T5-05 Early Detection of Campylobacter Using Air Sampling and VOC Analysers

Thursday, 30 March 2017: 11:30
314-316 (The Square)
Tim Gibson, RoboScientific Ltd, Leeds, United Kingdom
Stan Curtis, RoboScientific Ltd, Littleport, United Kingdom
Ben Curtis, RoboScientific Ltd, Littleport, United Kingdom
Lynn McIntyre, Harper Adams University, Newport, United Kingdom
Frank Vriesekoop, Harper Adams University, Newport, United Kingdom
Sarah Hardy, Banham Group Ltd, Attleborough, United Kingdom
Simon Lock-Pender, Banham Group Ltd, Attleborough, United Kingdom
Andrew Stacey, Cellular Systems Ltd, Grantham, United Kingdom
Introduction:  Campylobacter is a gram negative, micro-aerophilic bacterium, present in the gut and faeces of chickens; yet, it does not cause disease in the chickens. It causes food poisoning in humans; and in the UK, up to 280,000 cases per year, leading to 100 deaths, have been reported. It is, also, the most frequently reported foodborne illness in the EU; costing around 2.4billion euros per year due to illness. Early detection to help reduce food contamination would be very useful.

Purpose: The aim of this work was to develop and commercialise a simple field detection system that will enable the onset of Campylobacter in chicken farms to be detected using the volatile chemical profile produced.

Methods:  Air samples from above four chicken flocks were taken, daily, using a µCoriolis air sampler (Bertin Instruments). A volume of 3000 Litres of air was concentrated into 7 ml of distilled water and the resulting aqueous sample was sniffed 4 times using a Bloodhound® volatile analyser (RoboScientific Ltd), containing an array of chemical sensors tuned to the VOCs, associated with presence of Campylobacter. The data obtained was correlated with Campylobacter detection by molecular analysis, using a DNA amplification system.

Results:  Campylobacter detection using the Bloodhound® analyser correlated well with the DNA results and, in each flock, indicated the appearance of active Campylobacter infections in the chickens. Each flock sampled over a 33 to 38 day period showed a significant change in the VOCs detected when Campylobacter was present, indicated by the appearance of different sensor outputs; and, also, after data processing using discriminant analysis, by the clustering of data points remote to the Campylobacter negative samples. Mahalanobis distances jumped from 472 for negative samples to 15,777 for Campylobacter positive samples.

Significance: Early field detection of Campylobacter will provide knowledge to reduce chicken meat contamination by enabling slaughter and processing of negative flocks before positive flocks.