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
Accurate recognition of agricultural activity has a direct bearing on improving farm productivity in terms of achieving crop yield improvements, imparting precision training to farmers wherever needed, and measuring their efforts. Moreover, farm activities are not independent of each other. Cultivation of any crop is associated with a defined pattern of farmer activities called the crop protocol. With an indigenously developed garment for the farmer called smart-shirt, we propose a model for activity classification which has a mean activity prediction accuracy of over 88% for seven classes. The performance of numerous classifiers SVM, Naive Byes, K-NN, LDA and QDA is rigorously evaluated and compared for activity prediction. We also propose a model to use the a priori information associated with the crop protocol to recognize the major activity when presented with an unclear evidence of reported activities.
Inappropriate format for Document type, expected simple value but got array, please use list format