Identification of terpenes and essential oils by means of static headspace gas chromatography-ion mobility spectrometry.
Anal Bioanal Chem
; 409(28): 6595-6603, 2017 Nov.
Article
em En
| MEDLINE
| ID: mdl-28932891
Static headspace gas chromatography-ion mobility spectrometry (SHS GC-IMS) is a relatively new analytical technique that has considerable potential for analysis of volatile organic compounds (VOCs). In this study, SHS GC-IMS was used for the identification of the major terpene components of various essential oils (EOs). Based on the data obtained from 25 terpene standards and 50 EOs, a database for fingerprint identification of characteristic terpenes and EOs was generated utilizing SHS GC-IMS for authenticity testing of fragrances in foods, cosmetics, and personal care products. This database contains specific normalized IMS drift times and GC retention indices for 50 terpene components of EOs. Initially, the SHS GC-IMS parameters, e.g., drift gas and carrier gas flow rates, drift tube, and column temperatures, were evaluated to determine suitable operating conditions for terpene separation and identification. Gas chromatography-mass spectrometry (GC-MS) was used as a reference method for the identification of terpenes in EOs. The fingerprint pattern based on the normalized IMS drift times and retention indices of 50 terpenes is presented for 50 EOs. The applicability of the method was proven on examples of ten commercially available food, cosmetic, and personal care product samples. The results confirm the suitability of SHS GC-IMS as a powerful analytical technique for direct identification of terpene components in solid and liquid samples without any pretreatment. Graphical abstract Fingerprint pattern identification of terpenes and essential oils using static headspace gas chromatography-ion mobility spectrometry.
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Base de dados:
MEDLINE
Assunto principal:
Terpenos
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Óleos Voláteis
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Espectrometria de Mobilidade Iônica
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Cromatografia Gasosa-Espectrometria de Massas
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article