Abstract: Automatic thermal desorption-gas chromatography-mass spectrometry (ATD-GC-MS) was used to capture and detect environmental volatile components in Tieguanyin tea at the key stages of the fine manipulation process, and short time series expression miner (STEM) and partial least squares-discriminant analysis (PLS-DA) were used to analyze the volatile components. The results showed that a total of 122 volatile components belonging to eight chemical classes, i.e., alcohols, esters, olefins, alkanes, aldehydes, aromatic hydrocarbons, ketones and other compounds were identified, esters being the major ones. The STEM results showed that the detected volatile components could be divided into 19 trends, and there was significant enrichment in two trend models. Among them, the levels of 2-butanol, ethyl acetate, isovaleraldehyde, 3-methyl-1-butanol, 1-hexanol, 2-heptanol, methyl hexanoate, 6-methyl-5-hepten-2-one, and octyl isobutyrate, which have a special aroma, increased significantly with increasing number of fine manipulation cycles. PLS-DA could effectively distinguish between tossing and sun withering, and seven characteristic volatile components (variable importance in the projection (VIP) > 1) were common to the two stages including (Z)-4-hexen-1-yl acetate, (E)-butanoic acid, 3-hexenyl ester, (E)-3-hexen-1-ol, 2-hexenal, 3-methyl-butanenitrile, (E)-4,8-dimethylnona-1,3,7-triene and (Z)-3,7-dimethyl-1,3,6-octatriene. The proportion and composition of environmental volatile components in Tieguanyin tea changed during the fine manipulation process. Most of the volatile components showed obvious and regular changes. The seven shared volatile components could be considered as aroma indexes for judging intelligent fine manipulation.

Key words: Camellia sinensis cv. Tieguanyin; fine manipulation; environmental volatile components; automatic thermal desorption-gas chromatography-mass spectrometry; short time-series expression miner; partial least squares-discriminant analysis