Review of electronic-nose technologies and application for Chinese liquor identification

LI Qiang; GU Yu; WANG Nan-fei; DONG Han

doi:10.13374/j.issn2095-9389.2017.04.001

Volume 39 Issue 4

Apr. 2017

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Engineering > 2017 > 39(4): 475-486

LI Qiang, GU Yu, WANG Nan-fei, DONG Han. Review of electronic-nose technologies and application for Chinese liquor identification[J]. Chinese Journal of Engineering, 2017, 39(4): 475-486. doi: 10.13374/j.issn2095-9389.2017.04.001

Citation:

LI Qiang, GU Yu, WANG Nan-fei, DONG Han. Review of electronic-nose technologies and application for Chinese liquor identification[J]. Chinese Journal of Engineering, 2017, 39(4): 475-486. doi: 10.13374/j.issn2095-9389.2017.04.001

Citation:

PDF( 538 KB)

Review of electronic-nose technologies and application for Chinese liquor identification

doi: 10.13374/j.issn2095-9389.2017.04.001

School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China

Received Date: 2016-11-04

Abstract

Abstract

Due to their sensitivity to a wide diversity of volatile gases, electronic noses are ideal instruments for measuring and monitoring odors and they are being applied in agricultural production testing, biological medicine detection, environmental monitoring, and food testing. An electronic nose (E-nose) utilizes a sensor array to provide a fingerprint response to a given odor, using pattern recognition software to identify and discriminate between odors. Each sensor in the array behaves like a receptor by responding to different odors to varying degrees. The changes are then transduced into electrical signals, which are preprocessed and conditioned before identification by a pattern recognition system. In this paper, recent electronic-nose systems and algorithms are reviewed which developed over the past two decades that have potential applications for detecting Chinese liquors, including brand identification, flavor detection, and the prediction of the ages. In addition, the technical design scheme and the application were detailed for the polymer quartz piezoelectric sensor E-nose.
- sensors,
- electronic nose,
- pattern recognition systems,
- Chinese liquor,
- identification

FullText(HTML)

References(45)

References

[1]	Wilkens W F, Hartman J D. An electronic analog for the olfactory processes. J Food Sci, 1964, 29(3):372
[2]	Gardner J W, Bartlett P N. A brief history of electronic noses. Sens Actuators B, 1994, 18(1):210
[8]	Brekelmans M P, Fens N, Brinkman P, et al. Smelling the diagnosis:the electronic nose as diagnostic tool in inflammatory arthritis. A case-reference study. PLOS One, 2016, 11(3):e0151715
[10]	Tian F C, Zhang J, Yang S X, et al. Suppression of strong background interference on E-nose sensors in an open country environment. Sensors, 2016, 16(2):233
[11]	Chang K P P, Zakaria A, Nasir A S A, et al. Analysis and feasibility study of plant disease using e-nose//2014 IEEE International Conference on Control System, Computing and Engineering. Penang, 2014:58
[17]	Mahanubhav M D, Patil L A. Studies on gas sensing performance of CuO-modified Cdln₂O₄ thick film resistors. Sens Actuators B, 2007, 128(1):186
[19]	Abdallah S A, Al-Shatti L A, Alhajraf A F, et al. The detection of foodborne bacteria on beef:the application of the electronic nose. Springer Plus, 2013, 2:687
[20]	Gong J W. Non-Silicon Microfabricated Nanostructured Chemical Sensors for Electric Nose Application[Dissertation]. Florida:University of Central Florida Orlando, 2005
[23]	Andreeva N, Ishizaki T, Baroch P, et al. High sensitive detection of volatile organic compounds using superhydrophobic quartz crystal microbalance. Sens Actuators B, 2012, 164(1):15
[24]	Latif U, Rohrer A, Lieberzeit P A, et al. QCM gas phase detection with ceramic materials:VOCs and oil vapors. Anal Bioanal Chem, 2011, 400(8):2457
[25]	Das R, Biswas S, Bandyopadhyay R, et al. Polymerized linseed oil coated quartz crystal microbalance for the detection of volatile organic vapours. Sens Actuators B, 2013, 185:293
[26]	Gu Y, Li Q, Tian F F, et al. Structure and absorbability of a nanometer nonmetallic polymer thin film coating on quartz used in piezoelectric sensors. Chin Phys Lett, 2013, 30(10):108101
[27]	Raj V B, Singh H, Nimal A T, et al. Oxide thin films (ZnO, TeO 2, SnO₂, and TiO₂) based surface acoustic wave (SAW) Enose for the detection of chemical warfare agents. Sens Actuators B, 2013, 178:636
[28]	Sunil T T, Chaudhuri S. Detection of target gases and optimal selection of SAW sensors for E-Nose applications//Proceedings of Conference on Advances in Robotics. New York, 2013:1
[29]	Turk M, Pentland A. Eigenfaces for recognition. J Cognitive Neurosci, 1991, 3(1):71
[30]	Singh H, Raj V B, Kumar J, et al. Metal oxide SAW E-nose employing PCA and ANN for the identification of binary mixture of DMMP and methanol. Sens Actuators B, 2014, 200:147
[31]	Santos J P, Lozano J. Real time detection of beer defects with a hand held electronic nose//201510th Spanish Conference on Electron Devices (CDE). Madrid, 2015:1
[32]	Hong X Z, Wang J, Qi G D. E-nose combined with chemometrics to trace tomato-juice quality. J Food Eng, 2015, 149:38
[33]	Guadarrama A, Fernandez J A, Iniguez M, et al. Array of conducting polymer sensors for the characterisation of wines. Anal Chim Acta, 2000, 411(1):193
[35]	Dai Y W, Zhi R C, Zhao L, et al. Longjing tea quality classification by fusion of features collected from E-nose. Chemom Intell Lab Syst, 2015, 144:63
[36]	Thriumani R, Zakaria A, Jeffree A I, et al. A preliminary study on in-vitro lung cancer detection using E-nose technology//2014 IEEE International Conference on Control System, Computing and Engineering (ICCSCE). 2014:601
[37]	Jiang H, Chen Q S, Liu G H. Monitoring of solid-state fermentation of protein feed by electronic nose and chemometric analysis. Process Biochem, 2014, 49(4):583
[39]	Gu Y, Li Q. Application of the new pattern recognition system in the new e-nose to detecting Chinese spirits. Chin Phys B, 2014, 23(4):044213
[40]	Zeng H, Li Q, Gu Y. New pattern recognition system in the Enose for Chinese spirit identification. Chin Phys B, 2016, 25(2):024201
[41]	Abdullah A A, Yusuf N, Zakaria A, et al. Bacteria classification using electronic nose for diabetic wound monitoring. Appl Mech Mater, 2013, 339:167
[42]	Li H H, Chen Q S, Zhao J W, et al. Non-destructive evaluation of pork freshness using a portable electronic nose (E-nose) based on a colorimetric sensor array. Anal Methods, 2014, 6:6271
[44]	Belhumeur P N, Hespanha J P, Kriegman D J. Eigenfaces vs. fisherfaces:recognition using class specific linear projection. IEEE Trans Pattern Anal Mach Intell, 1997, 19(7):711
[45]	Cortes C, Vapnik V. Support-vector networks. Mach Learn, 1995, 20(3):273
[46]	Yusuf N, Omar M I, Zakaria A, et al. Diagnosis of bacteria for diabetic foot infection using electronic nose technology//2013IEEE Conference on Wireless Sensor (ICWISE). Sarawak, 2013:114
[47]	Yin X, Zhang L, Tian F C, et al. Temperature modulated gas sensing E-nose system for low-cost and fast detection. IEEE Sens J, 2016, 16(2):464
[48]	Wang X R, Lizier J T, Berna A Z, et al. Human breath-print identification by E-nose, using information-theoretic feature selection prior to classification. Sens Actuators B, 2015, 217:165
[49]	Chen Q S, Hui Z, Zhao J W, et al. Evaluation of chicken freshness using a low-cost colorimetric sensor array with AdaBoostOLDA classification algorithm. LWT Food Sci Technol, 2014, 57(2):502
[50]	Urmila K, Li H H, Chen Q S, et al. Quantifying of total volatile basic nitrogen (TVB——N) content in chicken using a colorimetric sensor array and nonlinear regression tool. Anal Methods, 2015, 7:5682
[51]	Bansal P. Analysis and Classification of Drift Susceptible Chemosensory Response[Dissertation]. Texas:University of Texas, 2014
[52]	Yu H C, Wang J, Yao C, et al. Quality grade identification of green tea using E-nose by CA and ANN. LWT Food Sci Technol, 2008, 41(7):1268
[53]	Zhang L, Tian F C, Liu S Q, et al. Chaotic time series prediction of E-nose sensor drift in embedded phase space. Sens Actuators B, 2013, 182:71
[54]	Breijo E G, Guarrasi V, Peris R M, et al. Odour sampling system with modifiable parameters applied to fruit classification. J Food Eng, 2013, 116(2):277
[55]	Gardner J W, Shin H W, Hines E L, et al. An electronic nosesystem for monitoring the quality of potable water. Sens Actuators B, 2000, 69(3):336
[56]	Aleixandre M, Santos J P, Sayago I, et al. A wireless and portable electronic nose to differentiate musts of different ripeness degree and grape varieties. Sensors, 2015, 15(4):8429
[61]	Jing Y, Meng Q, Qi P, et al. Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification. Rev Sci Instrum, 2014, 85(5):055004
[62]	Qin H, Huo D, Zhang L, et al. Colorimetric artificial nose for identification of Chinese liquor with different geographic origins. Food Res Int, 2012, 45(1):45
[64]	Xiao Z, Yu D, Niu Y, et al. Characterization of aroma compounds of Chinese famous liquors by gas chromatography-mass spectrometry and flash GC electronic-nose. J Chromatogr B, 2014, 945:92
[65]	Liu M, Han X, Tu K, et al. Application of electronic nose in Chinese spirits quality control and flavour assessment. Food Control, 2012, 26(2):564
[71]	Gu Y, Li Q, Xu B J, et al. Vibration analysis of new polymer quartz piezoelectric crystal sensor for detecting characteristic materials of volatility liquid. Chin Phys B, 2014, 23(1):017804
[72]	Gu Y, Li Q. Preparation and characterization of PTFE coating of new polymer quartz piezoelectric crystal sensor for testing Chinese spirits. Chin Phys B, 2015, 24(7):078106