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
Crop fertilization recommendation system involves using models to calculate the needed amount of variety of nutrients during the crop growth, choosing suitable fertilizers, and arranging fertilization time. Whether it can be used widely or not, the key point is that the models or parameters in system can be customized easily according with local agricultural production practices. To help address these issues, an infrastructure of knowledge base and its application is proposed. This paper firstly focuses on decomposition of the model by method of object-oriented in order to comply with the requirements of C++ programming. It is divided into three categories of entity, parameter, and operator for converting the entity objects in fertilization to the software system objects. And then the required knowledge to run model are classified to four types by their action, and expressed as a variety of rules form stored in relation database. In the end, a reasonable decision inference engine designed for applying them. It is actually a specific computer program to control local entities and the rules form introduced to system under a certain strategy and produce appliable recommendation.
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