Integrated Chiral Volatile Organic Compound, Gas Chromatography Mass Spectrometry, and Isotope Ratio Analyses with...

Area of Science:

• Analytical Chemistry
• Food Science
• Organic Chemistry

Background:

• Natural flavorings are prone to adulteration, necessitating robust authentication methods.
• Chiral volatile organic compounds (VOCs) and their enantiomeric ratios (ERs) are key biosynthetically derived authenticity markers.
• Stereochemical specificity is crucial for capturing the molecular complexity of natural flavors.

Purpose of the Study:

• To review and evaluate the combined application of chiral VOC analysis and compound-specific isotope ratio measurements for flavor authentication.
• To highlight advances in enantioselective gas chromatography-mass spectrometry (GC-MS) and multidimensional GC techniques.
• To assess chemometric pipelines, including machine learning (ML), for classification accuracy and interpretability in flavor authentication.

Main Methods:

• Enantioselective gas chromatography-mass spectrometry (GC-MS) workflows, including comprehensive two-dimensional GC (GC×GC) and heart-cut multidimensional GC (MDGC).
• Compound-specific isotope ratio measurements using isotope ratio mass spectrometry (IRMS).
• Chemometric pipelines incorporating machine learning (ML) for data analysis and classification.

Main Results:

• Enantiomeric ratios (ERs) serve as reliable markers for flavor authenticity.
• Integrated analytical workflows combining GC×GC/MDGC, interpretable ML, and IRMS enhance authentication accuracy.
• Standardized pretreatment, verified enantioselective separation, and uncertainty-aware ER reporting are critical for reproducibility.

Conclusions:

• Modular analytical pipelines integrating advanced GC techniques, interpretable ML, and IRMS offer a viable path for industrial flavor authentication.
• An integrated VOC/ER-centered framework combining chiral GC-MS, GC-combustion/pyrolysis-IRMS, and interpretable ML is proposed.
• Emphasis on ER fidelity and transparent, traceable outputs aligned with labeling regulations is crucial for implementation.