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固相微萃取-气相色谱/质谱法测定氮杂环挥发性香气化合物的方法开发:在酒精和木材基质中的应用。

Development of a Solid-Phase Microextraction-Gas Chromatography/Mass Spectrometry Method for Quantifying Nitrogen-Heterocyclic Volatile Aroma Compounds: Application to Spirit and Wood Matrices.

出版信息

J Agric Food Chem. 2019 Dec 11;67(49):13694-13705. doi: 10.1021/acs.jafc.9b05716. Epub 2019 Nov 22.

DOI:10.1021/acs.jafc.9b05716
PMID:31756091
Abstract

Over wood aging, matured spirits developed a complex aromatic bouquet where roasted-like notes were often perceived. Since many nitrogen heterocycles were related to these olfactory nuances, a headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-mass spectrometry was developed and validated to quantify them in both spirit and wood matrices. The various parameters affecting the extraction of the analytes from both spirit and wood samples were first investigated (i.e., fiber coating phase, dilution, pH and volume sample, adding salt, extraction time and temperature, and incubation time) to determine the best compromise for a single-run analysis of the whole set of studied compounds. Good linearity ( > 0.99), repeatability, reproducibility, accuracy and low detection, and quantification limits were obtained, making this analytical method a suitable tool for routine analysis of the selected nitrogen compounds. Fifteen pyrazines, three pyrroles, and three quinolines were quantified in a series of oak wood and commercial spirit samples where some of them were identified for the first time. The significant impact of some barrel features and the spirit in-wood maturation step on the -heterocycle profile in both matrices were finally discussed.

摘要

随着木材陈酿,陈酿烈酒发展出一种复杂的芳香气息,其中常常能感知到烘烤般的香气。由于许多含氮杂环化合物与这些嗅觉细微差别有关,因此开发并验证了顶空固相微萃取(HS-SPME)与气相色谱-质谱联用,以定量分析烈酒和木材基质中的这些化合物。首先研究了影响从烈酒和木材样品中提取分析物的各种参数(即纤维涂层相、稀释度、pH 值和样品体积、加盐、萃取时间和温度以及孵育时间),以确定单次运行分析整套研究化合物的最佳折衷方案。获得了良好的线性度(>0.99)、重复性、再现性、准确性和低检测限及定量限,使该分析方法成为常规分析所选含氮化合物的合适工具。在一系列橡木木材和商业烈酒样品中定量了 15 种吡嗪、3 种吡咯和 3 种喹啉,其中一些化合物是首次被鉴定出来的。最后讨论了一些桶特征和烈酒在木材中陈酿步骤对两个基质中杂环化合物分布的显著影响。

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