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      New approaches for the early detection of tree health pests and pathogens

      Impact

      Science Impact, Ltd.

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          Abstract

          This project aims to develop better methods for detecting tree pests and pathogens that are moving through trade or in the wider environment. The UK is threatened by a large number of invasive tree health threats and new tools are needed to help identify these more rapidly and improve detection efficiency. The technologies explored within the project were:1) ‘Sniffer’ technology to identify volatile chemicals emitted by pests or diseased plants;2) Hyper-spectral imaging techniques that can detect changes in diseased plants beyond the range of human vision;3) Novel traps for capturing insects;4) DNA-based detection approaches for identifying air- and water-borne pathogens.A key feature of the project was that it was interdisciplinary, with social researchers, modellers and economists working alongside scientists and engineers to deliver effective solutions to help a range of end-users, including plant health inspectors and industry representatives, achieve more effective surveillance and improved biosecurity. This joined-up approach has been explored through the Learning Platform (LP), which had three key research objectives:1) Research on stakeholder perspectives and practices and potential economic impacts;2) Conducting socio-technological Learning Labs (SLLs) to assist the co-design of socially acceptable technologies;3) Supporting the learning within and between WPs through a monitoring and evaluation framework.Overall through the LP we have gained a deeper understanding of the innovation process and how this can be used to improve the development and deployment of new technologies.

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          Author and article information

          Journal
          Impact
          impact
          Science Impact, Ltd.
          2398-7073
          September 01 2017
          September 01 2017
          : 2017
          : 7
          : 47-49
          Article
          10.21820/23987073.2017.7.47
          © 2017

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Earth & Environmental sciences, Medicine, Computer science, Agriculture, Engineering

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