A Real-Time Lipidomics Approach for Detecting Fish Fraud Using Rapid Evaporative Ionization Mass Spectrometry and LiveID Software

Importance of the Topic

Seafood mislabeling and adulteration represent a significant global challenge with up to 30% of fish products affected and annual losses approaching $120 billion.
Rapid, reliable species identification at the point of control is essential to combat fraud, protect consumers, and maintain supply chain integrity.

Objectives and Study Overview

This study demonstrates a real-time lipidomic approach combining Rapid Evaporative Ionization Mass Spectrometry (REIMS) and LiveID software to discriminate five visually and genetically similar white fish species—cod, coley, haddock, pollock, and whiting—without sample preparation or chromatography.

Methodology and Sample Preparation

Fish samples were stored at –80 °C and thawed before analysis. Tissue was sampled directly using an electrosurgical iKnife at 30 W in Autocut mode, generating an aerosol that was transferred to a Xevo G2-XS QTof mass spectrometer. Spectra (m/z 200–1200) were acquired in continuum mode (~0.5 s per scan). Chemometric modeling in LiveID applied lock mass correction, background subtraction, binning, normalization, and PCA‐LDA for classification.

Instrumentation

• iKnife monopolar electrosurgical sampling device with Erbe VIO 50 C generator
• Waters Xevo G2-XS QTof mass spectrometer with REIMS source
• MassLynx software for data acquisition
• LiveID software for real-time model building and recognition
• Progenesis QI, EZInfo, and SIMCA-P for biomarker discovery

Main Results and Discussion

The PCA/LDA model built on 478 fish samples (8–12 replicates each) achieved 99.9% correct classification in leave-20 %-out cross validation, with negligible outliers. A blind validation set confirmed 98.9% accuracy. Inter-laboratory testing on 68 samples returned 95.6% accuracy. Non‐model species (seabass, seabream) were correctly flagged as outliers in 92.8% of cases. Critical lipid biomarkers (e.g., phosphatidylethanolamines, phosphatidylinositols, sphingomyelins, free fatty acids) contributed to species separation.

Benefits and Practical Applications

• Real-time species identification in 2–3 seconds without sample cleanup
• Minimal operator expertise required for LiveID software
• Applicability to point-of-control testing along the supply chain
• Potential to extend analysis to origin, capture method, and product integrity

Future Trends and Opportunities

Integration of REIMS with advanced chemometrics and omics data could expand its utility for multi‐factor authentication (geographic origin, farming versus wild, processing methods) and real-time monitoring of diverse food products. Development of portable REIMS systems and cloud-based model sharing may further enhance on-site fraud detection and regulatory compliance.

Conclusion

The REIMS–LiveID platform delivers rapid, preparation-free, species-level authentication of fish with high accuracy and robustness across laboratories, offering a practical solution to combat seafood fraud and strengthen quality control.

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