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 yield mapping is an important endeavor for agricultural policy making in Mexico where it is a main staple crop. In central Mexico, maize is cultivated under different technological regimes ranging from traditional rain water dependency and using native seeds up to irrigation and improved seeds regimes. Yield variation is in the range of 1.0 ton/ha to over 12.0 ton/ha under the different regimes. It is necessary to explain the increase in average state yield for this crop in the past 10 years in view of a notorious decline tendency in cultivated and harvested area. Precision farming is a system of advanced technologies and procedures which merge spatial mapping variables of the terrain and surrounding conditions with specific management actions for crops. PF requires the integration of several basic component systems such as global positioning system (GPS), data collection and processing devices based on remote sensing and geographical information management systems. Measurements provided by these systems are oriented towards assessing terrain characteristics and spatial variability and can help to locate the better areas to orient management actions to best practices.
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