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.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Advanced techniques for Weed and crop identification for site specific Weed management (Retracted article. See vol. 111, pg. 139, 2012)
Weed management plays a major role in the production and economic benefits derived by agricultural industry worldwide. The monitoring of weed pressure, economic threshold, yield loss and environmental impact is critical for sustainable agriculture. Currently research is being carried out relating to weed mapping at field scale and the development of machine vision controlled equipment. Remote sensing and aerial imaging techniques utilised for site-specific weed management have limitations due to the accuracy of satellite imagery, its cost and timing. The advent of optoelectronic sensing and enhanced computing has provided a demand for the development of the real-time assessment and management of weeds in fields. The available technologies that can be used for developing a ground-sensor based system to assist in determination of weed pressure and economise on the application of herbicide under field conditions are reviewed. These technologies include image-based identification and spectroscopic methods for weed identification and threshold determination. The various methods studied and the concepts pursued by various researchers are discussed in the paper. Published by Elsevier Ltd on behalf of IAgrE.
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