Citation: ZHANG Dan-Dan, WEI Hang, QIU Xiao-Hong, ZHENG De-Yong, CAO Jie, YE Nai-Xing. Rapid Identification of Shuixian Tea in Northern Fujian from Different Regions by Proton Transfer Reaction-Time of Flight-Mass Spectrometry[J]. Chinese Journal of Analytical Chemistry, ;2017, 45(6): 914-921. doi: 10.11895/j.issn.0253-3820.160842 shu

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

1.
College of Horticulture, Fujian Agriculture and Forestry University, Key Laboratory of Tea Science in Universities of Fujian Province, Fuzhou 350002, China;
2.
Fuzhou University Postdoctoral Research Station of Chemical Engineering and Technology, Fuzhou 350108, China;
3.
Quanzhou Entry-Exist Inspection & Quarantine Bureau of P. R. C, Quanzhou 362000, China;
4.
College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China;
5.
Administration of Quality Supervision, Inspection and Quarantine Key Laboratory of Drug Detection, Fujian International Travel Healthcare Center, Fujian Entry-Exit Inspection and Quarantine Bureau, Fuzhou 350001, China

Received Date: 19 November 2016
Revised Date: 26 April 2017

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 was 84.66%. 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, non-destructive and sensitive detection method of tea, which could provide reference for geographical traceability.
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沈阳化工大学材料科学与工程学院沈阳 110142