食品与发酵工业 >

2019 , Vol. 45 >Issue 2: 190 - 195

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.018206

分析与检测

基于电子鼻系统的白酒掺假检测方法

  • 马泽亮 ,
  • 国婷婷 ,
  • 殷廷家 ,
  • 王志强 ,
  • 杨方旭 ,
  • 李彩虹 ,
  • 李钊 ,
  • 袁文浩
展开
  • (山东理工大学 计算机科学与技术学院,山东 淄博,255049)
硕士研究生(王志强副教授为通讯作者,E-mail:wzq@sdut.edu.cn)。

收稿日期: 2018-07-05

  网络出版日期: 2019-02-21

基金资助

国家自然科学基金项目(61473179,61701286);山东省自然科学基金项目(ZR2018LF002,ZR2015FL003);赛尔网络下一代互联网技术创新项目(NGII20170314)

收起

Detection of liquor adulteration based on the electronic nose system

  • MA Zeliang ,
  • GUO Tingting ,
  • YIN Tingjia ,
  • WANG Zhiqiang ,
  • YANG Fangxu ,
  • LI Caihong ,
  • LI Zhao ,
  • YUAN Wenhao
Expand
  • (School of Computer Science and Technology, Shandong University of Technology,Zibo 255049, China)

Received date: 2018-07-05

  Online published: 2019-02-21

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摘要

采用自行研制的便携式电子鼻检测系统,建立了一种能够快速辨别白酒掺假的新方法。系统检测时:首先利用传感器阵列获得白酒“指纹数据”,随后通过离散小波变换(discrete wavelet transform,DWT)提取反馈信息里的特征信息,然后采用主成分分析(principal component analysis,PCA)实现对不同纯度掺假白酒样品的定性判别、采用人工蜂群优化最小二乘支持向量机(artificial bee colony least squared support vector machines,ABC-LSSVM)实现对不同纯度掺假白酒样品的定量预测。结果表明, PCA对掺假白酒区分效果较好,区分正确率高达100%;ABC-LSSVM预测模型对白酒纯度具有较高的定量预测性能,其验证集中相关系数R2为0.933 2,平均绝对误差MRE为6.564 3%,均方根误差RMSE为 0.023 4。该研究可为掺假白酒的定性辨别及定量预测提供技术支持。

关键词： 电子鼻; 白酒掺假; 离散小波变换; 人工蜂群优化最小二乘支持向量机

本文引用格式

马泽亮 , 国婷婷 , 殷廷家 , 王志强 , 杨方旭 , 李彩虹 , 李钊 , 袁文浩 . 基于电子鼻系统的白酒掺假检测方法[J]. 食品与发酵工业, 2019 , 45(2) : 190 -195 . DOI: 10.13995/j.cnki.11-1802/ts.018206

Abstract

A new method for quickly identifying liquor adulteration was established by using a self-developed portable electronic nose detection system. When the system was detecting, the “fingerprint data” of liquor was obtained by sensor array. Then, information reflected the features was extracted by discrete wavelet transform (DWT) from the feedback. The principal component analysis (PCA) was then used to determine the quality of adulterated liquor samples with different purity. The quantitative prediction of adulterated liquor samples with different purity was realized by artificial bee colony least squared-support vector machines (ABC-LSSVM). The results showed that PCA could well-distinguish adulterated liquor. Its accuracy could be as high as 100%. ABC-LSSVM prediction model had a good quantitative prediction performance for liquor purity. Its correlation coefficient (R2) was 0.933 2, the mean relative error (MRE) was 6.564 3%, and the root mean square error (RMSE) was 0.023 4. This study provides technical supports for qualitative discrimination and quantitative prediction of adulterated liquors.

Key words： electronic nose; liquor adulteration; discrete wavelet transform; artificial bee colony-least squares support vector machine

参考文献

[1] NORIEGADOMÍNGUEZ M J, DURÁN D S, VÍRSEDA P, et al. Non-animal proteins as clarifying agents for red wines[J] . Journal International Des Sciences De La Vigne Et Du Vin, 2010, 44(3): 179-189.
[2] LI C, WEI J, ZHOU Q, et al. Rapid identification of Chinese Sauce liquor from different fermentation positions with FT-IR spectroscopy[J] . Journal of Molecular Structure, 2008, 883(1):99-102.
[3] 吴小燕,赵兰,李琳琳,等.紫外-可见吸收光谱法研究阴离子对刚果红/β-葡聚糖络合物的影响[J] .光谱学与光谱分析,2016,36(11):3597-3601.
[4] SHEN F, YANG D, YING Y, et al. Discrimination between Shaoxing wines and other chinese rice wines by near-infrared spectroscopy and chemometrics[J] . Food & Bioprocess Technology, 2012, 5(2):786-795.
[5] ALI K, MALTESE F, TOEPFER R, et al. Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses[J] . Journal of Biomolecular Nmr, 2011, 49(3-4):255-266.
[6] ARROYO-MANZANARES N, GARCÍA-CAMPAÑA A M, GÁMIZ-GRACIA L. Comparison of different sample treatments for the analysis of ochratoxin A in wine by capillary HPLC with laser-induced fluorescence detection[J] . Analytical & Bioanalytical Chemistry, 2011, 401(9):2987.
[7] GUADALUPE Z, MARTíNEZPINILLA O, GARRIDO á, et al. Quantitative determination of wine polysaccharides by gas chromatography-mass spectrometry (GC-MS) and size exclusion chromatography (SEC)[J] . Food Chemistry, 2012, 131(1):367-374.
[8] TOCI A T, CRUPI P, GAMBACORTA G, et al. Free and bound aroma compounds characterization by GC-MS of Negroamaro wine as affected by soil management[J] . Journal of Mass Spectrometry, 2012, 47(9):1104-1112.
[9] Yu H Y, NIU X Y, LIN H J, et al. A feasibility study on on-line determination of rice wine composition by Vis-NIR spectroscopy and least-squares support vector machines[J] . Food Chemistry, 2009, 113(1):291-296.
[10] 郭安鹊,张星星,张予林,等.葡萄酒中总铁和Fe~(2+)的改良菲洛嗪法快速测定[J] .农业机械学报,2017,48(10):338-344.
[11] GOODNER K L, BALDWIN E A, JORDÁN M J, et al. The use of an electronic nose to differentiate NFC orange juices[J] . Proceedings of the Florida State Horticultural Society, 2017, 388(4):405-418.
[12] 方向生,施汉昌,何苗,等.电子鼻在环境监测中的应用与进展[J] .环境科学与技术,2011,34(10):112-117,122.
[13] 路鹏,吴世新,戴志锋,等.基于电子鼻和GIS的大型生活垃圾堆肥厂恶臭污染源测定[J] .农业工程学报,2014,30(17):235-242.
[14] 邹慧琴,拱健婷,赵丽莹,等.中药砂仁“品与质”电子鼻判别模型的建立[J] .国际药学研究杂志,2015,42(4):513-518.
[15] 杜瑞超,冯怡,徐德生,等.电子鼻技术及其在中药行业中的应用前景[J] .中国实验方剂学杂志,2013,19(5):348-351.
[16] 田程,刘春生,吴浩忠,等.中药人参与西洋参饮片的电子鼻检测方法及识别模式[J] .中国中药杂志,2012,37(8):1165-1168.
[17] 陆宽,王雪雅,孙小静,等.电子鼻结合顶空SPME-GC-MS联用技术分析贵州不同品种辣椒发酵后挥发性成分[J] .食品科学,2018,39(4):199-205.
[18] 张娟,张申,张力,等.电子鼻结合统计学分析对牛肉中猪肉掺假的识别[J] .食品科学,2018,39(4):296-300.
[19] 裴高璞,史波林,赵镭,等.典型掺假蜂蜜的电子鼻信息变化特征及判别能力[J] .农业工程学报,2015,31(S1):325-331.
[20] 徐晚秀,李臻峰,张振,等.基于电子鼻的中国白酒酒龄检测[J] .食品与发酵工业,2016,42(2):144-149.
[21] 王辉,李臻峰,邓霞,等.基于电子鼻对不同香型白酒的快速识别和分类[J] .食品工业科技,2017,38(6):62-65; 83.
[22] GIL-SÁNCHEZ L, SOTO J, MARTÍNEZ-MÁÑEZ R, et al. A novel humid electronic nose combined with an electronic tongue for assessing deterioration of wine[J] . Sensors & Actuators A Physical, 2011, 171(2):152-158.
[23] 欧阳永中,李操,周亚飞,等.电喷雾萃取电离质谱法用于掺假白酒的快速分析[J] .化学学报,2013,71(12):1625-1632.
[24] WEI Z, WANG J, JIN W. Evaluation of varieties of set yogurts and their physical properties using a voltammetric electronic tongue based on various potential waveforms[J] . Sensors & Actuators B Chemical, 2013, 177(1):684-694.
[25] 熊雅婷,李宗朋,王健,等. 基于最小二乘支持向量机的白酒酒醅成分定量分析[J] . 食品科学, 2016, 37(12):163-168
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