Multivariate Optimization Procedure for Dynamic Headspace Extractions Coupled to GC(×GC)

Ryan P. Dias, Seo Lin Nam, Sheri A. Schmidt, A. P. de la Mata, J. Harynuk
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引用次数: 2

Abstract

Volatile organic compounds (VOCs) are ubiquitous chemicals of great interest in the study of aromas and flavours of foods. Many recent studies present optimized headspace (HS) and dynamic headspace (DHS) methods for specific sample types; however, the literature does not present ­(to the best of our knowledge) a generalized procedure for the thorough optimization of a DHS extraction. This article presents an approach using design of experiments (DoE) for the optimization of DHS extraction parameters. The approach is demonstrated for two different food sample types with diverse populations of VOCs: active sourdough colony as an example with a high moisture content, and sourdough bread as an example with a lower moisture content. Optimized methods are assessed for VOC extraction reproducibility and exhaustiveness; guidelines for DHS optimization are presented.
气相色谱耦合的动态顶空提取多元优化程序(×GC)
挥发性有机化合物(VOCs)是一种普遍存在的化学物质,在研究食物的香味和风味方面具有重要意义。最近的许多研究提出了针对特定样品类型的优化顶空(HS)和动态顶空(DHS)方法;然而,文献并没有提出(据我们所知)一个全面优化DHS提取的通用程序。本文提出了一种利用实验设计(DoE)优化DHS提取参数的方法。该方法在两种不同类型的食品样品中进行了验证:以高水分含量的活性酵母菌落为例,以低水分含量的酵母面包为例。对优化后的VOC提取方法的重现性和穷竭性进行了评估;提出了DHS优化的指导方针。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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