食品科学 ›› 2019, Vol. 40 ›› Issue (24): 228-233.doi: 10.7506/spkx1002-6630-20190429-386

• 成分分析 • 上一篇    下一篇

基于顶空气相色谱-离子迁移谱技术的生咖啡豆快速鉴别方法

杜萍,陈振佳,杨芳,李晓蕾,杨俊,刘春侠,梁静思,任芳   

  1. (1.昆明理工大学分析测试研究中心,云南省分析测试中心,云南 昆明 652094;2.中国咖啡工程研究中心,云南 德宏 678400;3.武汉工程大学环境生态与生物工程学院,湖北 武汉 430205;4.山东海能科学仪器有限公司,山东 德州 251500)
  • 出版日期:2019-12-25 发布日期:2019-12-24
  • 基金资助:
    “十三五”国家重点研发计划重点专项(2018YFD0201100);国家自然科学基金青年科学基金项目(31701604); 云南省高端人才引进项目(2016HE003;2016HE004);云南省重大科技专项(2018ZG014-015-016-017)

A Rapid Method for the Discrimination of Different Varieties of Green Coffee Beans by Headspace-Gas Chromatography-Ion Mobility Spectrometry

DU Ping, CHEN Zhenjia, YANG Fang, LI Xiaolei, YANG Jun, LIU Chunxia, LIANG Jingsi, REN Fang   

  1. (1. Analytic and Testing Research Center of Yunnan, Research Center for Analysis and Measurement, Kunming University of Science and Technology, Kunming 652094, China; 2. Coffee Engineering Research Center of China, Dehong 678400, China;3. School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China;4. Shandong Hanon Scientific Instruments Co. Ltd., Dezhou 251500, China)
  • Online:2019-12-25 Published:2019-12-24

摘要: 采用顶空气相色谱-离子迁移谱(headspace-gas chromatography-ion mobility spectrometry,HS-GC-IMS)技术对云南不同品种生咖啡豆的挥发性有机物(volatile organic compounds,VOCs)进行无损分析。根据保留指数和迁移时间对其挥发性成分进行二维定性,创建生咖啡豆VOCs的差异谱图,并对其VOCs数据进行主成分分析(principal component analysis,PCA)。结果表明,HS-GC-IMS可有效分离生咖啡豆挥发性成分,对样品VOCs的信息采集及分析可在20 min内完成,并鉴定出42 种挥发性物质,主要为醛类、酯类、醇类、酮类、吡嗪类、酸类及含硫化合物。采用PCA分析HS-GC-IMS图谱,可准确区分不同品种生咖啡豆。该方法具有快速、灵敏、无损的特点,为生咖啡豆的品种识别、产地追溯、品质控制等提供了一定参考依据和理论基础。

关键词: 生咖啡豆, 顶空气相色谱-离子迁移谱, 挥发性成分, 区分

Abstract: The volatile organic compounds (VOCs) of different varieties of green coffee beans from Yunnan province were analyzed nondestructively by headspace-gas chromatography-ion migration spectroscopy (HS-GC-IMS). According to the retention index in GC and the migration time, the VOCs were identified two-dimensionally and differential profiles were created. Principal component analysis (PCA) was performed on the VOCs data. The results showed that HS-GC-IMS could effectively separate the volatile components of green coffee beans, and that the information collection and analysis could be completed within 20 min. A total of 42 volatile substances were identified, mainly including aldehydes, esters, alcohols, ketones, pyrazines, acids and sulfur-containing compounds. PCA analysis of HS-GC-IMS spectra could accurately distinguish different varieties of green coffee beans. This method is rapid, sensitive and nondestructive, and it is of great significance for varietal identification, origin tracing and quality control of green coffee beans.

Key words: green coffee beans, headspace-gas chromatography-ion migration spectroscopy, volatile components, discrimination

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