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Usefulness of GC-IMS for rapid quantitative analysis without sample treatment: Focus on ethanol, one of the potential classification markers of olive oils.

Authors :
Contreras, María del Mar
Aparicio, Luis
Arce, Lourdes
Source :
LWT - Food Science & Technology. Feb2020, Vol. 120, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

The usefulness of headspace (HS)-gas chromatography (GC)-ion mobility spectrometry (IMS) has been explored for quantitative purposes, focusing on ethanol in olive oils. For that, since this emerging analytical tool provides a 2D analysis, different calibration curves were built using the height, area and volume of the detected species, i.e. a protonated monomer and a proton-bound dimer of ethanol. The methodology was validated and the quantification results compared to those obtained by GC coupled to more conventional detectors. Once then, the content of ethanol was determined in 81 olive oil samples. The ethanol content was lower than 12 mg/kg for 89% of extra virgin olive oil samples, whereas it was higher than 12 mg/kg for around 90% of virgin olive oil samples. This concentration value was used as a limit to support the decision-making process for olive oil classification into extra virgin, virgin, and lampante olive oil by complementary methods, sensory analysis and chemometrics. In conclusion, the proposed HS-GC-IMS method requires no sample pretreatment, shows low limits of detection (0.095 mg/kg) and quantification (0.100 mg/kg) and is faster enough to monitor the content of this marker in olive oils in the industry. • GC-IMS for rapid quantitative analysis of ethanol in olive oils. • Ethanol is a potential classification marker of extra virgin and virgin olive oils. • Alternatively, lampante olive oils show no clear trends concerning the ethanol content. • The determination of ethanol in olive oil do not requires sample pretreatment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00236438
Volume :
120
Database :
Academic Search Index
Journal :
LWT - Food Science & Technology
Publication Type :
Academic Journal
Accession number :
141218131
Full Text :
https://doi.org/10.1016/j.lwt.2019.108897