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
Analysis of Early Host Responses for Asymptomatic Disease Detection and Management of Specialty Crops
The rapid and unabated spread of vector-borne diseases within US specialty crops threatens our agriculture, our economy, and the livelihood of growers and farm workers. Early detection of vector-borne pathogens is an essential step for the accurate surveillance and management of vector-borne diseases of specialty crops. Currently, we lack the tools that would detect the infectious agent at early (primary) stages of infection with a high degree of sensitivity and specificity. In this paper, we outline a strategy for developing an integrated suite of platform technologies to enable rapid, early disease detection and diagnosis of huanglong-bing (HLB), the most destructive citrus disease. The research has two anticipated outcomes: i) identification of very early, disease-specific biomarkers using a knowledge base of translational genomic information on host and pathogen responses associated with early (asymptomatic) disease development; and ii) development and deployment of novel sensors that capture these and other related biomarkers and aid in presymptomatic disease detection. By combining these two distinct approaches, it should be possible to identify and defend the crop by interdicting pathogen spread prior to the rapid expansion phase of the disease. We believe that similar strategies can also be developed for the surveillance and management of diseases affecting other economically important specialty crops.
Inappropriate format for Document type, expected simple value but got array, please use list format