Identification Grading System™ (IGS™)

Importance of the Topic

Non-targeted screening of complex mixtures demands reliable and efficient compound identification. The Identification Grading System (IGS) enhances confidence in unknown analyses by integrating multiple chemical criteria into a single grade, facilitating rapid decision-making and reducing manual review effort.

Objectives and Study Overview

This work introduces LECO’s IGS module within ChromaTOF software, developed during the EPA’s ENTACT collaborative trial. Key objectives include:

• Defining a four-criterion grading scheme for compound identification
• Applying the IGS filter to GCxGC-TOFMS datasets
• Simplifying data review to prioritize the most confident hits

Methodology and Instrumentation

The workflow couples comprehensive two-dimensional gas chromatography (GCxGC) with high-resolution time-of-flight mass spectrometry (TOF-MS) on the Pegasus GC-HRT 4D platform. IGS evaluates each deconvolution result using:

1. Accurate mass detection of molecular ions
2. Library-based spectral similarity scoring
3. Accurate mass matching of fragment ions
4. Retention index agreement with reference data

Instrumental setup:

• Pegasus GC-HRT 4D GCxGC-TOFMS system
• ChromaTOF software with integrated IGS module
• Curated and user-generated spectral libraries

Main Results and Discussion

In an EPA ENTACT blind sample, initial deconvolution yielded approximately 4,800 features. Applying an IGS score threshold >2 reduced this to ~245 high-confidence identifications. The system correctly identified around 80 % of known spiked compounds, demonstrating:

• Enhanced separation of coeluting species via GCxGC
• Unskewed, high-quality spectra across narrow chromatographic peaks using high-resolution TOF-MS
• Efficient prioritization of true positives for follow-up

Benefits and Practical Applications

IGS streamlines non-targeted analysis by providing automated confidence grading, which is valuable for:

• Environmental monitoring and pollutant screening
• Quality assurance in pharmaceuticals and food safety
• Forensic chemistry and metabolic profiling

Future Trends and Potential Applications

Emerging developments may include:

• Machine learning integration for enhanced spectral matching
• Extension to additional chromatographic and mass spectrometric techniques
• Real-time IGS scoring in online analytical workflows
• Expanded, annotated libraries covering broader chemical spaces

Conclusion

The Identification Grading System offers a unified, multi-metric approach to boost confidence and efficiency in non-targeted GCxGC-TOFMS analyses, significantly reducing review time and improving reliability of compound identification.

References

• DOI: 10.1007/s00216-018-1435-6
• DOI: 10.1021/es5002105