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
SALTIRSOIL (SALTS in IRrigated SOILs) is a model for the medium to long term simulation of soil salinity in irrigated, well-drained lands. Once the algorithms were verified, the objective of our study was to validate SALTIRSOIL under one of several water quality and management scenarios in Mediterranean agriculture. Because drip and surface are the most common irrigation systems in irrigated agriculture in Valencia (Spain), the validation was performed with climate, soil, irrigation water (composition and management) and crop (species and management) information from an experimental plot surface irrigated with well water and planted with watermelon that has been monitored since the late spring of 2007. To carry out the validation, first we performed a global sensitivity analysis (GSA). Second, we compared simulated soil saturation extract composition against measured data. According to the GSA, SALTIRSOIL calculations of soil salinity seem to be most affected by climate (rainfall and evapotranspiration) with 60% of explained soil salinity variance, water salinity with 26% of explained variance, and then irrigation with 4%. According to the closeness of the first comparisons between predictions and measurements, SALTIRSOIL does not seem to be affected by any systematic error, and as a consequence, neither inclusion of new parameters nor calibration of the others already included would be needed at least for surface irrigation. The validation of SALTIRSOIL continues under other water quality and irrigation management scenarios. (C) 2011 Elsevier Ltd. All rights reserved.
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