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结合吹扫捕集、全二维气相色谱和质谱研究香气多样性。

Investigating aroma diversity combining purge-and-trap, comprehensive two-dimensional gas chromatography, and mass spectrometry.

机构信息

Molecular System, Organic & Biological Analytical Chemistry Group, University of Liège, Liège, Belgium.

Institute of Chemistry, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.

出版信息

J Sep Sci. 2020 May;43(9-10):1790-1799. doi: 10.1002/jssc.201900902. Epub 2019 Nov 18.

DOI:10.1002/jssc.201900902
PMID:31674101
Abstract

Headspace gas chromatography is frequently used for aroma profiling thanks to its ability to naturally exploit the volatility of aroma compounds, and also to provide chemical information on sample composition. Its main advantages rely on simplicity, no use of solvent, amenability to automation, and the cleanliness of the extract. In the present contribution, the most effective sampling (dynamic extraction), separation (multidimensional gas chromatography), and detection (mass spectrometry) techniques for untargeted analysis are exploited in combination, showing their potential in unraveling aroma profiles in fruit beers. To complete the overall analytical process, a neat workflow for data analysis is discussed and used for the successful characterization and identification of five different beer flavors (berries, cherry, banana, apple, and peach). From the technical viewpoint, the coupling of purge-and-trap, comprehensive two-dimensional gas chromatography, and mass spectrometry makes the global methodology unique, and it is for the first time discussed. A (low-)flow modulation approach allowed for the full transfer into the second dimension with mass-spectrometry compatible flow (< 7 mL/min), avoiding the need of splitting before detection and making the overall method sensitive (1.2-5.2-fold higher signal to noise ratio compared to unmodulated gas chromatography conditions) and selective.

摘要

顶空气相色谱法由于其能够自然利用香气化合物的挥发性,以及提供有关样品组成的化学信息,因此常用于香气剖析。其主要优点在于简单、不使用溶剂、易于自动化以及提取物清洁。在本研究中,将最有效的采样(动态提取)、分离(多维气相色谱)和检测(质谱)技术结合起来进行非靶向分析,展示了它们在揭示水果啤酒香气特征方面的潜力。为了完成整个分析过程,还讨论并使用了一种简洁的数据分析工作流程,成功地对五种不同的啤酒风味(浆果、樱桃、香蕉、苹果和桃子)进行了特征描述和鉴定。从技术角度来看,吹扫捕集、全二维气相色谱和质谱的结合使整体方法具有独特性,这也是首次进行讨论。采用(低)流量调制方法,可以将全二维气相色谱兼容的流量(<7 mL/min)完全转移到第二维,避免在检测前进行分流,从而使整个方法具有较高的灵敏度(与未调制气相色谱条件相比,信噪比提高了 1.2-5.2 倍)和选择性。

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