Back to Search
Start Over
Application of Comprehensive 2D Gas Chromatography Coupled with Mass Spectrometry in Beer and Wine VOC Analysis
- Source :
- Analytica, Vol 4, Iss 3, Pp 347-373 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- To meet consumer demand for fermented beverages with a wide range of flavors, as well as for quality assurance, it is important to characterize volatiles and their relationships with raw materials, microbial and fermentation processes, and the aging process. Sample preparation techniques coupled with comprehensive 2D gas chromatography (GC×GC) and mass spectrometry (MS) are proven techniques for the identification and quantification of various volatiles in fermented beverages. A few articles discuss the application of GC×GC for the measurement of fermented beverage volatiles and the problems faced in the experimental analysis. This review critically discusses each step of GC×GC-MS workflow in the specific context of fermented beverage volatiles’ research, including the most frequently applied volatile extraction techniques, GC×GC instrument setup, and data handling. The application of novel sampling techniques to shorten preparation times and increase analytical sensitivity is discussed. The pros and cons of thermal and flow modulators are evaluated, and emphasis is given to the use of polar-semipolar configurations to enhance detection limits. The most relevant Design of Experiment (DoE) strategies for GC×GC parameter optimization as well as data processing procedures are reported and discussed. Finally, some consideration of the current state of the art and future perspective, including the crucial role of AI and chemometrics.
- Subjects :
- GC×GC-MS
VOC
data processing
Analytical chemistry
QD71-142
Subjects
Details
- Language :
- English
- ISSN :
- 26734532
- Volume :
- 4
- Issue :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- Analytica
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.6e1bba128e9e4cd1a02e0b6edff00f08
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/analytica4030026