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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Automatic identification of two growth stages for rapeseed plant: Three leaf and Four Leaf Stage


As an indispensable technology of agricultural development in the world, digital agriculture is the coalition of agriculture and modern information technology together with artificial intelligence technology. As one of the most important aspects of digital agriculture, crop growth monitoring requires for non-destructive real-time and accurate access to plant growth information in order to guide fine management of crop. Among them, monitoring of crop in different periods is an important component of plant growth monitoring. In this study, a computer pattern recognition method - ASM (Active shape model) is employed to automatically identify whether the rapeseed plant has reached three-leaf stage and four-leaf stage or not. Frist, the rapeseed plant blades are manually marked on the training samples. Then, all the blade models are aligned to obtain an averaged shape model, which is utilized as the geometric shape model. Finally, the averaged model is employed to search in the rapeseed plant image. Once the matched geometric model is found in the rapeseed plant image, the conclusion that the rapeseed plant has reached three-leaf stage and four-leaf stage will be drawn. Experiments are conducted on real images and the proposed method produce similar observation results comparing with the manual observation method. Therefore, the automated identification method can meet the demand for practical observation needed for agronomic modeling and in triggering action alerts to farmers.

  • CN
  • Huazhong_Agr_Univ (CN)
Data keywords
  • information technology
Agriculture keywords
  • agriculture
Data topic
  • information systems
  • modeling
  • sensors
Document type

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

Institutions 10 co-publis
  • Huazhong_Agr_Univ (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.