基于质子转移反应-飞行时间质谱快速鉴别不同产地闽北水仙茶

发布时间：2018-03-23 10:11

  本文选题：质子转移反应-飞行时间质谱　切入点：闽北水仙茶　出处：《分析化学》2017年06期

【摘要】：采用质子转移反应-飞行时间质谱仪(PTR-TOF-MS),构建了3个产地(武夷山、建阳、建瓯)113个闽北水仙茶样品香气的化学指纹图谱,对所得的闽北水仙茶香气指纹图谱进行主成分分析(PCA),获得了不同产地闽北水仙茶样品的质谱信息特征,然后采用软独立建模分类法(SIMCA)、K最邻近结点算法(KNN)、偏最小二乘判别分析法(PLS-DA)对闽北水仙茶的质谱信息进行了模式识别。结果表明,PTR-TOFMS结合分类识别模式能有效区分不同产地的闽北水仙茶。PCA提取了3个主成分,累计贡献率为84.66%;3个识别模型的校正集判别正确率分别为89.38%、100.00%和100.00%,预测集的判别正确率分别为83.18%、96.46%和95.57%。基于此成功建立了不同产地的闽北水仙茶识别模型。本方法无需样品预处理、分析速度快、灵敏度高、对茶叶无损伤,为茶叶产地溯源提供了新方法。
[Abstract]:A chemical fingerprint of 113 samples of Narcissus tea from three producing areas (Wuyishan, Jianyang, Jianou) was constructed by using the proton transfer reaction-time of flight mass spectrometer (PTR-TOF-MSN). The aroma fingerprint of Narcissus chinensis tea from North Fujian Province was analyzed by principal component analysis (PCA), and the mass spectrum information characteristics of Narcissus chinensis tea samples from different producing areas were obtained. Then, the soft independent modeling classification method (Simca) and the partial least squares discriminant analysis (PLS-DA) were used to recognize the mass spectrum information of Narcissus chinensis tea. The results show that PTR-TOFMS combined with classification pattern can effectively distinguish Narcissus tea. Three principal components were extracted from Narcissus chinensis tea from the same area. The cumulative contribution rate was 84.66, the correct discriminant rate of three recognition models was 89.380.000% and 100.00000%, respectively, and the accuracy rate of prediction set was 83.186.46% and 95.577.Based on this, the identification model of Narcissus chinensis tea from different producing areas was successfully established. The analysis is fast, sensitive and harmless to tea, which provides a new method for tracing the origin of tea.
【作者单位】： 福建农林大学园艺学院/茶学福建省高校重点实验室;福州大学化学工程与技术博士后科研流动站;泉州出入境检验检疫局综合技术服务中心;福建农林大学生命科学院;国家质检总局毒品检测重点实验室福建国际旅行卫生保健中心福建出入境检验检疫局;
【基金】：福建省“2011协同创新中心”中国乌龙茶产业协同创新中心专项(No.闽教科[2015]75号) 福建省科技厅对外合作项目(No.2013I0001) 福建检验检疫局科技计划项目(No.FK2015-18和FK2013-43) 中国博士后科学基金项目(No.2012M511440)资助
【分类号】：O657.63;TS272.7
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