Portability is a major issue that influences the practical application of electronic noses (e-noses). For liquors detection, an e-nose must preprocess the liquid samples (e.g., using evaporation and thermal desorption), which makes the portable design even more difficult. To realize convenient and rapid detection of liquors, we designed a portable e-nose platform that consists of hardware and software systems. The hardware system contains an evaporation/sampling module, a reaction module, a control/data acquisition and analysis module, and a power module. The software system provides a user-friendly interface and can achieve automatic sampling and data processing. This e-nose platform has been applied to the real-fake recognition of Chinese liquors. Through parameter optimization of a one-class support vector machine classifier, the error rate of the negative samples is greatly reduced, and the overall recognition accuracy is improved. The results validated the feasibility of the designed portable e-nose platform.

1.
N.
Prieto
,
M. L.
Rodriguez-Méndez
,
R.
Leardi
,
R.
Oliveri
,
D.
Hernando-Esquisabel
,
M.
Iniguez-Crespo
, and
J. A.
Saja
, “
Application of multi-way analysis to UV–visible spectroscopy, gas chromatography and electronic nose data for wine ageing evaluation
,”
Anal. Chim. Acta
719
,
43
51
(
2012
).
2.
H. X.
Wang
,
Z. Q.
Hu
,
F. Y.
Long
,
C. F.
Guo
,
Y. H.
Yuan
, and
T. L.
Yue
, “
Early detection of Zygosaccharomyces rouxii—spawned spoilage in apple juice by electronic nose combined with chemometrics
,”
Int. J. Food Microbiol.
217
,
68
78
(
2016
).
3.
C.
Cevoli
,
L.
Cerretani
,
A.
Gori
,
M. F.
Caboni
,
T.
Gallina Toschi
, and
A.
Fabbri
, “
Classification of Pecorino cheeses using electronic nose combined with artificial neural network and comparison with GC-MS analysis of volatile compounds
,”
Food Chem.
129
,
1315
1319
(
2011
).
4.
H.
Knobloch
,
W.
Schroedl
,
C.
Turner
,
M.
Chambers
, and
P.
Reinhold
, “
Electronic nose responses and acute phase proteins correlate in blood using a bovine model of respiratory infection
,”
Sens. Actuators, B
144
,
81
87
(
2010
).
5.
Y. Q.
Jing
,
Q. H.
Meng
,
P. F.
Qi
,
M.
Zeng
,
W.
Li
, and
S. G.
Ma
, “
Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification
,”
Rev. Sci. Instrum.
85
,
055004
(
2014
).
6.
J. W.
Gardner
and
P. N.
Bartlett
, “
A brief history of electronic noses
,”
Sens. Actuators, B
18
,
210
211
(
1994
).
7.
T. M.
Dymerski
,
T. M.
Chmiel
, and
W.
Wardencki
, “
Invited Review Article: An odor-sensing system—powerful technique for foodstuff studies
,”
Rev. Sci. Instrum.
82
,
111101
(
2011
).
8.
L.
Buck
and
R.
Axel
, “
A novel multigene family may encode odorant receptors: A molecular basis for odor recognition
,”
Cell
65
,
175
187
(
1991
).
9.
E.
Nozza
,
L.
Capelli
,
L.
Eusebio
,
M.
Derudi
,
G.
Nano
,
R. D.
Rosso
, and
S.
Sironi
, “
The role of bioethanol flueless fireplaces on indoor air quality: Focus on odour emissions
,”
Build. Environ.
98
,
98
106
(
2016
).
10.
T.
Dymerski
,
J.
Gębicki
,
W.
Wardencki
, and
J.
Namieśnik
, “
Quality evaluation of agricultural distillates using an electronic nose
,”
Sensors
13
,
15954
15967
(
2013
).
11.
J. C.
Lei
,
C. J.
Hou
,
D. Q.
Huo
,
X. G.
Luo
,
M. Z.
Bao
,
X.
Li
,
M.
Yang
, and
H. B.
Fa
, “
A novel device based on a fluorescent cross-responsive sensor array for detecting lung cancer related volatile organic compounds
,”
Rev. Sci. Instrum.
86
,
025106
(
2015
).
12.
P.
Sharma
,
A.
Ghosh
,
B.
Tudu
,
S.
Sabhapondit
,
B. D.
Baruah
,
P.
Tamuly
,
N.
Bhattacharyya
, and
R.
Bandyopadhyay
, “
Monitoring the fermentation process of black tea using QCM sensor based electronic nose
,”
Sens. Actuators, B
219
,
146
157
(
2015
).
13.
L. C.
Wang
,
K. T.
Tang
,
S. W.
Chiu
,
S. R.
Yang
, and
C. T.
Kuo
, “
A bio-inspired two-layer multiple-walled carbon nanotube–polymer composite sensor array and a bio-inspired fast-adaptive readout circuit for a portable electronic nose
,”
Biosens. Bioelectron.
26
,
4301
4307
(
2011
).
14.
T. A.
Vincent
and
J. W.
Gardner
, “
A low cost MEMS based NDIR system for the monitoring of carbon dioxide in breath analysis at ppm levels
,”
Sens. Actuators, B
236
,
954
964
(
2016
).
15.
F.
Hossein-Babaei
,
M.
Paknahad
, and
V.
Ghafarinia
, “
A miniature gas analyzer made by integrating a chemoresistor with a microchannel
,”
Lab Chip
12
,
1874
1880
(
2012
).
16.
M.
Ghasemi-Varnamkhasti
,
S. S.
Mohtasebi
,
M.
Siadat
,
J.
Lozano
,
H.
Ahmadi
,
S. H.
Razavi
, and
A.
Dicko
, “
Aging fingerprint characterization of beer using electronic nose
,”
Sens. Actuators, B
159
,
51
59
(
2011
).
17.
L. M.
Manevitz
and
M.
Yousef
, “
One-class SVMs for document classification
,”
J. Mach. Learn. Res.
2
,
139
154
(
2001
).
18.
B.
Schölkopf
,
J. C.
Platt
,
J. C.
Shawe-Taylor
,
A. J.
Smola
, and
R. C.
Williamson
, “
Estimating the support of a high-dimensional distribution
,”
Neural Comput.
13
,
1443
1471
(
2001
).
19.
J.
Robert
, “
Kernel entropy component analysis
,”
IEEE Trans. Pattern Anal. Mach. Intell.
32
(
5
),
847
860
(
2009
).
You do not currently have access to this content.