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
The Actualities and Prospects of Ultrasound-based Pattern Recognition in Crop Feature Extraction
With the advances in information technology and electronics, various intelligent agricultural machines and equipments have been developed for crop production during pre-harvest, harvest and post-harvest stages, respectively. Accurate information about the crop feature parameters is very important for precision agriculture in crop production. Sensing techniques and systems for measuring crop parameters with an acceptable accuracy and high reliability at a reasonable price are essential prerequisite for obtaining this information. Ultrasound, as a nondestructive, fast and reliable technique, can be used to measure the parameters of crop. Utilizing the pattern recognition technique, canopy volume, crop biomass and fruit maturity state can be determined based on these parameters. This paper reviewed the developments in ultrasound-based pattern recognition system for extracting feature of crop over the past decades up to 2010. The current status of ultrasonic systems was described in the context of commercial application. Some of the challenges and considerations on the use of the sensor and technology for specialty crop production are also discussed. Emphases are placed on the technology that have been proven effective or have shown great potential for crop feature extraction.
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