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The Study of Fingerprint Characteristics of Dayi Pu-Erh Tea Using a Fully Automatic HS-SPME/GC–MS and Combined Chemometrics Method

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  • Shidong Lv
  • Yuanshuang Wu
  • Jiangsheng Zhou
  • Ming Lian
  • Changwen Li
  • Yongquan Xu
  • Shunhang Liu
  • Chao Wang
  • Qingxiong Meng

Abstract

The quality of tea is presently evaluated by the sensory assessment of professional tea tasters, however, this approach is both inconsistent and inaccurate. A more standardized and efficient method is urgently needed to objectively evaluate tea quality. In this study, the chemical fingerprint of 7 different Dayi Pu-erh tea brands and 3 different Ya'an tea brands on the market were analyzed using fully automatic headspace solid-phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC–MS). A total of 78 volatiles were separated, among 75 volatiles were identified by GC–MS in seven Dayi Pu-erh teas, and the major chemical components included methoxyphenolic compounds, hydrocarbons, and alcohol compounds, such as 1,2,3-trimethoxybenzene, 1,2,4-trimethoxybenzene, 2,6,10,14-tetramethyl-pentadecane, linalool and its oxides, α-terpineol, and phytol. The overlapping ratio of peaks (ORP) of the chromatogram in the seven Dayi Pu-erh tea samples was greater than 89.55%, whereas the ORP of Ya'an tea samples was less than 79.10%. The similarity and differences of the Dayi Pu-erh tea samples were also characterized using correlation coefficient similarity and principal component analysis (PCA). The results showed that the correlation coefficient of similarity of the seven Dayi Pu-erh tea samples was greater than 0.820 and was gathered in a specific area, which showed that samples from different brands were basically the same, despite have some slightly differences of chemical indexes was found. These results showed that the GC-MS fingerprint combined with the PCA approach can be used as an effective tool for the quality assessment and control of Pu-erh tea.

Suggested Citation

  • Shidong Lv & Yuanshuang Wu & Jiangsheng Zhou & Ming Lian & Changwen Li & Yongquan Xu & Shunhang Liu & Chao Wang & Qingxiong Meng, 2014. "The Study of Fingerprint Characteristics of Dayi Pu-Erh Tea Using a Fully Automatic HS-SPME/GC–MS and Combined Chemometrics Method," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-18, December.
  • Handle: RePEc:plo:pone00:0116428
    DOI: 10.1371/journal.pone.0116428
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    1. Jie Sun & Hao Li & Qipeng Yuan, 2012. "Metabolic Regulation of Trisporic Acid on Blakeslea trispora Revealed by a GC-MS-Based Metabolomic Approach," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-9, September.
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    Cited by:

    1. Yan-Qin Yang & Hong-Xu Yin & Hai-Bo Yuan & Yong-Wen Jiang & Chun-Wang Dong & Yu-Liang Deng, 2018. "Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-19, March.
    2. Keran Su & Xin Zhang & Shao Quan Liu & LiHui Jia & Benjamin Lassabliere & Kim Huey Ee & Aileen Pua & Rui Min Vivian Goh & Jingcan Sun & Bin Yu & XiaoXue Hu, 2020. "Identification of key odorants in honeysuckle by headspace-solid phase microextraction and solvent-assisted flavour evaporation with gas chromatography-mass spectrometry and gas chromatograph-olfactom," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-14, August.

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