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
Growth model-based decision_support system for crop management (GMDSSCM was developed including process based models of 4 different crops, i.e. wheat, rice, rapeseed and cotton. This system aims in facilitating simulation and application of crop models for different purposes. Individual models each include six submodels for simulating phasic development, organ formation, biomass production, yield and quality formation, soil-crop water relations, and nutrient (N, P, K) balance. The implemented system can be used for evaluating individual and comprehensive management strategies based on the results of crop growth simulation under various environments and different genotypes. 4 Stand-alone version (GMDSSCM,4) was established under the platforms VC++ and VB by adopting the characteristics of object-oriented and component-based software and with the effective integration and coupling of the growth-prediction and decision-making functions. 4 web-based system (GMDSSCW was further developed on a net platform using C# language. These GMDSSCM systems have been used to predict dynamically crop growth and to make decisions regarding to management systems. This tool should be helpful for construction and application of informational and digital farming systems.
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