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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Image Repainted Method of Overlapped Leaves for Orchid Leaf Area Estimation


Currently, Internet of Things (loT) has become a hot issue. For agriculture, loT techniques bring many advantages, such as lowering the time consumed and the manpower required by real time data collection. Taiwan is one of the main orchid exporters in the world, and orchid export accounts for over 70% of the total floral export in Taiwan, and the species of phalaenopsis accounts for 60 % of the floral export. In a previous study, the loT technique was utilized to automatically measure environmental factors and orchid leaf traits. An automatic image collecting system and an image processing method were employed to calculate the leaf area and the growth rate of the leaf area which was positively related to the blooming quality. However, when calculating the leaf area, the overlapping leaves caused inaccurate results. To solve this problem, this paper proposes a method to repaint the overlapped area. The leaves of orchids are symmetrical, and this feature is utilized to obtain the overlapped area and repaint the area. Finally, two data sets of processed images are collected to verify the proposed method. This paper provides an effective method of repainting overlapped leaf areas. Using the proposed method and the leaf area estimation method can reduce the error caused by leaf overlapping and increase the accuracy of leaf area estimation and growth rate calculation.

  • TW
  • Natl_Taiwan_Univ_NTU (TW)
Data keywords
  • internet of things
Agriculture keywords
  • agriculture
Data topic
  • big data
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.