Determination of Mineral Oil Hydrocarbons in Rice and Noodles using LC-GC Online Technique

Significance of the Topic

The presence of mineral oil hydrocarbons (MOSH and MOAH) in food represents a growing health and regulatory concern. These compounds can migrate from packaging inks and production equipment into dry foods such as rice and noodles. Chronic exposure carries potential risks, including the accumulation of MOSH in body fat and the possible carcinogenic properties of MOAH. Establishing reliable analytical limits and routine monitoring is critical to protect consumers and comply with European regulations.

Objectives and Study Overview

This study aimed to develop and validate an online hyphenated LC–GC–FID method for the rapid, automated determination of MOSH and MOAH in rice and noodle samples. Key goals included simplifying sample preparation, achieving high throughput, and meeting performance criteria defined by EN 16995:2017 and related EU recommendations.

Methodology and Instrumentation

The analytical workflow integrates normal-phase HPLC with GC–FID through an automated interface:

• Sample Preparation: Simple extraction of dry rice and noodle powder without manual cleanup or SPE steps.
• Online HPLC Pre-separation: Normal-phase column separates MOSH and MOAH fractions and removes wax esters and other interferences.
• LC–GC Transfer: Heart cuts of defined molecular weight ranges are transferred directly to the GC.
• Detection: Dual FID detectors record the saturated (MOSH) and aromatic (MOAH) hydrocarbon “humps.”

Instrument configuration:

• Shimadzu Nexera UHPLC system (two LC-20ADXR pumps, CBM-20A controller, SPD-20A UV detector)
• Shimadzu GC-2030 with two FID detectors
• PAL autosampler and CHRONOS software automated control
• LabSolutions platform for data acquisition and analysis

Key Results and Discussion

Analytical performance parameters met regulatory requirements:

• Spaghetti Sample: MOSH measured at 12.7 mg/kg in the C16–C35 range, with clear separation of C16–C25 and C25–C35 subfractions.
• Rice Sample: Detected naturally occurring odd-numbered alkanes (C21–C35) in addition to MOSH/MOAH humps.
• Reproducibility and Accuracy: Integration of defined molecular weight regions according to BfR guidelines provided consistent quantification.
• Throughput: Fully automated sequence enabled rapid analysis cycles suitable for routine laboratory workloads.

Benefits and Practical Applications

The online LC–GC method offers:

• Elimination of manual purification steps, reducing labor and solvent use.
• High sample throughput and minimal risk of cross-contamination.
• Robust and stable hardware design for routine operation.
• Compliance with EN 16995:2017, EU 2017/84, and EFSA guidance.

Future Trends and Potential Applications

Emerging directions include:

• Extension to fatty food matrices via optimized sample preparation for oils and fats.
• Integration of mass spectrometric detection for structural identification of MOAH components.
• Development of standardized protocols across multiple food commodities to harmonize global monitoring.
• Implementation of AI-driven data evaluation tools to enhance throughput and interpret complex chromatograms.

Conclusion

The described LC–GC–FID system provides a fast, reliable, and fully automated solution for routine monitoring of MOSH and MOAH in dry foodstuffs. Its simplified workflow, coupled with regulatory compliance and high analytical performance, makes it a valuable tool for food safety laboratories and quality control in the food industry.

References

1. EFSA Journal 2012;10(6):2704 Mineral Oil Hydrocarbons in Food
2. EU Commission Recommendation 2017/84 of 16 January 2017
3. EN 16995:2017 Foodstuffs – Determination of MOSH and MOAH with online HPLC–GC–FID
4. BfR Bestimmung von Kohlenwasserstoffen aus Mineralöl oder Kunststoffen