Application Note: 3-MCPD/Glycidol: ISO-18363-4 Automated Zwagerman Method
Automated preparation and GC/MS analysis of oil for 3-MCPD and Glycidol based on ISO 18363-4 with isotope standards for speed, trueness, and precision
This appliation note describes a solution for fully automated determination of 3-MCPD, 2-MCPD, and Glycidol in edible oils based on method ISO 18363-4, often referred to as “Zwagerman/Overman”. Glycidol, 3-MCPD, and 2-MCPD are determined in a single GC/MS assay based on established calibration curves. To accurately quantify the amount of 3-MCPD converted to glycidol, which would otherwise lead to glycidol overestimation, the method applies 13C-correction. Workflow:
The oil or fat sample is dissolved in toluene and methyl-tert-butyl-ether (MTBE). Subsequently, the internal standards 3-MCPD-13C3 diester, as internal standard for 3-MCPD and 2-MCPD, and pentadeuterated glycidyl ester as internal standard for glycidol are added. The sample is cooled to 10 °C and alkaline transesterification is initiated by addition of a sodium methoxide solution in methanol. After 12 min incubation at 10 °C, the sample mixture is acidified with an acidic solution of sodium bromide to convert the released glycidol to 3-MBPD. The fatty acid methyl esters generated during the transesterification are removed by extracting twice with iso-octane.
The polar analytes remain in the aqueous phase and are derivatized with phenylboronic acid for GC-MS/MS determination. A pre-column backflush keeps phenylboronic acid and major matrix constituents from entering and contaminating the analytical column and mass spectrometer. More than 30 different real samples were analysed, no interfering matrix peaks or other chromatographic or mass spectral issues were observed. The sample preparation method works ruggedly. Analyte concentrations were calculated according to chapter 9.2 and 9.3 of the standard and analysis results for a proficiency test sample and for a sample analysed by an external laboratory corresponded well with the obtained results. The excellent standard deviations achieved for the complete analysis workflow speak in favour of automation.