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Review
. 2020 Jun;57(6):1977-1990.
doi: 10.1007/s13197-019-04143-4. Epub 2019 Nov 5.

Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

Ernest Bonah  1   2 , Xingyi Huang  1 , Joshua Harrington Aheto  1 , Richard Osae  1
Affiliations
Review

Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

Ernest Bonah et al. J Food Sci Technol. 2020 Jun.

Abstract

Food safety issues across the global food supply chain have become paramount in promoting public health safety and commercial success of global food industries. As food regulations and consumer expectations continue to advance around the world, notwithstanding the latest technology, detection tools, regulations and consumer education on food safety and quality, there is still an upsurge of foodborne disease outbreaks across the globe. The development of the Electronic nose as a noninvasive technique suitable for detecting volatile compounds have been applied for food safety and quality analysis. Application of E-nose for pathogen detection has been successful and superior to conventional methods. E-nose offers a method that is noninvasive, fast and requires little or no sample preparation, thus making it ideal for use as an online monitoring tool. This manuscript presents an in-depth review of the application of electronic nose (E-nose) for food safety, with emphasis on classification and detection of foodborne pathogens. We summarise recent data and publications on foodborne pathogen detection (2006-2018) and by E-nose together with their methodologies and pattern recognition tools employed. E-nose instrumentation, sensing technologies and pattern recognition models are also summarised and future trends and challenges, as well as research perspectives, are discussed.

Keywords: Electronic nose; Foodborne pathogens; Pattern recognition; Sensors; Volatile organic compounds (VOCs).

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Conflict of interest statement

Conflict of interestThe authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
a A fabricated E-nose machine for online detection at Jiangsu University, b commercial E-nose machine, Airsense PEN3 (Airsense Analytics GmbH, Schwerin, Germany)
Fig. 2
Fig. 2
Stages of classic signal processing of electronic nose data by Gutierrez-Osuna and Nagle (1999)
Fig. 3
Fig. 3
Sampling, detection and analysis of volatiles by E-nose
Fig. 4
Fig. 4
Categories of chemical classes of VOCs for bacterial identification
See this image and copyright information in PMC

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