食品科学 ›› 2023, Vol. 44 ›› Issue (8): 201-211.doi: 10.7506/spkx1002-6630-20220511-144

• 成分分析 • 上一篇    下一篇

基于ATD-GC-MS技术检测铁观音做青过程环境挥发性成分的动态变化

毕婉君, 魏子淳, 郑玉成, 邓慧莉, 倪子鑫, 林宏政, 郝志龙, 孙云   

  1. (1.福建农林大学园艺学院,福建 福州 350002;2.武夷山茗兮录茶业有限公司,福建 武夷山 354300)
  • 出版日期:2023-04-25 发布日期:2023-05-06
  • 基金资助:
    财政部和农业农村部:国家现代农业产业技术体系资助项目(CARS-19); 福建农林大学科技创新专项(CXZX2018076);福建农林大学茶产业链科技创新与服务体系建设项目(K1520005A06); 福建张天福茶叶发展基金会科技创新基金项目(FJZTF01)

Using Automatic Thermal Desorption Gas Chromatography-Mass Spectrometry to Detect Dynamic Changes of Environmental Volatile Components in Tieguanyin Oolong Tea during Fine Manipulation

BI Wanjun, WEI Zichun, ZHENG Yucheng, DENG Huili, NI Zixin, LIN Hongzheng, HAO Zhilong, SUN Yun   

  1. (1. College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China; 2. Mingxilu Tea Co. Ltd., Wuyishan 354300, China)
  • Online:2023-04-25 Published:2023-05-06

摘要: 采用全自动热脱-气相色谱-质谱法捕集和检测铁观音做青关键工艺节点的环境挥发性成分,应用短时间序列表达挖掘器(short time-series expression miner,STEM)和偏最小二乘法判别分析(partial least squares-discriminant analysis,PLS-DA)对铁观音做青过程中挥发性成分进行分析。结果显示,铁观音做青环境中共鉴定出122 种挥发性成分,包括醇类、酯类、烯烃类、烷烃类、醛类、芳香烃类、酮类和其他化合物8 大类,其中酯类是做青环境中的主要挥发物;STEM结果表明,检测出的挥发性成分可划分成19 种变化趋势,且在2 种趋势模型中有显著性富集,其中仲丁醇、乙酸乙酯、异戊醛、异戊醇、正己醇、2-庚醇、己酸甲酯、甲基庚烯酮、异丁酸辛酯等挥发性成分带有特殊香气并随着做青次数的增加而显著增加;PLS-DA结果表明,摇青和晾青两部分可有效区分开,并鉴定出7 种共同特征挥发性成分(变异权重参数值>1):(Z)-乙酸-4-己烯-1-酯、反-3-己烯基丁酯、叶醇、3-己烯醛、异戊腈、(3E)-4,8-二甲基壬-1,3,7-三烯、罗勒烯异构体混合物。由此可见,铁观音做青过程中环境挥发性成分类别的比例和所含物质都会随做青过程的推进有所变化,大部分挥发性成分呈现较为明显的规律性变化,其中筛选得到的7 种特征挥发性成分呈现有规律的倍数变化,可作为判断智能化做青的香气指标。

关键词: 铁观音;做青;环境挥发性成分;全自动热脱-气相色谱-质谱法;短时间序列表达挖掘器;偏最小二乘法判别分析

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

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