UHPLC/MS Profiling of Nonvolatiles in Whiskeys Using the Agilent 6530 Accurate-Mass Q-TOF LC/MS and Mass Profiler Professional

Significance of the Topic

Profiling the nonvolatile composition of whiskey is critical for ensuring product authenticity, protecting against fraud, and optimizing production processes. Accurate chemical fingerprints support quality control, regulatory compliance, and brand integrity in the high-value American whiskey industry.

Objectives and Study Overview

This study employed a non-targeted UHPLC/Q-TOF LC/MS workflow combined with multivariate analysis to profile 63 commercial American whiskeys (bourbon, rye, Tennessee, and other types). The goals were to identify compound sets that discriminate whiskey types, distinguish products from different bourbon producers, and assess the impact of barrel aging on chemical composition.

Methodology and Instrumentation

Whiskey samples were analyzed neat at bottling proof, in triplicate and randomized. A Molecular Feature Extractor algorithm detected features in the LC/MS data. Mass Profiler Professional aligned masses and retention times, and principal component analysis (PCA) visualized grouping patterns. Compound identification used MS/MS spectra matched against the Agilent Metlin Personal Compound Database and Library and literature references.

Used Instrumentation

• Agilent 1290 Infinity UHPLC System with ZORBAX Eclipse Plus RRHD C18 column (5 cm × 2.1 mm, 1.8 µm) at 60 °C, 0.6 mL/min flow, 12-minute gradient.
• Agilent 6530 Q-TOF LC/MS in negative electrospray mode, mass range m/z 75–1 500, acquisition at 3 spectra/sec, with automated MS/MS at 20 eV.
• Agilent MassHunter Qualitative Analysis Software v6.00 and Mass Profiler Professional v12.6.1.

Main Results and Discussion

• Initial profiling detected ~7 600 features, reduced to 3 100 after replicate filtering and to 266 by presence across whiskey types. A final ANOVA filter (p < 0.05) yielded 40 discriminating compounds.
• PCA differentiated bourbon, rye, and Tennessee whiskeys; Tennessee samples largely separated from bourbon and rye. Smaller rye producers showed stronger separation from bourbons.
• Among six major bourbon producers, Producer 4 samples formed a distinct cluster in PCA, indicating unique compound profiles.
• Aging differentiation used 33 samples grouped by barrel age (< 4 years, 4–8 years, > 8 years). Young whiskeys were separated from older ones, though intermediate and oldest groups overlapped partially.
• Key markers for young whiskeys included C8–C12 fatty acids and phenolic aldehydes; longer-aged whiskeys showed C18–C20 fatty acids, syringaldehyde, ellagic acid, and vanillin.

Benefits and Practical Applications

This non-targeted UHPLC/Q-TOF approach enables rapid (< 12 min) chemical profiling without sample preparation. Identified marker compounds support:

• Authentication and fraud prevention.
• Quality control and batch consistency monitoring.
• Process optimization by tracking chemical changes during aging.

Future Trends and Potential Applications

• Expansion of high-resolution spectral libraries for broader metabolite coverage.
• Development of targeted assays for routine monitoring of marker compounds.
• Application to other distilled spirits and fermented beverages.
• Integration with sensory data and chemometric modeling for flavor prediction.

Conclusion

The combined UHPLC/Q-TOF and multivariate analysis workflow provides an effective, high-throughput tool for detailed whiskey profiling. It discriminates product types, producer signatures, and aging effects, offering a robust platform for authenticity verification and quality assurance in the whiskey industry.

References

• 1. Collins TS, Zweigenbaum J, Ebeler SE. Profiling of nonvolatiles in whiskeys using UHPLC-QTOF MS. Food Chemistry. 2014;163:186–196.
• 2. MacNamara K, Dabrowska D, Baden M, Helle N. Advances in the ageing chemistry of distilled spirits distilled in oak barrels. LC/GC. 2011;14:6–22.