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  • Title: [Discriminant analysis and similarity evaluation of gas chromatography-mass spectrometry fingerprints of aroma components in green tea grading].
    Author: Long L, Song S, Cao X.
    Journal: Se Pu; 2019 Mar 08; 37(3):325-330. PubMed ID: 30900863.
    Abstract:
    Two series of 41 Xinyang Maojian tea samples were investigated and the gas chromatography-mass spectrometry (GC-MS) fingerprints of their aroma components of seven different grades were established using headspace solid-phase micro extraction (HS-SPME) and GC-MS. Based on the 23 selected characteristic aroma components, the samples could be classified into seven different groups through discriminant analysis with four and three groups in two separate series. Six fingerprint similarity calculation methods that reflect the differences between grades of tea to different extents were employed, and the new improved extent similarity method was demonstrated to be the best among them. The results for the similarity evaluation displayed good correlation with the actual grades, especially for the series of tea of higher qualities, and the differences between the different grades of teas could be quantified.
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