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Comparison of Three Methods for Extraction of Volatile Lipid Oxidation Products from Food Matrices for GC–MS Analysis

  • Original Paper
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Journal of the American Oil Chemists' Society

Abstract

The aim of this study was to compare three different collection methods; purge and trap, solid phase micro extraction and automated dynamic headspace/thermal desorption, all followed by GC–MS analysis used for the measurements of concentrations of volatile oxidation products in three different food matrices, namely oil, emulsion and milk. The linearity ranges of calibration curves obtained by the three different methods were compared for oil samples. Overall, the results showed that the three collection methods were comparable, although there were large differences in the linearity range of the calibration curves depending on the collection method. However, some challenges were observed for solid phase micro extraction and automated dynamic headspace/thermal desorption, namely, competition problems and overestimation of concentration by calibration curves, respectively. Based on the results, we suggest mainly to apply solid phase micro extraction on simple matrices and to be cautious with more complex matrices such as enriched milk and highly oxidized oils. Thereby, the study confirmed some challenges observed by other authors regarding competition problems on the fiber when using solid phase micro extraction. Furthermore, we observed that purge and trap, and automated dynamic headspace/thermal desorption were excellent for extraction of volatile compounds in all three matrices. However, automated dynamic headspace/thermal desorption calibration curves did provide an overestimation for oil samples so results must be interpreted with caution.

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Fig. 1

Adapted from Gerstel [15]

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Correspondence to Birgitte Raagaard Thomsen.

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Thomsen, B.R., Yesiltas, B., Sørensen, AD.M. et al. Comparison of Three Methods for Extraction of Volatile Lipid Oxidation Products from Food Matrices for GC–MS Analysis. J Am Oil Chem Soc 93, 929–942 (2016). https://doi.org/10.1007/s11746-016-2837-2

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  • DOI: https://doi.org/10.1007/s11746-016-2837-2

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