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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A portable soil nitrogen detector based on NIRS


As one of the most important soil nutrient components, soil total nitrogen (TN) content needs to be measured in precision agriculture. A portable soil TN detector based on the 89S52 microcontroller was developed, and a Back Propagation Neural Network (BP-NN) estimation model embedded in the detector was established using near-infrared reflectance spectroscopy with absorbance data at 1550, 1300, 1200, 1100, 1050, and 940 nm wavelengths. The detector consisted of two parts, an optical unit and a control unit. The optical unit included six near-infrared lamp-houses, a shared lamp-house drive circuit, a shared incidence and reflectance Y-type optical fiber, a probe, and a photoelectric sensor. The control unit included an amplifier circuit, a filter circuit, an analog-to-digital converter circuit, an LCD display, and a U-disk storage component. All six absorbance data as inputs were used to calculate soil TN content by means of the estimation model. Finally, the calculated soil TN content was displayed on the LCD display and at the same time stored in the U-disk. A calibration experiment was conducted. The soil TN content correlation coefficient (R (2)) of the BP-NN estimation model was 0.88, and the validation R (2) was 0.75. This result indicated that the developed detector had a stable performance and a high precision.

  • CN
  • China_Agr_Univ_CAU (CN)
Data keywords
    Agriculture keywords
    • agriculture
    Data topic
    • modeling
    • sensors
    Document type

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

    Institutions 10 co-publis
    • China_Agr_Univ_CAU (CN)
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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.