • knowledge based
Agriculture keywords
  • agriculture
  • farming
Data topic
  • big data
  • information systems
  • modeling
  • decision support
Document type

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

Institutions 10 co-publis
  • Agr_Univ_Athens_AUA (GR)
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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.