Rapid Non-Destructive Quantification of Eugenol in Curdlan Biofilms by Electronic Nose Combined with Gas Chromatography-Mass Spectrometry

Eugenol is hepatotoxic and potentially hazardous to human health. This paper reports on a rapid non-destructive quantitative method for the determination of eugenol concentration in curdlan (CD) biofilms by electronic nose (E-nose) combined with gas chromatography-mass spectrometry (GC-MS). Differen...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2020-08, Vol.20 (16), p.4441
Main Authors: Han, Lu, Zhu, Jingyi, Fan, Xia, Zhang, Chong, Tu, Kang, Peng, Jing, Wang, Jiahong, Pan, Leiqing
Format: Article
Language:English
Subjects:
beta-Glucans
biofilm
Biofilms
Chromatography
curdlan
Discriminant analysis
Electronic Nose
Electronic noses
Eugenol
Food
Gas chromatography
Gas Chromatography-Mass Spectrometry
GC-MS
Glycerol
Humans
Mass spectrometry
Methods
Nondestructive testing
Odorants - analysis
prediction model
Prediction models
Principal components analysis
Quantitative analysis
Scientific imaging
Sensors
Spectroscopy
Support vector machines
Volatility
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Summary:Eugenol is hepatotoxic and potentially hazardous to human health. This paper reports on a rapid non-destructive quantitative method for the determination of eugenol concentration in curdlan (CD) biofilms by electronic nose (E-nose) combined with gas chromatography-mass spectrometry (GC-MS). Different concentrations of eugenol were added to the film-forming solution to form a series of biofilms by casting method, and the actual eugenol concentration in the biofilm was determined. Analysis of the odor collected on the biofilms was carried out by GC-MS and an E-nose. The E-nose data was subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) in order to establish a discriminant model for determining eugenol concentrations in the biofilms. Further analyses involving the application of all sensors and featured sensors, the prediction model-based partial least squares (PLS) and support vector machines (SVM) were carried out to determine eugenol concentration in the CD biofilms. The results showed that the optimal prediction model for eugenol concentration was obtained by PLS at R of 0.952 using 10 sensors. The study described a rapid, non-destructive detection and quantitative method for determining eugenol concentration in bio-based packaging materials.
ISSN:1424-8220
1424-8220
DOI:10.3390/s20164441