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
Feed intake, feeding and rumination time are important parameters in the identification of suboptimal feeding conditions and possible health disorders. The automatic recording of individual feeding behavior constitutes a reasonable tool for early detection of deviations in feeding behavior and feeding deficiencies. For this reason, a new system for measuring feeding behavior of dairy cows has been developed. The sensor-based system DairyCheck consists of a halter with two incorporated electrodes, a data logger, an accelerometer, power supply, and evaluation software. Measurement of feeding behavior ensues through surface electromyography (EMG), whereby electrical potential oscillations during jaw movements are recorded. Data are transmitted directly via radio transmission to a computer with automatic evaluation software. Automatic analysis software is based on an algorithm to identify single jaw movements and differentiate between active feeding phases and non-active dormant phases. For validation, feeding behavior of 14 cows as determined by both the EMG system and visual observation was analyzed. Results showed adequate agreement of the results of both assessments. However, further progress and research are necessary for automatic data interpretation with a self-learning algorithm, to develop this EMG-based system into an appropriate management tool in the field of precision dairy farming. (C) 2014 Elsevier B.V. All rights reserved.
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