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
Modeling of Phosphorus Loads in Sugarcane in a Low-Relief Landscape Using Ontology-based Simulation
Water flow and P dynamics in a low-relief landscape manipulated by extensive canal and ditch drainage systems were modeled utilizing an ontology-based simulation model. In the model, soil water flux and processes between three soil inorganic P pools (labile, active, and stable) and organic P are represented as database objects. And user-defined relationships among objects are used to automatically generate computer code (Java) for running the simulation of discharge and P loads. Our objectives were to develop ontology-based descriptions of soil P dynamics within sugarcane- (Saccharum officinarum L.) grown farm basins of the Everglades Agricultural Area (EAA) and to calibrate and validate such processes with water quality monitoring data collected at one farm basin (1244 ha). In the calibration phase (water year [WY] 99-00), observed discharge totaled 11,114 m(3) ha(-1) and dissolved P 0.23 kg P ha(-1); and in the validation phase (WY 02-03), discharge was 10,397 m(3) ha(-1) and dissolved P 0.11 kg P ha(-1) During WY 99-00 the root mean square error (RMSE) for monthly discharge was 188 m(3) ha(-1) and for monthly dissolved P 0.0077 kg P ha(-1); whereas during WY 02-03 the RMSE for monthly discharge was 195 m(3) ha(-1) and monthly dissolved P 0.0022 kg P ha(-1). These results were confirmed by Nash-Sutcliffe Coefficient of 0.69 (calibration) and 0.81 (validation) comparing measured and simulated P loads. The good model performance suggests that our model has promise to simulate P dynamics, which may be useful as a management tool to reduce P loads in other similar low-relief areas.
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