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中国精品科技期刊2020
刘超, 田鹏, 刘莎, 张超, 刘占奇, 李梦, 董孝元. 浓香型白酒饮用舒适度与白酒中微量成分相关性分析[J]. 食品工业科技, 2018, 39(12): 255-260. DOI: 10.13386/j.issn1002-0306.2018.12.045
引用本文: 刘超, 田鹏, 刘莎, 张超, 刘占奇, 李梦, 董孝元. 浓香型白酒饮用舒适度与白酒中微量成分相关性分析[J]. 食品工业科技, 2018, 39(12): 255-260. DOI: 10.13386/j.issn1002-0306.2018.12.045
LIU Chao, TIAN Peng, LIU Sha, ZHANG Chao, LIU Zhan-qi, LI Meng, DONG Xiao-yuan. Correlation analysis between the liquor drinking comfort degree and the microconstituents in the strong flavour Chinese spirits[J]. Science and Technology of Food Industry, 2018, 39(12): 255-260. DOI: 10.13386/j.issn1002-0306.2018.12.045
Citation: LIU Chao, TIAN Peng, LIU Sha, ZHANG Chao, LIU Zhan-qi, LI Meng, DONG Xiao-yuan. Correlation analysis between the liquor drinking comfort degree and the microconstituents in the strong flavour Chinese spirits[J]. Science and Technology of Food Industry, 2018, 39(12): 255-260. DOI: 10.13386/j.issn1002-0306.2018.12.045

浓香型白酒饮用舒适度与白酒中微量成分相关性分析

Correlation analysis between the liquor drinking comfort degree and the microconstituents in the strong flavour Chinese spirits

  • 摘要: 目的:通过分析浓香型白酒饮用舒适度与白酒中微量成分之间的相关性,为浓香型白酒舒适度的评价提供指导。方法:使用气相色谱仪(GC)对白酒中的微量成分进行定量检测,运用饮用后感受评价表对各不同白酒进行舒适度评价,评分越高,说明白酒饮用舒适度越好。结果:通过对浓香型白酒不同样品的微量组分进行主成分分析,可以得到各档次白酒的综合指标得分,将感官得分与其建立起一种联系,能够得到四次方的回归方程X=54.76F4+53.936F3-20.175F2+11.629F+60.978,R2=0.9999。结论:该模型能够较为准确的对白酒档次进行分级,为不同种浓香型白酒的品质识别提供理论支持。

     

    Abstract: Objective:By analyzing the correlation between the Liquor drinking comfort degree and the microconstituents in the strong flavour Chinese spirits to provid guidance for the evaluation of the comfort level of the strong flavour Chinese spirits.Methods:Used GC to analyze the microconstituents in the strong flavour Chinese spirits,and used the HES tables to evaluate the different liquor drinking comfort degree.The higher the score,the better the drinking comfort degree.Result:Through the principal component of microconstituents,there was a certain correlation between liquor drinking comfort degree score and the microconstituents.It can get the quadratic regression equation X=54.76F4+53.936F3-20.175F2+11.629F+60.978,R2=0.9999. Conclusion:The model could classify the grade of liquor more accurately and provide theoretical support for the quality identification of different kinds of spiced liquor.

     

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