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

Rapid Identification of Shuixian Tea in Northern Fujian from Different Regions by Proton Transfer Reaction-Time of Flight-Mass Spectrometry

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。

To determine the Minbei Shuixian tea from different region quickly and non-destructively,proton transfer reaction-time of flight-mass spectrometry( PTR-TOF-MS) was used to obtain chemical fingerprints of the volatile compounds of 113 samples directly from the surface of the dry tea leaves without any sample pretreatment in three regions( Wuyishan,Jianyang and Jian'ou). The raw MS data were analyzed by multivariate analysis,including principal component analysis( PCA) and analysis of variance( ANOVA). In addition, soft independent modeling class analogy( SIMCA),K nearest neighbor algorithm( KNN) and partial least squares discriminant analysis( PLS-DA) were used for pattern recognition. The experimental results demonstrated that in the positive ion mode,PTR-TOF-MS combined with multivariate analysis could effectively distinguish tea from different regions. Three principal components were extracted by PCA,and their cumulative contribution rate was84.66%. The correct rates of the three sets of calibration models were 89.38%,100.00%,100.00%,and the accuracy rates of the prediction set were 83.18%,96.46%,95.57%,respectively. The different region pattern recognition model were successfully established. It was found that Shuixian tea in different regions of northern Fujian could be differentiated by PTR-TOF-MS and the results provided a basis for establishing a fast,nondestructive and sensitive detection method of tea,which could provide reference for geographical traceability.