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Rapid Commun Mass Spectrom


Title:Rapid and direct identification of the origin of white tea with proton transfer reaction time-of-flight mass spectrometry
Author(s):Zhang D; Wu W; Qiu X; Li X; Zhao F; Ye N;
Address:"College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, 350002, China. Fujian Business University, Fuzhou, Fujian, 350016, China. Minjiang Teachers College, Fuzhou, Fujian, 350018, China. Athena Institute of Holistic Wellness, Nanping, Fujian, 354399, China. College of Chemistry, Fuzhou University, Fuzhou, Fujian, 350108, China. College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, 350122, China"
Journal Title:Rapid Commun Mass Spectrom
Year:2020
Volume:34
Issue:20
Page Number:e8830 -
DOI: 10.1002/rcm.8830
ISSN/ISBN:1097-0231 (Electronic) 0951-4198 (Linking)
Abstract:"RATIONALE: White tea has become very popular in recent years, but there has been no scientific identification of white tea from different origins. For product authentication and valorization, every kind of white tea must be marked with an indication of its origin. METHODS: Volatile profiles of white tea leaf samples from their main origins in China (Fuding City, Zhenghe City and Jianyang City) were analyzed using proton transfer reaction time-of-flight mass spectrometry (PTR-TOFMS). Tentative identifications of the volatile organic compounds (VOCs) were obtained by PTR-TOFMS of the headspace. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the differences among the various origins. RESULTS: Teas from different origins were shown to have characteristic VOCs and profiles. Thus, white teas from different origins could be separated by characterizing the volatile emissions from the dry tea leaves. The ability of the two classification models to use the volatile fingerprints in origin discrimination was investigated. CONCLUSIONS: Two classification models (PCA and OPLS-DA) were applied to the PTR-TOFMS data obtained from the VOCs of various white teas. The classification models were shown to be useful in identifying the origin of white tea samples, providing a reference for white tea identification"
Keywords:
Notes:"PubMed-not-MEDLINEZhang, Dandan Wu, Weihua Qiu, Xiaohong Li, Xiaojing Zhao, Feng Ye, Naixing eng 31270735/National Natural Science Foundation of China/ CXZX2016117/Special fund for scientific and technological innovation of Fujian Agriculture And Forestry University/ CXZX2017181/Special fund for scientific and technological innovation of Fujian Agriculture And Forestry University/ England 2020/05/18 Rapid Commun Mass Spectrom. 2020 Oct 30; 34(20):e8830. doi: 10.1002/rcm.8830"

 
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