基于电子鼻的葡萄酒感官评价模型的构建

利用PEN3电子鼻检测10种不同菌株酿造的葡萄酒及1瓶商业葡萄酒样的香气,并通过电子鼻WinMuster及SPSS 19.0软件进行模式识别分析,评价基于不同模式识别分析方法电子鼻对不同菌株葡萄酒的区分效果;建立葡萄酒感官评价的综合主成分评价模型,并用该模型对这11种葡萄酒进行感官评价,进一步通过传统的专业品尝员对葡萄酒感官评价方法检测所建综合主成分模型的评价效果。结果表明,基于主成分分析与线性判别分析,电子鼻可以更好地区分不同菌株酿造的葡萄酒样;另外所建模型对葡萄酒的感官评价结果与传统感官评价方法具有较好的一致性,为进行更客观的葡萄酒感官评价提供了新的途径及一定的参考。

Model for wine sensory evaluation based on electronic nose

Using PEN3 electronic nose to detect the aroma of 10 wines fermented with different strains and a commercial wine sample. Different pattern recognition analysis methods were used to evaluate whether the distinguish effect of electronic nose on different wines, and principal component analysis was used to build a model for wine sensory evaluation by the software of WinMuster and SPSS 19.0, respectively. The 11 wines were evaluat- ed by the model, further evaluated by traditional professional taster for comprehensive evaluation effect of principal component model. Result showed that based on principal component analysis and linear discriminant analysis, the electronic nose can distinguish the differences of the wine better. The model built had good consistency with traditional sensory evaluation methods, providing a new approach for more objective wine sensory evaluation.