The hyphenation of static headspace sampling with comprehensive 2D GC equipped with a modulator based on capillary flow technology and a flame ionization detector was used to separate and identify 43 representative target volatile compounds (light hydrocarbons, carbonyls, pyrazines, alcohols, furans, and benzenes) frequently detected in the roasting process of nuts. Five column combinations with differing degrees of orthogonality (one conventional and four inverted phase sets) were tested in order to obtain the best conditions for analyzing these volatile compounds. Optimization of the working conditions for each of the different column combinations was performed by means of a central composite design. The best results in terms of separation and differentiation among the different chemical groups were achieved with a combination of inverted phase columns (first dimension: highly polar, INNOWax; second dimension: mid-polar, ZB-35). Additionally, a reference template was developed to provide an effective and rapid analysis of the target compounds. Finally, the proposed method was successfully employed to identify volatile compounds in raw and roasted almond samples from the Spanish cultivar Largueta.
Keywords: Almonds; Central composite design; Column selection; Static headspace; Volatile compounds.
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