Chemometric Profiling of Whiskey Using the 5977A GC/MSD

Significance of the Topic

Gas chromatography–mass spectrometry (GC/MS) coupled with chemometric analysis plays a pivotal role in food and beverage quality control by providing an objective, sensitive, and reproducible method to profile volatile and semi-volatile compounds. In the context of whiskey production and authentication, such analytical approaches complement human sensory evaluation and help differentiate closely related brands, detect contamination, and ensure product consistency over time.

Objectives and Study Overview

This application note describes a non-targeted chemometric approach using the Agilent 5977A GC/MSD with Extractor EI Source and the Agilent 7890B GC, combined with automated headspace solid phase micro-extraction (SPME) and advanced statistical tools, to:

• Compare two tuning protocols (Etune vs Atune) for sensitivity in trace compound detection
• Generate comprehensive compound profiles of five commercially available whiskeys
• Apply statistical analyses (ANOVA, PCA, HCA) to classify and differentiate the whiskey brands based on their volatile fingerprints

Methodology and Instrumentation

Sample Preparation and Extraction

• Five whiskey samples (one popular brand and four competitors) were analyzed in triplicate.
• Headspace SPME used a 50/30 µm DVB/CAR/PDMS fiber in 10 mL vials containing 5 mL of whiskey, incubated at 60 °C with agitation for 10 min.
• The fiber was thermally desorbed at 240 °C for 1 min in split mode (50:1).

GC/MS Conditions

• Instrument: Agilent 7890B GC coupled to Agilent 5977A GC/MSD with Extractor EI Source.
• Column: HP INNOWAX (25 m × 0.20 mm, 0.40 µm).
• Oven program: 40 °C (1.5 min), ramp to 240 °C at 30 °C/min, hold 3 min; total runtime 16 min.
• MS: EI at 70 eV, scan range 50–550 amu, transfer line at 255 °C.

Data Processing

• Deconvolution with AMDIS (ChemStation) generated .ELU files.
• Compound extraction and filtering in Agilent Mass Profiler Professional (MPP) using abundance and CV thresholds.
• Statistical tools: one-way ANOVA (p < 0.05), principal component analysis (PCA), hierarchical cluster analysis (HCA).
• Identification via NIST 11 MS Library and Agilent MassHunter ID Browser.

Major Results and Discussion

Comparison of tuning protocols showed that the Etune algorithm enhanced sensitivity for trace-level compounds, yielding 48 entities with ≥2-fold higher intensity than Atune; four of these were undetectable with Atune. Overall profiling identified 142 entities, of which 74 passed noise and abundance filters. High-abundance compounds (20 entities) subjected to ANOVA (p < 0.05) revealed 15 significant markers. PCA differentiated the five whiskeys into four groups: the popular brand with Competitor A, Competitor B, Competitor C, and Competitor D, based on characteristic ester and fatty acid profiles. Low and medium intensity compounds (54 entities) were similarly classified by HCA into eight clusters, highlighting unique markers in each sample group and confirming Etune’s superior detection of key esters such as pentadecanoic acid ethyl ester.

Benefits and Practical Applications

• Objective differentiation of whiskey brands beyond sensory panels.
• Detection of adulteration or contamination in distilled spirits.
• Quality assurance during production, storage, and aging.
• Framework applicable to other food and beverage matrices.

Future Trends and Potentials

Advances in GC/MS instrumentation (high-resolution and tandem MS), automation of sample handling, and integration with machine learning will further enhance non-targeted profiling. The development of robust predictive models could enable real-time quality control, origin authentication, and shelf-life prediction. Expanding compound libraries and multivariate analytics will improve the sensitivity and specificity of flavor and aroma fingerprinting in complex matrices.

Conclusion

The combination of the Agilent 5977A GC/MSD, automated headspace SPME, and chemometric software delivers a powerful platform for non-targeted profiling of whiskey aromas. The Etune protocol enhances sensitivity for low-level compounds, and multivariate analysis (ANOVA, PCA, HCA) effectively classifies and differentiates whiskey brands based on their volatile chemical signatures.

References

• Baumann S., Aronova S., “Olive Oil Characterization using Agilent GC/Q-TOF MS and Mass Profiler Professional Software,” Agilent Technologies Application Note 5991-0106EN.
• Vaclavík L., Lacina O., Hajšlová J., Zweigenbaum J., “The use of high performance liquid chromatography-quadrupole time-of-flight mass spectrometry coupled to advanced data mining and chemometric tools for discrimination and classification of red wines according to their variety,” Analytica Chimica Acta, 685, 45–51 (2011).
• Serino T., “Detecting Contamination in Shochu Using the Agilent GC/MSD, Mass Profiler Professional, and Sample Class Prediction Models,” Agilent Technologies Application Note 5991-0975EN.