摘要
该研究分别利用电子鼻和气质联用(gas chromatography-mass spectrometry,GC-MS)分析7种不同品牌浓香型白酒的差异。结果表明,电子鼻的S2、S6、S7和S94个传感器对不同品牌浓香型白酒具有较好的响应信号,经主成分分析(principal component analysis,PCA)筛选后可以作为浓香型白酒差异的特征指标来衡量。基于传感器信号,比较了PCA和线性判别对不同各品牌浓香型白酒的分类效果,PCA分析能够对不同品牌白酒进行较好区分。GC-MS分析表明,不同品牌浓香型白酒风味物质含量存在明显差异,而PCA分析中关系密切的样品在风味成分层面存在相似性。该研究提供了一种基于电子鼻、GC-MS技术和数理统计分析相结合的浓香型白酒分类方法,为浓香型白酒的快速质量分类方法的开发提供了理论和数据支撑。
Baijiu is a complex system that is constitute of ethanol-water and trace amount of aroma compounds,and its quality is decided by the constitution and ratio of aroma compounds.In this study,electronic nose(e-nose)and gas chromatography-mass spectrometry(GC-MS)were used to analysis the difference in 7 brands of strong-flavor Baijiu(SFB).The results showed that the sensors including S2,S6,S7 and S9 in e-nose presented excellent response signals for different brands of SFB.Based on signals of e-nose,comparison between principal component analysis(PCA)and linear discriminant analysis was conducted.The results suggested that PCA could gave clear classification between different brand of SFB.GC-MS analysis showed that obvious discrimination was determined in different brands of SFB,and samples that clustered together in PCA plot had similar volatile profiles.This study provided a comprehensive method employing e-nose,GC-MS and statistical analysis to classify different SFB,and it also provided theoretical and data reference for the development of fast classification method for SFB.
作者
刘芳
杨康卓
张建敏
何张兰
彭志云
郑佳
LIU Fang;YANG Kangzhuo;ZHANG Jianmin;HE Zhanglan;PENG Zhiyun;ZHENG Jia(Technology Research Center,Wuliangye Yibin Co.,Ltd.Yibin 644007,China)
出处
《食品与发酵工业》
CAS
CSCD
北大核心
2020年第2期73-78,共6页
Food and Fermentation Industries
基金
固态发酵资源利用四川省重点实验室开放基金(2018GTJ004)
国家重点研发计划(2016YFD0400500)
关键词
浓香型白酒
电子鼻
GC-MS
分类
主成分分析
strong-flavor Baijiu
electronic nose
GC-MS
classification
principal component analysis
