The topic: The EU Commission proposes new lower maximum levels ​​for aromatic mineral oil hydrocarbons in food. Companies are using the remaining time before implementation to check their products for compliance with the new levels. This, and the associated increasing demand for corresponding analytical services, is a challenging opportunity for contract laboratories: Mineral oil residue analysis is complex, and a high degree of automation is required to process large sample series in a reliable and efficient manner. 

When the term mineral oil residues is used in food context, saturated (mineral oil saturated hydrocarbons, MOSH) and aromatic compounds (mineral oil aromatic hydrocarbons, MOAH) are the compound classes mainly referred to. In the European Food Safety Authority (EFSA) assessment, MOSH does not present a public health risk at current levels of dietary exposure. MOAH, however, is problematic due to the presence of known genotoxic and carcinogenic compounds. The EU Commission has therefore proposed maximum values ​​for MOAH in food effective late 2024 or early 2025:  

  • 0.5 mg/kg for products with ≤ 4 % fat/oil content  
  • 1.0 mg/kg for products with > 4 % and ≤ 50 % fat/oil content and  
  • 2.0 mg/kg for products with > 50 % fat/oil content 

The challenge in MOSH/MOAH analysis is to extract a large number of chemically diverse hydrocarbons (C10-C50) from highly matrix-laden samples, followed by the separation and quantitative determination of the compounds. Numerous sample preparation steps must be performed to remove interfering substances before determining the MOSH and MOAH levels in a food by GC-FID. When performed manually, MOSH/MOAH analysis has proven inefficient, labor intensive and error prone. 

The solution lies in automating the MOSH/MOAH analysis including the sample preparation such as saponification of interfering triglycerides, removal of interfering n-alkanes via activated aluminum oxide (AlOx), as well as of olefins by epoxidation. Extracts can be processed automatically in an integrated analytical solution consisting of a MultiPurpose Sampler (MPS robotic Pro), HPLC and GC-FID. Complex processes such as saponification and epoxidation can also be performed 24/7 independent of the analysis system using a separate robotic sampler to ensure high throughput and efficient processing.  

The Hardware in the GERSTEL MOSH/MOAH solution consists of an Agilent 1260 Infinity II HPLC system and a dual channel GC-FID system (Agilent 8890 GC). The systems are coupled via an LC-GC interface (GERSTEL) and outfitted with an autosampler (GERSTEL MPS roboticPro) for automated sample preparation and sample introduction. A special GC column mounting system offers easy access to the GC columns and connections for quick and easy replacement and maximum up-time. The column connection technology, in turn, ensures permanently gas-tight connections even after the columns have been disconnected and reconnected several times. The user controls all system parameters and can easily rinse or replace the guard columns. The modularity of the system ensures that it is easily and quickly adapted to any changes in laboratory requirements.  

Technical details: The food sample extract to be analyzed for MOSH/MOAH is cleaned and fractionated using normal phase liquid chromatography (NP-HPLC) based on polarity differences. The MOSH fraction elutes before the MOAH fraction; n-hexane and dichloromethane (DCM) are used as eluents, with the DCM ratio first increasing from 0 to 35 %, then to 100 % (column backflush), and finally reduced to 0 %. Matrix residue is backflushed from the column with 100 % DCM and the column reconditioned with 100 % n-hexane in forward flow. After HPLC separation, the large-volume MOSH and MOAH fractions (450 µL each) are individually transferred to the dual channel GC-FID system for simultaneous parallel determination. To prevent overloading of the separation columns, the solvent is evaporated and vented through a separate outlet (GERSTEL Early Vapor Exit, EVE). GC separation is followed by detection (FID) of the analytes. Individual quantification of the analytes is not performed, but rather the total amount of hydrocarbons (C10 - C50) is determined; the result is total amounts with individually added load ranges. For the MOSH/MOAH analysis, a mixture of nine different internal standards is used, which are not only used for quantification, but also to mark the beginning and end of the MOSH and MOAH fraction elution respectively, and to verify overall system performance. 

Outstanding features: As an example, consider the removal of naturally occurring n-alkanes of plant origin from the MOSH fraction using activated aluminum oxide (AlOx) in a manual process: Depending on the food type, the AlOx must be activated in the oven for between 40 and 60 hours at 400 °C and then manually loaded onto a disposable glass column, only to be disposed after each analysis. The manual procedure not only requires a lot of manual work, but also lots of material. In the standard AlOx process, not only n-alkanes, but also MOAH are removed and therefore a second measurement is required, in which the AlOx cleanup is omitted in order to quantify the MOAH fraction loss. The automated process used in the GERSTEL system eliminates the second analysis step since the AlOx column is inserted after the LC separation. This means we save work, time and valuable resources. 

Expert opinion: In addition to reducing the number of manual process steps which are highly labor intensive and require a lot of time, automation of MOSH/MOAH analysis offers several added benefits: It reduces the risk of errors and improves efficiency, reliability and reproducibility while enabling 24/7 analysis throughput. In addition, the simplified process enhances laboratory sustainability, efficiency, and productivity. Speaking of which: Processing ​​ MOSH/MOAH data can be tricky and time-consuming, especially if done using spreadsheet tables. GERSTEL provides a powerful software package that enables easy and reliable MOSH/MOAH data processing with easy to assess graphical representations: Why accept a difficult work process when life can be so easy?

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