Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform

In this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages—all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response value...

Full description

Bibliographic Details
Main Authors: Zhebo Wei, Xize Xiao, Jun Wang, Hui Wang
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/17/11/2500
id doaj-4d227244f9fc4ec3860d761b35eb26af
record_format Article
spelling doaj-4d227244f9fc4ec3860d761b35eb26af2020-11-25T00:15:36ZengMDPI AGSensors1424-82202017-10-011711250010.3390/s17112500s17112500Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage PlatformZhebo Wei0Xize Xiao1Jun Wang2Hui Wang3Department of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, ChinaDepartment of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, ChinaDepartment of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, ChinaDepartment of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, ChinaIn this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages—all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response values were transmitted to the Smartphone thorough a wireless communication module. Then, Aliyun worked as a cloud storage platform for the storage of responses and identification models. The measurement of the E-nose was composed of the taste information obtained phase (TIOP) and the aftertaste information obtained phase (AIOP). The area feature data obtained from the TIOP and the feature data obtained from the TIOP-AIOP were applied to identify rice wines by using pattern recognition methods. Principal component analysis (PCA), locally linear embedding (LLE) and linear discriminant analysis (LDA) were applied for the classification of those wine samples. LDA based on the area feature data obtained from the TIOP-AIOP proved a powerful tool and showed the best classification results. Partial least-squares regression (PLSR) and support vector machine (SVM) were applied for the predictions of marked ages and SVM (R2 = 0.9942) worked much better than PLSR.https://www.mdpi.com/1424-8220/17/11/2500rice winemarked ageSmartphoneelectronic nose
collection DOAJ
language English
format Article
sources DOAJ
author Zhebo Wei
Xize Xiao
Jun Wang
Hui Wang
spellingShingle Zhebo Wei
Xize Xiao
Jun Wang
Hui Wang
Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform
Sensors
rice wine
marked age
Smartphone
electronic nose
author_facet Zhebo Wei
Xize Xiao
Jun Wang
Hui Wang
author_sort Zhebo Wei
title Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform
title_short Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform
title_full Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform
title_fullStr Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform
title_full_unstemmed Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform
title_sort identification of the rice wines with different marked ages by electronic nose coupled with smartphone and cloud storage platform
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2017-10-01
description In this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages—all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response values were transmitted to the Smartphone thorough a wireless communication module. Then, Aliyun worked as a cloud storage platform for the storage of responses and identification models. The measurement of the E-nose was composed of the taste information obtained phase (TIOP) and the aftertaste information obtained phase (AIOP). The area feature data obtained from the TIOP and the feature data obtained from the TIOP-AIOP were applied to identify rice wines by using pattern recognition methods. Principal component analysis (PCA), locally linear embedding (LLE) and linear discriminant analysis (LDA) were applied for the classification of those wine samples. LDA based on the area feature data obtained from the TIOP-AIOP proved a powerful tool and showed the best classification results. Partial least-squares regression (PLSR) and support vector machine (SVM) were applied for the predictions of marked ages and SVM (R2 = 0.9942) worked much better than PLSR.
topic rice wine
marked age
Smartphone
electronic nose
url https://www.mdpi.com/1424-8220/17/11/2500
work_keys_str_mv AT zhebowei identificationofthericewineswithdifferentmarkedagesbyelectronicnosecoupledwithsmartphoneandcloudstorageplatform
AT xizexiao identificationofthericewineswithdifferentmarkedagesbyelectronicnosecoupledwithsmartphoneandcloudstorageplatform
AT junwang identificationofthericewineswithdifferentmarkedagesbyelectronicnosecoupledwithsmartphoneandcloudstorageplatform
AT huiwang identificationofthericewineswithdifferentmarkedagesbyelectronicnosecoupledwithsmartphoneandcloudstorageplatform
_version_ 1725385947136131072