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
Real-time analysis of soil moisture, soil organic matter, and soil total nitrogen with NIR spectra
The grey-brown alluvial soil in northern china was selected as research object, and the feasibility and possibility of real-time analyzing soil parameter with NIR spectroscopic techniques were explored. One hundred fifty samples were collected from a winter wheat farm. NIR absorbance spectra were rapidly measured under their original conditions by a Nicolet Antaris FT-NTIR analyzer. Three soil parameters, namely soil moisture, SOM (soil organic mater) and TN (total nitrogen) content, were analyzed. For soil moisture content, a linear regression model was available, using 1 920 mn wavelength with correlation coefficient of 0.937. so that the results obtained could be directly used to real-time evaluate soil moisture. SOM content and TN content were estimated with a multiple linear regression model, 1 870 and 1 378 nm wavelengths were selected in the SOM estimate model. and 2 262 and 1 888 nm wavelengths were selected in the TN estimate model. The results showed that soil SOM and TN contents can be evaluated by using NIR absorbance spectra of soil samples.
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