Compositional Quantitation and Brand Identification of Beer via NMR Approach Combined with Multivariate Statistical Analysis
- 物理技术－已发表论文 
利用核磁共振技术检测福建产青岛、雪花、雪津麦之初和惠泉一麦等4种不同品牌啤酒的化学组分,结合多元统计方法分析不同啤酒的主成分差异,获得麦芽糖、葡萄糖、丙氨酸、乙酸等26种主要差异组分。并结合2种重要风味物质甘氨酸、丙酮酸,定量分析这28种主要成分,获得不同类型啤酒之间的组成差异及它们对啤酒风味的影响;进而建立啤酒的Fisher判别模型,实现不同品牌啤酒的鉴别。本研究可以检测不同来源啤酒样品的差异化学成分及含量,又可为其他酒类的鉴定分类提供参考。In this study, the chemical components of four beer samples of different brands including Tsingtao, Snow, Xuejin and Huiquan were quantitatively analyzed using NMR spectroscopy, and their differential components were identified by multivariate statistical analysis. 26 differential components were obtained, including maltose, glucose, alanine and organic acids. Quantitative analysis of the 26 components plus 2 important flavoring components glycine and pyruvate acid were carried out to confirm the compositional differences between these four kinds of beer and to understand their influence on the special flavor of beer. Furthermore, Fisher classification discriminant model was successfully established for the identification of beer of different brands. This study provided a new method to detect the chemical components and their content in beer of different brands, and a useful reference for the classification of other alcoholic drinks.