基于氨基酸组成的黄酒酒龄电子舌鉴别

该研究采用电子舌结合化学计量学方法用于黄酒酒龄的快速鉴别。为确证黄酒样品酒龄,采用氨基酸分析仪分析了1年陈、3年陈和5年陈黄酒中20种氨基酸,并利用主成分分析（principal component analysis,PCA）对氨基酸数据进行了分析。采用电位型电子舌采集了不同酒龄黄酒样品的味觉指纹信息,并采用判别分析（discriminant analysis,DA）方法结合味觉指纹信息建立黄酒酒龄快速鉴别模型。采用偏最小二乘法（partial least squares regression,PLSR）建立电子舌响应信号与氨基酸含量之间的相关关系。氨基酸数据结合PCA分析表明所有样品均标注正...

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Bibliographic Details
Published in农业工程学报 Vol. 33; no. 2; pp. 297 - 301
Main Author 于海燕 张燕 许春华 田怀香
Format Journal Article
LanguageChinese
Published 上海应用技术大学食品科学与工程系,201418 2017
Subjects
主成分分析
化学计量学方法
模型
氨基酸
电子舌
黄酒
主成分分析
models
电子舌
Chinese rice wine
氨基酸
模型
amino acids
chemometric method
化学计量学方法
黄酒
electronic tongue
principal component analysis
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Summary:该研究采用电子舌结合化学计量学方法用于黄酒酒龄的快速鉴别。为确证黄酒样品酒龄,采用氨基酸分析仪分析了1年陈、3年陈和5年陈黄酒中20种氨基酸,并利用主成分分析（principal component analysis,PCA）对氨基酸数据进行了分析。采用电位型电子舌采集了不同酒龄黄酒样品的味觉指纹信息,并采用判别分析（discriminant analysis,DA）方法结合味觉指纹信息建立黄酒酒龄快速鉴别模型。采用偏最小二乘法（partial least squares regression,PLSR）建立电子舌响应信号与氨基酸含量之间的相关关系。氨基酸数据结合PCA分析表明所有样品均标注正确;电子舌结合DA所建黄酒酒龄鉴别模型可将3个年份预测集样品正确区分;异亮氨酸（Ile）、天门冬氨酸（Asp）、酪氨酸（Tyr）和缬氨酸（Val）与电子舌相关性高,模型的相对分析误差（Residual predictive deviation,RPD）高于2。研究表明电位型电子舌结合判别分析是黄酒龄鉴别的稳健方法。
Bibliography:11-2047/S
Yu Haiyan, Zhang Yan, Xu Chunhua, Tian Huaixiang （Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai 201418, China）
amino acids; principal component analysis; models; chemometric method; Chinese rice wine; electronic tongue
To ensure a good reputation for the producers and to guarantee the basic quality of wine for the consumers, an electronic tongue（E-tongue） coupled with a chemometric method was applied to rapidly discriminate the wine age of Chinese rice wine. Amino acid profiles analyzed by an amino acid analyzer together with principal component analysis（PCA） was used for validation of the wine age of the Chinese rice wine samples sourced from 1-year, 3-year, and 5-year. E-tongue responses collected by a potentiometric E-tongue together with discriminant analysis（DA） were used for the rapid discrimination of the wine age. The correlation between the E-tongue responses and the amino acid profiles was established by partial least squares regression（PLSR）. The resul
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2017.02.041