Advanced method optimization for volatile aroma profiling of beer using two-dimensional gas chromatography time-of-flight mass spectrometry

被引:71
作者
Stefanuto, Pierre-Hugues [1 ]
Perrault, Katelynn A. [1 ,2 ]
Dubois, Lena M. [1 ]
L'Homme, Benjamin [1 ]
Allen, Catherine [1 ]
Loughnane, Caitriona [1 ]
Ochiai, Nobuo [3 ]
Focant, Jean -Francois [1 ]
机构
[1] Univ Liege, Dept Chem, Organ & Biol Analyt Chem Grp CART, Allee Six Aout 11,B6c, B-4000 Liege, Belgium
[2] Chaminade Univ Honolulu, Forens Sci Unit, 3140 Waialae Ave, Honolulu, HI 96815 USA
[3] Gerstel KK, Meguro Ku, 2-13-18 Nakame, Tokyo 1520031, Japan
关键词
GCxGC; Method optimization; Multivariate statistics; Beer; Aroma; Volatile organic compounds; BAR SORPTIVE EXTRACTION; SMOKE PARTICULATE PHASE; X GC-TOFMS; MULTIVARIATE-ANALYSIS; FERMENTATION; SAMPLES; FLAVOR;
D O I
10.1016/j.chroma.2017.05.064
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The complex mixture of volatile organic compounds (VOCs) present in the headspace of Trappist and craft beers was studied to illustrate the efficiency of thermal desorption (TD) comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC x GC-TOFMS) for highlighting subtle differences between highly complex mixtures of VOCs. Headspace solid-phase microextraction (HS-SPME), multiple (and classical) stir bar sorptive extraction (mSBSE), static headspace (SHS), and dynamic headspace (DHS) were compared for the extraction of a set of 21 representative flavor compounds of beer aroma. A Box-Behnken surface response methodology experimental design optimization (DOE) was used for convex hull calculation (Delaunay's triangulation algorithms) of peak dispersion in the chromatographic space. The predicted value of 0.5 for the ratio between the convex hull and the available space was 10% higher than the experimental value, demonstrating the usefulness of the approach to improve optimization of the GC x GC separation. Chemical variations amongst aligned chromatograms were studied by means of Fisher Ratio (FR) determination and F-distribution threshold filtration at different significance levels (alpha = 0.05 and 0.01) and based on z-score normalized area for data reduction. Statistically significant compounds were highlighted following principal component analysis (PCA) and hierarchical cluster analysis (HCA). The dendrogram structure not only provided clear visual information about similarities between products but also permitted direct identification of the chemicals and their relative weight in clustering. The effective coupling of DHS-TD-GC x GC-TOFMS with PCA and HCA was able to highlight the differences and common typical VOC patterns among 24 samples of different Trappist and selected Canadian craft beers. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:45 / 52
页数:8
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