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基于双质谱和宽带真空紫外吸收检测的顶空固相微萃取高容量纤维涂层用于气相色谱法对啤酒挥发物进行非靶向分析的比较

Comparison of headspace solid-phase microextraction high capacity fiber coatings based on dual mass spectrometric and broadband vacuum ultraviolet absorption detection for untargeted analysis of beer volatiles using gas chromatography.

作者信息

Zanella Delphine, Anderson Hailee E, Selby Talena, Magnuson Robert H, Liden Tiffany, Schug Kevin A

机构信息

University of Liege, Molecular System, Organic & Biological Analytical Chemistry Group, 11 Allee Du Six Aout, 4000, Liege, Belgium.

Department of Chemistry and Biochemistry, The University of Texas at Arlington, 700 Planetarium Place, Arlington, TX, 76019, USA.

出版信息

Anal Chim Acta. 2021 Jan 2;1141:91-99. doi: 10.1016/j.aca.2020.10.026. Epub 2020 Oct 19.

Abstract

Despite the same basic ingredients used in brewing, there is a significant variation in beer styles. With the rapid increase in craft brewing, beer styles have become even more numerous and complex in the recent past. A GC-MS/VUV (post-column split for dual detection) instrument with headspace high capacity SPME was used to investigate 21 different beers which represent three beer styles - India pale ales, blondes, and hefeweizens. Since results from untargeted studies can be affected by the sorbent material used, the extraction performances of three high capacity SPME fibers, i.e., polydimethylsiloxane, polydimethylsiloxane/carbon wide range, and polydimethylsiloxane/carbon wide range/divinylbenzene, were evaluated. Good reproducibility (<10% RSD) was obtained for each high capacity fiber using both detectors. The tandem MS/VUV detection coupled with GC separation proved to be particularly valuable for compound identification, especially for isomers and compounds with similar structures. The evaluation of VUV detection for untargeted analysis led to similar performances as MS detection. Both the VUV and the MS were able to effectively differentiate between beer styles using principal component analysis. In addition, the use of 3 different statistical approaches, one-way ANOVA (p-value < 0.05), partial least square discriminant analysis, and random forest, universally identified 12 of the components most influential in distinguishing the three beer styles (e.g., β-myrcene, linalool, isopentyl acetate, 2,4-di-tert-butylphenol). This is the first reported evaluation of VUV detection and the first comparison of simultaneous VUV and MS detection for untargeted classification of complex mixtures using GC.

摘要

尽管酿造啤酒使用的基本原料相同,但啤酒的风格却有很大差异。随着精酿啤酒的迅速增长,啤酒风格在最近变得更加多样和复杂。使用配备顶空高容量固相微萃取(SPME)的气相色谱-质谱联用/真空紫外光(柱后分流用于双重检测)仪器,对代表三种啤酒风格的21种不同啤酒进行了研究,这三种啤酒风格分别是印度淡色艾尔啤酒、金色啤酒和德式小麦啤酒。由于非靶向研究的结果可能会受到所用吸附剂材料的影响,因此评估了三种高容量SPME纤维,即聚二甲基硅氧烷、聚二甲基硅氧烷/碳宽范围和聚二甲基硅氧烷/碳宽范围/二乙烯基苯的萃取性能。使用两种检测器,每种高容量纤维都获得了良好的重现性(相对标准偏差<10%)。气相色谱分离与串联质谱/真空紫外光检测相结合被证明对化合物鉴定特别有价值,尤其是对异构体和结构相似的化合物。对真空紫外光检测用于非靶向分析的评估得出了与质谱检测相似的性能。真空紫外光和质谱都能够使用主成分分析有效地区分啤酒风格。此外,使用三种不同的统计方法,即单因素方差分析(p值<0.05)、偏最小二乘判别分析和随机森林,普遍确定了区分这三种啤酒风格最具影响力的12种成分(例如,β-月桂烯、芳樟醇、乙酸异戊酯、2,4-二叔丁基苯酚)。这是首次报道的对真空紫外光检测的评估,也是首次比较气相色谱用于复杂混合物非靶向分类的同时真空紫外光和质谱检测。

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