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采用模糊聚类法辅助鉴别烟用香精的品质

Evaluation of Tobacco Flavors Aided by Fuzzy Cluster Analysis

  • 摘要: 采用毛细管气相色谱法(GC)、气相色谱/质谱联用法(GC/MS)对6种烟用栗子香精进行了定性、定量分析,筛选出10种共有组分。运用模糊聚类分析(FCA)技术,对香精中这10种组份的含量数据进行处理,以深入研究香精品质与化学成分、样品来源等因素的相互关系。通过模糊聚类分析谱系图量化地给出了香精的相似程度,其结果与专家评香结果基本一致,提出了一个计算机辅助鉴别香精品质的新方法。

     

    Abstract: The aroma components in six types of tobacco chestnut flavor were analyzed qualitatively and quantitatively by capillary gas chromatography and gas chromatography-mass spectroscopy, and ten common components were selected.In order to further investigate the quality of flavor with relation to its chemical components, sampling sources, and other factors, the data of the contents of ten common components were processed with fuzzy cluster analysis (FCA) technology.The similarity of tobacco flavors was presented quantitatively by FCA profile and generally agreed with the sensory evaluation.A new computer-aid method of evaluating tobacco flavors was proposed.

     

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