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Analytical Methods Vol - 9 Issue - 5

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Sensor array optimization and discrimination of apple juices according to variety by an electronic nose

Content Provider	Royal Society of Chemistry (RSC)
Author	Wu, Hao Yue, TianLi Zhang, Chen Xu, Zhijiao
Copyright Year	2017
Abstract	An electronic nose (PEN3) containing 10 metal oxide semiconductor type chemical sensors (W1C, W5S, W3C, W6S, W5C, W1S, W1W, W2S, W2W and W3S) was used to discriminate between eight varieties of apple juice. Sensor array optimization was carried out to eliminate irrelevant, redundant information and improve discrimination accuracy. Traditional ANOVA and loading analysis methods and the Wilks statistics method were conducted and sensors sensitive to aroma compounds were selected to optimize the sensor array. Three optimized sensor sets were obtained. PCA, k-means clustering and SVM were proposed to analyze the original and optimized sensor signals. An exploratory overview using the PCA-based pattern showed that optimized set 2 W5S, W5C, W1W and W3S obtained using the Wilks statistics method performed best. The Wilks statistics method was proven to be a useful tool for sensor array optimization by weighing up the sensors' discriminatory ability. This result was further demonstrated using k-means clustering analysis. The SVM method achieved better discrimination performance in comparison with the PCA-based pattern. SVM revealed satisfactory discrimination of apple juices, provided a 100% success training rate and a 98.33–100% success testing rate. The optimization sensor array was demonstrated to be able to improve the discriminatory performance of EN. The results obtained indicated that EN can be successfully applied to apple juice discrimination.
Starting Page	921
Ending Page	928
Page Count	8
File Format	HTM / HTML PDF
ISSN	17599660
Volume Number	9
Issue Number	6
Journal	Analytical Methods
DOI	10.1039/c6ay02610a
Language	English
Publisher	Royal Society of Chemistry
Access Restriction	Open
Subject Keyword	Semiconductor Apple juice Electronic nose Wilks World Wide Web Consortium Sensor array W2W Mathematical optimization Analysis of variance K-means clustering PCA
Content Type	Text
Resource Type	Article
Subject	Analytical Chemistry Engineering Chemical Engineering

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World wide web consortium. (1999).

2 world wide web consortium ( ) ja universaalit web-standardit world wide web consortium (w3c).

Sensor array optimization and discrimination of apple juices according to variety by an electronic nose

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