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
Rural inhabitants of arid lands constantly face a lack of sufficient water to fulfill their agricultural and household needs. In this situation they have to take quick and precise decisions about how to cope with the situation. Moreover, there is not readily available technical information to support their decisions regarding the course of action they should follow to handle the agro-climatic risk. In this paper a computer model (soil water balance model) is described to assess the impact on crops yields of rainfall shortages in dry lands in Mexico. The model is linked to a knowledge based database where a farmer may find readily available information to support cropping decisions. The knowledge base activates when the computed average crop yield is less than the 50% of the expected crop yield. The knowledge base provides information on risk, potential crops, and the geographical location (counties) where the crop may succeed. Also, it provides a technology to increase water productivity under limited availability situations. Further, the model can evaluate the impact of a climate change scenario (IPCC B2). Other inputs to the model being equal, the user may shift the model to run the climate change scenario and to compare the outputs of the model to assess the climate change impact on future crops yields. (C) 2015 Elsevier B.V. All rights reserved.
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