DENTIFYING NON-INTENTIONALLY ADDED SUBSTANCES (NIAS) IN FOOD CONTACT MATERIALS

Significance of the Topic

Non-intentionally added substances in food contact materials pose potential health risks and regulatory challenges. Effective screening and identification of these unknown compounds are essential for ensuring consumer safety and meeting quality control requirements in food packaging.

Objectives and Study Overview

This study aimed to evaluate the capabilities of atmospheric pressure gas chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry (APGC-QTof) and the UNIFI scientific information system for the detection and structural elucidation of unknown NIAS in starch-based biopolymer packaging.

Methodology and Instrumentation

Sample Preparation

• Extraction of biopolymer pellets with methanol using ultrasonic bath at 40 °C
• Concentration of combined extracts under nitrogen to 1 mL

GC-EI-MS Conditions

• System: Agilent 7890A GC with 5975B quadrupole MS (70 eV electron ionization)
• Column: DB-5MS (30 m × 0.25 mm × 0.25 μm)
• Injection: 1 μL pulsed splitless
• Oven program: 50 °C to 300 °C at 10 °C/min

APGC-QTof Conditions

• System: Waters Xevo G2-XS QTof with APGC source
• Ionization: soft APGC producing radical cations and protonated molecules
• MSE acquisition: low and high collision energy for simultaneous precursor and fragment data
• Source and cone settings optimized for sensitivity

Data Processing

• UNIFI Scientific Information System v1.8.2 for componentization, library search, mass accuracy filtering, and structural proposals

Main Results and Discussion

Enhanced Detection

• APGC-QTof revealed a greater number of chromatographic peaks compared to EI-MS due to higher sensitivity and softer ionization

Structural Elucidation Examples

• At 16.3 min, EI matched a lactone with library match factor 917; APGC molecular ion at m/z 201.1120 enabled assignment to a protonated cyclic ester
• At 17.2 min, low EI match led to tentative assignment; APGC fragment at m/z 232.1817 suggested a different sugar derivative
• At 27.3 min, APGC detected traces of beta-tocotrienol, not observed by EI

Correction of Tentative Identifications

• Accurate mass and isotopic pattern filtering reduced false positives from initial ChemSpider hits
• Fragmentation pathways proposed using mass accuracy and organic chemistry rules

Benefits and Practical Applications

• Soft ionization by APGC preserves molecular ions, facilitating elemental formula determination
• High-resolution MSE data streamline compound identification and reduce manual interpretation
• Complementarity of APGC-QTof and EI-MS ensures broader coverage of volatile and semi-volatile NIAS
• UNIFI workflow automates componentization, library searches, and structural proposals, improving throughput

Future Trends and Applications

Integration of APGC-QTof with advanced data analytics and machine learning is expected to expand the NIAS screening scope. Development of comprehensive spectral libraries for soft ionization techniques and real-time monitoring workflows will support more efficient risk assessment in packaging materials.

Conclusion

The combination of APGC-QTof and UNIFI provides a powerful approach for identifying non-intentionally added substances in food contact materials. This strategy enhances detection sensitivity, improves structural elucidation confidence, and complements traditional EI-MS methods, ultimately supporting safer packaging practices.