Novel technologies for the detection of Fusarium head blight disease and airborne inoculum

A - Papers appearing in refereed journals

West, J. S., Canning, G., Perryman, S. A. M. and King, K. M. 2017. Novel technologies for the detection of Fusarium head blight disease and airborne inoculum. Tropical Plant Pathology. 42 (3), pp. 203-209.

AuthorsWest, J. S., Canning, G., Perryman, S. A. M. and King, K. M.
Abstract

Many pathogens are dispersed by airborne spores, which can vary in space and time. We can use air sampling integrated with suitable diagnostic methods to give a rapid warning of inoculum presence to improve the timing of control options, such as fungicides. Air sampling can also be used to monitor changes in genetic traits of pathogen populations such as the race structure or frequency of fungicide resistance. Although some image-analysis methods are possible to identify spores, in many cases, species-specific identification can only be achieved by DNA-based methods such as qPCR and LAMP and in some cases by antibody-based methods (lateral flow devices) and biomarker-based methods (‘electronic noses’ and electro-chemical biosensors). Many of these methods also offer the prospect of rapid on-site detection to direct disease control decisions. Thresholds of spore concentrations that correspond to a disease risk depend on the sampler (spore-trap) location (whether just above the crop canopy, on a UAV or drone, or on a tall building) and also need to be considered with weather-based infection models. Where disease control by spore detection is not possible, some diseases can be detected at early stages using optical sensing methods, especially chlorophyll fluorescence. In the case of Fusarium infections on wheat, it is possible to map locations of severe infections, using optical sensing methods, to segregate harvesting of severely affected areas of fields to avoid toxins entering the food chain. This is most useful where variable crop growth or microclimates within fields generate spatially variable infection, i.e. parts of fields that develop disease, while other areas have escaped infection and do not develop any disease.

KeywordsDisease risk; Spore-trap; qPCR; LAMP; Optical sensing
Year of Publication2017
JournalTropical Plant Pathology
Journal citation42 (3), pp. 203-209
Digital Object Identifier (DOI)doi:10.1007/s40858-017-0138-4
Open accessPublished as ‘gold’ (paid) open access
FunderAgriculture and Horticulture Development Board
Innovate UK
Funder project or codeWheat
RD-2140021
RD-2140020105
Optimised Detection and Control of Potato Blight: Sensing Pathogens to Inform Smart Spray Decisions
Agrivision: Development of a system for low cost remotely managed, automated crop stress monitoring and detection
Arable Crop Disease Alert System
Sclerotinia risk live-reporting system for oilseed rape
Innovative disease monitoring and diagnostics for improved efficiency of crop production
Publisher's version
Copyright license
CC BY
Output statusPublished
Publication dates
Online14 Feb 2017
Publication process dates
Accepted02 Feb 2017
PublisherSpringer
ISSN1983-2052

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