4.5 Review

Aroma determination in alcoholic beverages: Green MS-based sample preparation approaches

期刊

MASS SPECTROMETRY REVIEWS
卷 -, 期 -, 页码 -

出版社

WILEY
DOI: 10.1002/mas.21802

关键词

alcoholic beverages; green extraction; mass spectrometry; sample preparation; volatile odoractive compounds

向作者/读者索取更多资源

Determining aroma in alcoholic beverages is a popular research topic, and the development of sample preparation strategies using miniaturized techniques and mass spectrometry has gained attention. These techniques offer a solution to address the complexity of the matrices in alcoholic beverages and reduce environmental impact.
Aroma determination in alcoholic beverages has become a hot research topic due to the ongoing effort to obtain quality products, especially in a globalized market. Consumer satisfaction is mainly achieved by balancing several aroma compounds, which are mixtures of numerous volatile molecules enclosed in challenging matrices. Thus, sample preparation strategies for quality control and product development are required. They involve several steps including copious amounts of hazardous solvents or time-consuming procedures. This is bucking the trend of the ever-increasing pressure to reduce the environmental impact of analytical chemistry processes. Hence, the evolution of sample preparation procedures has directed towards miniaturized techniques to decrease or avoid the use of hazardous solvents and integrating sampling, extraction, and enrichment of the targeted analytes in fewer steps. Mass spectrometry coupled to gas or liquid chromatography is particularly well suited to address the complexity of these matrices. This review surveys advancements of green miniaturized techniques coupled to mass spectrometry applied on all categories of odor-active molecules in the most consumed alcoholic beverages: beer, wine, and spirits. The targeted literature consider progresses over the past 20 years.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据