基于气相离子迁移谱黄酒产地识别的研究

祁兴普; 陈通; 刘萍; 李创; 姚芳; 张静; 刘靖

doi:10.13386/j.issn1002-0306.2019.22.047

基于气相离子迁移谱黄酒产地识别的研究

祁兴普¹,
陈通²,
刘萍¹,
李创¹,
姚芳¹,
张静¹,
刘靖^1, ,

1. 江苏农牧科技职业学院食品科技学院, 江苏泰州 225300;
2. 江苏大学食品与生物工程学院, 江苏镇江 212013

基金项目:

泰州市科技支撑计划(TN201712)

江苏省高职院校青年教师企业实践培训项目(2019QYSJ075)。

详细信息

作者简介:
祁兴普(1982-),男,博士,讲师,研究方向:食品、农产品品质快速无损检测,E-mail:6354752@qq.com。

通讯作者:
刘靖(1967-),女,博士,教授,研究方向:食品质量与安全方向,Email:460318854@qq.com。

中图分类号: TS262.4
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出版历程
- 收稿日期: 2019-01-27
- 网络出版日期: 2020-11-12
- 刊出日期: 2019-11-14

Origin Identification of Yellow Wine Based on Gas Chromatography-Ion Mobility Spectrometry

1. School of Food Science and Technology, Jiangsu Agri-animal Husbandry Vocational College, Taizhou 225300, China;
2. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China

摘要

摘要: 为建立一种快速、准确的黄酒产地鉴别方法,本研究运用气相-离子迁移谱(Gas Chromatography-Ion Mobility Spectrometry,GC-IMS)对不同产地的黄酒中的挥发性有机成分进行分析,构建黄酒产地信息的气味指纹图谱,并对不同产地的黄酒样品进行了判别和分类。采用二维差谱方法筛选16个有效特征峰作为表征黄酒产地差异信息的特征变量,采用主成分分析(Principal Component Analysis,PCA)和线性判别分析(Linear Discriminate Analysis,LDA)方法建立判别模型。结果表明,选取的特征变量经PCA处理后前两个主成分的累积贡献率为96.07%,不同产地的黄酒样品在主成分分析图中均有对应的归属区域,以前2个主成分得分结合LDA方法可以有效的区分不同产地的黄酒样品,预测集中识别率高达94.44%。研究表明,GC-IMS技术结合化学计量学方法能够快速、准确、直观地区分不同产地的黄酒样品,为黄酒的鉴别和原产地保护提供了一种新的检测方法。
- 黄酒 /
- 气相色谱-离子迁移谱 /
- 主成分分析 /
- 线性判别分析
Abstract: In this study,gas chromatography-ion mobility spectrometry technology was used to analyze the volatile organic components of yellow wine with different origins,construct odor fingerprint of yellow wine,and discriminate and classify different origins of yellow wine based on differences in odor components. A total of 16 effective characteristic peaks were selected by the two-dimensional difference spectrometry method as the variables to characterize the differences in origins of yellow wine. After principle component analysis,the cumulative contribution rate of the first two principal components was 96.07%,yellow wine samples from different origins all had corresponding attribution areas in the principal component map and the principal component score combined with linear discriminate analysis were used to realize discriminant analysis. The results showed that linear discriminate analysis combined with principal component analysis could effectively distinguish yellow wine samples with different origins,and the accuracy rate of recognition was 94.44% in the prediction set. Gas chromatography-ion mobility spectrometry combined with chemometrics can quickly,accurately and intuitively distinguish yellow wine samples with different origins,which provides a new reference method for identification and origin protection of yellow wine.
- yellow wine /
- gas chromatography-ion mobility spectrometry /
- principal component analysis /
- linear discriminate analysis

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