e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Characterization of some Middle European soil textures by gamma-spectrometry


Information about the variability of different soil attributes within a field is essential for sustainable land management and precision agriculture. Mobile proximal gamma-ray spectrometry can map soil characteristics of vast areas at different scales rapidly and cost-effectively. This study aims at investigating reliability and capability of mobile-gamma-spectrometry (radiometrics) data to map typical soils of Middle Europe. In this paper, we investigate relationships between the radioelement concentrations (K, U, Th, and dose rate) and soil parameters (texture, CEC, pH, and organic-C content) at four different field sites and soil textures. The data reliability is confirmed at the survey start. Mobile data have an excellent linear correlation (nearly 1:1) with the stationary readings (of identical devices, acquisition setups, and soil conditions) but moderate correlation with laboratory data (of different devices, setups, and sample conditions). Dried lab samples have systematically higher radioelement concentrations than the field soils (normally wet). Consequently, the mobile-gamma-spectrometric data is sufficiently accurate for soil mapping, and its calibration by laboratory data is less useful due to the varying environmental conditions. Single absolute radioelement concentrations show only moderate correlations with the different soil parameters, particularly clay content and CEC. This may be related to varying environmental conditions (soil moisture, soil structure, vegetation, land use, etc.) between the study sites. Investigations of the ratios of radioelement concentrations yield a clear improvement of their correlations to soil parameters, especially for sand and clay contents, CEC, and organic C. Additionally, multiple-linear-regression models were established using the element concentrations of potassium and thorium to predict silt content and pH. The results of the highly correlated models were confirmed by comparing with clay and silt content and pH value, respectively, to six additional independent field samples. Briefly, applications of gamma-ray data for soil mapping offers the possibility of the development of quantitative relationships regarding soil parameters like sand and clay contents, CEC, and organic C. Classification of soil textures by gamma-ray data seems to be promising, though a broader database of soils is needed for further research. We recommend gamma-ray mapping as a complementary or even an alternative to common mapping techniques.

  • DE
  • Kiel_Univ (DE)
Data keywords
  • data reliability
Agriculture keywords
  • agriculture
Data topic
  • information systems
  • modeling
  • decision support
  • sensors
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.