高等学校化学学报

高等学校化学学报 ›› 2013, Vol. 34 ›› Issue (7): 1623.doi: 10.7503/cjcu20121013

• 分析化学 • 上一篇    下一篇

基于液体阵列味觉仿生传感器鉴别白酒香型的新方法

侯长军1, 戴斌1, 霍丹群1, 杨平2, 徐勇2, 李俊杰1, 罗小刚1, 杨眉1, 法焕宝3   

  1. 1. 重庆大学生物工程学院, 重庆 400044;
    2. 国家固态酿造工程技术研究中心, 泸州老窖股份有限公司, 泸州 646000;
    3. 重庆大学化学工程学院, 重庆 400044
  • 收稿日期:2012-11-07 出版日期:2013-07-10 发布日期:2013-06-21
  • 通讯作者: 侯长军, 男, 博士, 教授, 博士生导师, 主要从事卟啉生化传感器方面的研究. E-mail: houcj@cqu.edu.cn E-mail:houcj@cqu.edu.cn
  • 基金资助:

    国家自然科学基金(批准号: 31171684, 81102132);四川省科技支撑计划(批准号: 2010NZ0093);中央高校基本科研业务费(批准号: CDJXS11231178, CDJXS10 23 00);四川省重点实验室开放基金(批准号: NJ2011-03)和重庆大学大型仪器设备开放基金资助.

New Method for Identifying the Aromatic Types of Chinese Liquors Based on a 96-well Plate

HOU Chang-Jun1, DAI Bin1, HUO Dan-Qun1, YANG Ping2, XU Yong2, LI Jun-Jie1, LUO Xiao-Gang1, YANG Mei1, FA Huan-Bao3   

  1. 1. College of Bioengineering, Chongqing University, Chongqing 400044, China;
    2. National Engineering Research Center of Solid-State Brewing, Luzhou Laojiao Group Co., Ltd., Luzhou 646000, China;
    3. College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China
  • Received:2012-11-07 Online:2013-07-10 Published:2013-06-21
  • Contact: yang mei E-mail:houcj@cqu.edu.cn

PDF (PC)

被引次数

21

摘要：

通过模拟哺乳动物的味觉系统, 建立了交叉响应的液体阵列传感器, 为鉴别白酒香型提供了新方法. 选用7种染料和1种卟啉化合物作为传感单元, 构建液体阵列传感器, 集合8个传感单元的光谱响应信号构成分析物的指纹图谱, 达到识别的目的. 使用96孔板酶标仪采集响应数据, 结合主成分分析(PCA)、分层聚类分析(HCA)和判别分析(LDA)等模式识别方法进行数据处理, 对9种具有代表性的不同香型白酒样品进行了鉴别分析. PCA结果表明, 该方法对于白酒的检测主要基于酒体微量成分, 其中酸类物质对识别的贡献最大(贡献率达54.3%), 芳香类物质贡献率为18.6%; 同时, 仅用63.4%的数据信息量即可对白酒香型进行区分. HCA结果表明, 平行样均正确归类, 各白酒之间的相似程度在聚类图上得到体现. LDA结果表明, 该阵列对于9种白酒样品香型识别的准确率达到100%.

关键词: 白酒香型, 味觉仿生, 液体阵列传感器, 交叉响应

Abstract:

A cross-response liquid array sensor that simulated the mammalian taste system was developed for the determination of liquor aromatic types. The liquid array sensor was constructed with 8 sensing units which were consisted of 7 chemical dyes and 1 porphyrin compound. It achieved the type identification through the analyte fingerprints constituted by congregating the spectral response signal of 8 sensing units. The data were collected via a 96-well plate microplate reader, and then was further analyzed with principal component analysis(PCA), hierarchical clustering analysis(HCA) and linear discriminant analysis(LDA). We detected 9 different aromatic liquors. PCA results suggested that the mechanism of identification was mainly based on the trace components of Chinese liquor. Thereamong, the acids of Chinese liquor were the maximum contribution for the identification, because the contribution rate of acids was 54.3% and that of aromatic substances was only 18.6%. Simultaneously, only by 63.4% data rate could distinct liquor aromatic types with satisfaction. HCA dendrogram demonstrated that 9 different aromatic liquors could be correctly classified. LDA further showed the classification accuracy of identification for these 9 different aromatic liquors was 100%. These results showed that this method may provide a simple and efficient way for the rapid identification of liquor.

Key words: Liquor aromatic types, Taste biomimetic, Liquid array sensor, Cross-reactive

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