Comparison of the performance of metal oxide and conducting polymer electronic noses for detection of aflatoxin using artificially contaminated maize

Machungo, C; Berna, AZ; McNevin, D; Wang, R; Trowell, S

Comparison of the performance of metal oxide and conducting polymer electronic noses for detection of aflatoxin using artificially contaminated maize

Machungo, C Berna, AZ McNevin, D

Wang, R Trowell, S

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Publisher:: ELSEVIER SCIENCE SA
Publication Type:: Journal Article
Citation:: Sensors and Actuators B: Chemical, 2022, 360
Issue Date:: 2022-06-01

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Field	Value	Language
dc.contributor.author	Machungo, C
dc.contributor.author	Berna, AZ
dc.contributor.author	McNevin, D https://orcid.org/0000-0003-1665-3367
dc.contributor.author	Wang, R
dc.contributor.author	Trowell, S
dc.date.accessioned	2022-07-26T07:56:13Z
dc.date.available	2022-07-26T07:56:13Z
dc.date.issued	2022-06-01
dc.identifier.citation	Sensors and Actuators B: Chemical, 2022, 360
dc.identifier.issn	0925-4005
dc.identifier.issn	0925-4005
dc.identifier.uri	http://hdl.handle.net/10453/159179
dc.description.abstract	The electronic nose offers potential as a rapid and cost effective field portable diagnostic device that would allow for quick screening of produce for aflatoxin contamination at the market entry level. This study aimed to compare the performance of three electronic nose sensor technologies: metal oxide semiconductor sensors (Fox 3000), conducting polymer sensors (Cyranose 320) and doped metal oxide semiconductor sensors with thermocycling (DiagNose), for the detection of volatiles associated with maize contaminated with aflatoxins. Australian maize (variety DK703w) samples were artificially inoculated with aflatoxigenic and non-aflatoxigenic Aspergillus flavus isolates and 2 % v/v Tween 20 as a control. Mutual information was used to select features from the electronic nose sensor signals for classification of the samples. The effectiveness, of selected features to discriminate between the different classes of samples was evaluated by support vector machines and k-nearest neighbour with leave-one-out cross-validation. Cross-validated classification accuracy for the different sample classes ranged from 81 % to 94 % for DiagNose, 76 to 79 % for Fox 3000 and 68 to 75 % for Cyranose. The results suggest that an electronic nose equipped with doped metal oxide semiconductor sensors and thermocycling is more effective for detection of aflatoxin contamination of maize.
dc.language	English
dc.publisher	ELSEVIER SCIENCE SA
dc.relation.ispartof	Sensors and Actuators B: Chemical
dc.relation.isbasedon	10.1016/j.snb.2022.131681
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0205 Optical Physics, 0301 Analytical Chemistry, 0912 Materials Engineering
dc.subject.classification	Analytical Chemistry
dc.title	Comparison of the performance of metal oxide and conducting polymer electronic noses for detection of aflatoxin using artificially contaminated maize
dc.type	Journal Article
utslib.citation.volume	360
utslib.for	0205 Optical Physics
utslib.for	0301 Analytical Chemistry
utslib.for	0912 Materials Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CFS - Centre for Forensic Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-26T07:56:08Z
pubs.publication-status	Published
pubs.volume	360

Abstract:

The electronic nose offers potential as a rapid and cost effective field portable diagnostic device that would allow for quick screening of produce for aflatoxin contamination at the market entry level. This study aimed to compare the performance of three electronic nose sensor technologies: metal oxide semiconductor sensors (Fox 3000), conducting polymer sensors (Cyranose 320) and doped metal oxide semiconductor sensors with thermocycling (DiagNose), for the detection of volatiles associated with maize contaminated with aflatoxins. Australian maize (variety DK703w) samples were artificially inoculated with aflatoxigenic and non-aflatoxigenic Aspergillus flavus isolates and 2 % v/v Tween 20 as a control. Mutual information was used to select features from the electronic nose sensor signals for classification of the samples. The effectiveness, of selected features to discriminate between the different classes of samples was evaluated by support vector machines and k-nearest neighbour with leave-one-out cross-validation. Cross-validated classification accuracy for the different sample classes ranged from 81 % to 94 % for DiagNose, 76 to 79 % for Fox 3000 and 68 to 75 % for Cyranose. The results suggest that an electronic nose equipped with doped metal oxide semiconductor sensors and thermocycling is more effective for detection of aflatoxin contamination of maize.

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http://hdl.handle.net/10453/159179