Expanding the Knowledge Related to Flavors and Fragrances by Means of Three-Dimensional Preparative Gas Chromatography and Molecular Spectroscopy

Abstract

As universally known, gas chromatography (GC) coupled with mass spectrometry (MS) allows us to acquire spectra that can be searched in specific databases to attain qualitative information on a peak of interest. When not present in databases, structure elucidation is required before including a new component in a library: from that moment, scientists all around the world will be able to identify the new molecule with analytical confidence after GC-MS analysis. Conversely, if data are not shared in commercial databases, even if a molecule is studied and elucidated, it appears to be unknown or only identifiable on the basis of third-party data taken from the literature, which is a serious limitation. The present paper deals with a case that confirms this assumption. A component of Myrtus communis L. volatile fraction was tentatively identified based on literature data. Despite this, reliable identification could not be achieved due to the lack of a corresponding spectrum in commercial MS databases. Afterwards, the target component was isolated in a reasonable quantity and with a high degree of purity for downstream characterization by spectroscopic techniques. For this purpose, preparative (prep) GC may appear insufficient for the isolation of volatile components from highly complex samples. In this study, a prep-MDGC system was implemented for the isolation of the compound of interest from myrtle oil, consisting of three wide-bore columns of different selectivity coupled by means of Deans switch transfer devices. Based on the NMR and GC-FTIR data acquired, the unknown compound was identified as 2,2,5,5,7,7-hexamethyl-3,7-dihydro-1-benzofuran-4,6(2H,5H)-dione. Noticeably, this is a known molecule, yet its mass spectrum had never been registered into MS databases and thus was not available to the scientific community. Finally, the spectrum was included for the first time in a commercial library, namely the FFNSC 5.0 MS database. The aim of the present study was to highlight the opportunity to make analytical data quickly available in a reliable way by registering them in searchable MS databases to improve the identification means for researchers all over the world.