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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Cloud-based monitoring and analysis of yield efficiency in precision farming


Yield mapping visualizes yield rate per geological distribution. It is frequently used as a baseline metric to measure yield efficiency in precision farming. A major challenge in mapping yield for specialty crops is how to collect accurate yield data without incurring substantial overhead to a farming operation. We design a yield efficiency analysis system that uses a cloud-based computing platform to acquire and analyze yield data. By reusing labor data collected by a cloud-based labor monitoring system that we developed earlier, our system calculates yield data from labor data, and computes yield map in real time and without the overhead for data acquisition. A distinctive feature of our approach is the introduction of a customizable yield distribution function that quantifies the probability of geographic distribution of fruits weighted at a Labor Monitoring Device. Practitioners may define yield distribution functions based on operational characteristics of an orchard, enabling our system adaptive for a variety of orchards with different harvesting operations and canopy architecture. Using a multi-tenancy software architecture, our system can support multiple orchards concurrently with improved scalability and data privacy. Our system has been deployed and tested on Amazon Web Services (AWS).

  • US
  • Washington_State_Univ (US)
Data keywords
  • cloud based
Agriculture keywords
  • farming
Data topic
  • sensors
Document type

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

Institutions 10 co-publis
  • Washington_State_Univ (US)
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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.