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
Research on programming model for optimal management zone delineation in precision agriculture
Based on a set of high new technologies, such as the modern information technology, the organism's technology and the variable rate technology, and so on, the precision agriculture has been become the important way of modem agricultural production. A mixed integer, quadratic programming model using a mean-variance (E-V) framework is used to represent the precision agriculture issues of varying planting date with novel polymer seed coatings. It is hoped that model results will aid in improving management zone delineation rules and lead to the development of farm level decision rules including risks faced by producers. A novel modeling procedure that both identifies the economically optimal management zone or grid size and permits economic comparison of alternative decision rules to determine such zones is presented in this research. The decision of how to appropriately delineate economically optimal management zones or grid sizes represents a great opportunity to assist producers in achieving the combined goals of profit maximization and risk management.
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