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

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. KEY POINTS * Design of experiments (DoE) modelling for dynamic headspace (DHS) extractions. * Sample type impacts on design of DHS extractions. * DoE yields reproducible, predictable extraction methods.
Mixtures of volatile organic compounds (VOCs) emanate from foods and beverages during human consumption, and these compounds blend together to create flavours and aromas. While many VOCs are present endogenously [...]