Trust Your Results in Mineral Oil Analysis

Importance of the Topic

Mineral oil hydrocarbons (MOH) are emerging contaminants in food, packaging, cosmetics and pharmaceuticals. Recent incidents, including MOH found in infant formula in 2019, have underscored the urgent need for robust analytical workflows. Accurate identification and quantification of MOH are critical for consumer safety, regulatory compliance and harmonization of control methods across laboratories.

Objectives and Study Overview

• Develop a unified workflow combining liquid–gas chromatography with comprehensive two-dimensional GC (GC×GC) and time-of-flight mass spectrometry (TOFMS) alongside flame ionization detection (FID).
• Implement a dedicated ChromaTOF software version for reliable integration and interpretation of unresolved GC humps.
• Compare performance and quantitation against the conventional LC-GC-FID reference method recommended by EU authorities.

Methodology and Instrumentation

An LC-GC×GC-TOFMS/FID platform was assembled. MOSH and MOAH fractions were separated by online LC, transferred through an LC-GC interface into a thermal modulator and split to both FID and TOFMS detectors. Internal and retention-time standards were used for quantification and carbon-range definitions. Samples included a paraffin oil spiked with a C8–C40 alkane mixture and two real animal-feed matrices. Data processing and hump integration were performed in ChromaTOF with a novel algorithm for trimming riding peaks and subtracting column bleed.

Used Instrumentation

• LC: Agilent 1260 Infinity II with Allure Silica column and VWD at 230 nm
• LC-GC Interface: CHRONECT LC-GC (Axel Semrau)
• Thermal Modulation: LECO GC×GC QuadJet™ modulator
• 1D Column: Rxi-17SilMS (15 m × 0.25 mm × 0.25 µm)
• 2D Column: Rxi-1ms (2 m × 0.15 mm × 0.15 µm)
• Detectors: LECO Pegasus BT 4D TOFMS and FID

Key Results and Discussion

Performance checks with retention-time standards confirmed stable response factors (0.8–1.2 range). The ChromaTOF trimming algorithm effectively removed narrow peaks riding on unresolved MOSH/MOAH humps in both 1D and reconstructed 2D data, yielding clean chromatograms for integration. TOFMS data enabled spectral filters and library matches for confident identification of alkyl aromatics (C10–C50). Quantitative comparison of triplicate analyses on spiked paraffin oil showed agreement with expected MOSH (3.7 %) and MOAH (2.2 %) values. Results on animal feed samples demonstrated consistency between LC-GC-FID and LC-GC×GC-TOFMS/FID for total C10–C50 MOSH and MOAH content.

Benefits and Practical Applications

• Significant reduction in integration uncertainty via automated hump trimming.
• Enhanced selectivity through parallel TOFMS detection and spectral filtering.
• Compliance with EU reference methodology while providing confirmatory data.
• Streamlined workflow for control and commercial laboratories assessing MOH contamination.

Future Trends and Opportunities

• Further standardization of GC×GC-TOFMS protocols for MOH across international laboratories.
• Extension of the method to additional petroleum-based contaminants and food matrices.
• Integration of machine-learning algorithms for improved peak deconvolution and classification.
• Real-time monitoring and high-throughput screening in industrial QA/QC environments.

Conclusion

The unified LC-GC×GC-TOFMS/FID methodology, supported by a dedicated ChromaTOF software algorithm, delivers reliable qualitative and quantitative data for MOSH and MOAH analysis. It addresses key limitations of non-selective GC-FID methods by automating hump integration and leveraging mass spectral confirmation, representing a state-of-the-art advancement in mineral oil analysis.

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