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dc.contributor.authorKaye, Richard
dc.contributor.authorJohnston, Ian
dc.contributor.authorBaxter, Richard
dc.contributor.authorMunro, Ian
dc.contributor.authorTracey, Mark
dc.contributor.authorDay, Rodney
dc.contributor.authorMcCluskey, Daniel
dc.date.accessioned2023-10-31T11:00:02Z
dc.date.available2023-10-31T11:00:02Z
dc.date.issued2017-03-16
dc.identifier.citationKaye , R , Johnston , I , Baxter , R , Munro , I , Tracey , M , Day , R & McCluskey , D 2017 , ' Development of an automated smart trap for wheat pathogens ' , Innovation in plant biosecurity 2017 , York , United Kingdom , 15/03/17 - 16/02/18 .
dc.identifier.citationconference
dc.identifier.otherORCID: /0000-0001-9696-3191/work/145926076
dc.identifier.otherORCID: /0000-0001-9199-938X/work/145926839
dc.identifier.urihttp://hdl.handle.net/2299/27012
dc.description.abstractNational surveys show fungicide use on wheat continues to increase despite fluctuations in disease pressure, reaching a 30 year high in 2012 (Defra). Septoria tritici is the most significant foliar disease in UK wheat causing between £43M to £53M in yield losses annually; Yellow and brown rust are more sporadic but have caused significant losses during high disease years. In all cases control is by fungicide application costing £82M annually (GFK Kynetec 2013). Effective disease management relies on either prophylactic pesticide use or significant manual intervention and time consuming assessment of crop disease indicators by farmers and agronomists. Furthermore indications are that current levels of pesticide use could lead to increased risk of pesticide resistance, if this should occur it is estimated that wheat yields could reduce by up to 20%. To address this we have developed a prototype integrated and automated spore detection system, designed for unattended field application, to monitor and identify the presence of Septoria, brown and yellow rust. The prototype system incorporates novel cyclonic pathogen collection, on-board sample processing and isothermal DNA amplification chemistry (LAMP). We present the engineering design, optimisation and evaluation of our prototype system reporting on successfully completed laboratory testing and initial field trial results. This prototype will be the basis for the development of a commercially available system which, in addition to inoculum detection, will be capable of providing growers/agronomists with real-time information on inoculum moving into a crop enabling more effective timing and selection of fungicide application, and thus better control, increased yield, and improved environmental stewardship.en
dc.format.extent1
dc.format.extent2869540
dc.language.isoeng
dc.titleDevelopment of an automated smart trap for wheat pathogensen
dc.contributor.institutionDepartment of Engineering and Technology
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionCentre for Research in Biodetection Technologies
dc.contributor.institutionMicro Electro-Mechanical Systems
dc.contributor.institutionMicrofluidics and Microengineering
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionEnterprise and Business Development
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionCentre for Climate Change Research (C3R)
dc.contributor.institutionExtracellular Vesicle Research Unit
dc.contributor.institutionBioEngineering
dc.contributor.institutionCentre for Hazard Detection and Protection Research
dc.contributor.institutionECS Engineering and Technology VLs
dc.contributor.institutionSchool of Engineering and Technology
dc.contributor.institutionSustainable Energy Technologies
dc.contributor.institutionMaterials and Structures
dc.contributor.institutionSPECS Deans Group
dc.description.statusPeer reviewed
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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