食品科学 ›› 2023, Vol. 44 ›› Issue (20): 292-299.doi: 10.7506/spkx1002-6630-20230306-053

• 成分分析 • 上一篇    下一篇

多组学技术融合电子感官的咖啡风味品质分析

李钰莲,郑建祎,黄旭辉,董秀萍,赵保民,秦磊   

  1. (1.大连工业大学食品学院,国家海洋食品工程技术研究中心,辽宁 大连 116034;2.江苏派乐滋食品有限公司,江苏 徐州 221112)
  • 出版日期:2023-10-25 发布日期:2023-11-07
  • 基金资助:
    辽宁省“兴辽英才计划”青年拔尖人才项目(XLYC2007158);辽宁省博士科研启动基金计划项目(2021-BS-228)

Analysis of the Flavor Quality of Coffee Using Multiple Omic Technologies Combined with Electronic Sensory Detection Technology

LI Yulian, ZHENG Jianyi, HUANG Xuhui, DONG Xiuping, ZHAO Baomin, QIN Lei   

  1. (1. National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China; 2. Jiangsu Palarich Food Company Limited, Xuzhou 221112, China)
  • Online:2023-10-25 Published:2023-11-07

摘要: 通过代谢组学、风味组学与快速检测的电子感官技术相融合,对6 种不同咖啡的风味品质差异进行鉴定分析。结果表明,2,6-二乙基吡嗪、2-乙基-1-己醇、丙酮、异戊酸、戊酸甲酯等可作为区分不同烘焙度咖啡的香气标志物;鸟嘌呤、色氨酸-丙氨酸、巴豆酸、1-甲基腺苷等48 种化合物是区分来源于不同产地的咖啡粉及其混合样本的代谢差异标志物。浅度烘焙咖啡中有较高含量的1,4-D-木糖、丙氨酸、异亮氨酸、苯丙氨酸等呈滋味物质。中深度烘焙咖啡中的麦芽三糖含量较多,而肌苷含量较少。电子鼻、电子舌检测结合主成分分析可用于不同类型咖啡的快速筛分、品种判别。该结果为咖啡工厂生产提供理论依据和技术支撑,也为建立评价咖啡风味品质标准提供参考。

关键词: 咖啡;多组学融合分析技术;电子感官;滋味;香味

Abstract: By the combined use of metabolomics, flavoromics, and rapid electronic sensory detection technology, this study identified and analyzed the differences in flavor quality of six coffees. The results suggested that 2,6-dimethylpyrazine, 2-ethylhexan-1-ol, acetoin, isovaleric acid, and methyl valerate could be employed as aroma markers to distinguish coffees with different degrees of roasting. Additionally, 48 compounds, including guanine, tryptophan-alanine, crotonic acid, and 1-methyladenosine, were found to be the metabolic difference indicators to distinguish coffee powder from different geographical origins and their mixed samples. The major taste compounds of lightly roasted coffee were 1,4-D-xylose, alanine, isoleucine, and phenylalanine. Maltotriose was found to be a major compound in moderately roasted coffee, which also contained a lesser amount of inosine. The combination of electronic nose and electronic tongue detection with principal component analysis (PCA) could be used for rapid classification and variety identification of coffee. These results provide a theoretical basis and technical support for the production of coffee as well as a reference for establishing standards to evaluate the flavor and quality of coffee.

Key words: coffee; fusion of multiple omics technologies; electronic sensory detection; taste; aroma

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