Characterizing unknowns in food packaging using GC Orbitrap Mass Spectrometry

Importance of the Topic

This study addresses the critical issue of chemical migration from food packaging into consumables. Packaging materials are essential for preserving food quality and safety, yet non-intentionally added substances (NIAS) such as impurities, reaction by-products and breakdown products can leach into food. Comprehensive identification of these unknowns is vital for assessing potential health risks and ensuring regulatory compliance.

Objectives and Study Overview

The primary goal was to develop a rapid, non-targeted workflow for characterizing unknown compounds in food packaging coatings. Using a tin can internal coating extract, the study employed high-resolution full-scan GC-Orbitrap MS with electron ionization (EI) and positive chemical ionization (PCI) to detect, identify and structurally elucidate intense but previously unassigned peaks.

Methodology and Instrumentation

Sample Preparation:

• Extraction of coating material using hexane:acetone (1:1) at room temperature for 16 h.
• Concentration of extract to ≈1 mL for GC analysis.

Used Instrumentation:

• Thermo Scientific Q Exactive GC Orbitrap mass spectrometer.
• Thermo Scientific TRACE 1310 GC system with TG-5SilMS column (30 m×0.25 mm×0.25 µm, 10 m guard).
• TriPlus RSH autosampler; EI at 70 eV and PCI with methane reagent gas.

Data Acquisition and Processing:

• Full-scan mode (50–700 Da) at 120,000 resolving power (FWHM at m/z 200).
• TraceFinder for automated deconvolution, accurate mass library matching (NIST 2014) and HR filtering.
• MassFrontier for theoretical fragmentation and structural elucidation.

Main Results and Discussion

• 961 deconvoluted features were detected above a 100:1 signal-to-noise threshold.
• Six intense unknown peaks were prioritized at retention times 30.6–53.2 min.
• PCI spectra revealed molecular adducts [M+H]+, [M+C2H5]+ and [M+C3H5]+, enabling sub-1 ppm mass accuracy assignments of elemental formulas.
• High-resolution MS/MS of [M+H]+ ions yielded diagnostic fragments and supported proposed structures for each unknown.
• One compound was identified as 2-hydroxy-5-methyl-1,3-benzenedicarboxaldehyde (99.2 % spectrum match with HR filtering).
• Three isomeric forms of C26H28O8 were resolved, each exhibiting distinct MS/MS patterns, illustrating the power of accurate-mass fragmentation in distinguishing structural isomers.

Benefits and Practical Applications

• The high resolving power and mass accuracy of Orbitrap GC-MS significantly reduce false positives in library searches.
• PCI facilitates unambiguous molecular ion identification for compounds lacking library spectra.
• Automated deconvolution accelerates peak extraction in complex matrices.
• MS/MS accurate-mass data deliver structural insights, improving confidence in NIAS identification for regulatory and safety assessments.

Future Trends and Potential Applications

• Integration of in-house high-resolution spectral libraries for broader compound coverage.
• Application of hybrid GC-Orbitrap workflows to other food contact materials, plastics and recycled polymers.
• Advanced data-mining algorithms and machine learning to predict NIAS toxicity based on structural features.
• Coupling with complementary techniques (e.g., LC-Orbitrap MS) for profiling non-volatile migrants.

Conclusion

The combination of full-scan high-resolution GC-Orbitrap MS, EI/PCI acquisition and automated deconvolution provides a robust, rapid and confident workflow for characterizing unknown compounds in food packaging. The approach streamlines structural elucidation, enhances detection of trace migrants and supports risk assessment efforts.

References

1. Katan LL, editor. Migration from Food Contact Materials. Blackie Academic and Professional; 1996.
2. Barnes KA, Sinclair CR, Watson DH. Chemical Migration and Food Contact Materials. Woodhead Publishing; 2006.
3. Thermo Fisher Scientific. AN10492: Chemical profiling and differential analysis of whiskies using Orbitrap GC-MS. Runcorn, UK; 2015.