采用模糊数学感官评价法优化蹄叶橐吾功能饮料的配方，得出最优配方为：蹄叶橐吾添加量8.0 g/L，罗汉果添加量6.0 g/L，蔗糖添加量40.0 g/L，甘草添加量1.0 g/L，此时的产品感官评分最高。运用电子鼻和电子舌技术测定蹄叶橐吾饮料和4种不同品牌饮料的气味和滋味，对所得数据进行主成分分析（PCA）和线性判别分析（LDA），得出PCA和LDA的第一、二组分总贡献率分别为99.1%、98.1%和87.22%、93.0%，均大于85%，在一定程度上可以反映样品整体情况。不同样品在PCA图和LDA图中的分布区域不同，表明样品间有较明显区分。与电子鼻相比，电子舌检测所得的同一种样品的分布点更加集中，不同种样品的分布区域较为分散，表明电子舌的检测区分度更高。蹄叶橐吾饮料与市面上销售的同类产品相比，气味和滋味有明显区别，丰富了饮料的多样性。

Sensory evaluation and fuzzy mathematics method were used to optimize the formula of hoof leaf ligularia functional beverage, the optimal formulas were as follows: 8.0 g/L of hoof leaf ligularia, 6.0 g/L of fructus momordicae, 40.0 g/L of sucrose , and 1.0 g/L of licorice. Electronic nose and tongue techniques were used to evaluate the odor and flavor of hoof leaf ligularia beverage and other four kinds of commercial functional drinks. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to investigate data. The total contribution rate of the first and second components of PCA were 99.1% and 98.1%, respectively, and LDA were 87.22% and 93.0%, respectively. They were all greater than 85% which indicated that the first and second components could represent the whole sample to some extent. The distribution areas of different samples in PCA and LDA diagrams were different, demonstrating that there were clear distinctions between the samples. Compared with the electronic nose, the data distribution of the same test sample detected by electronic tongue was more concentrated, and the distribution areas of different kinds of samples were more scattered, indicating that the discrimination of electronic tongue was more effective. Compared with the similar products sold on the market, the odor and flavor of hoof leaf ligularia functional beverage was different, which enriched the diversity of beverage.

长春工业大学大学生创新创业项目（2017cxcy175）