Differential Analysis of Perfumes with GC-TOFMS

Significance of Topic

Detailed chemical profiling of perfumes is essential for maintaining quality control, guiding product development and performing competitive analysis. Non-targeted analytical strategies reveal both known and previously undetected compounds, offering a comprehensive understanding of complex fragrance formulations.

Objectives and Study Overview

This work demonstrates a differential analysis comparing a reference brand perfume with two imitation products using GC-TOFMS and advanced deconvolution software. The goals were to identify declared ingredients, discover unexpected analytes, and highlight formulation differences.

Used Instrumentation

• Gas Chromatograph: Agilent 7890 with MPS2 autosampler
• Injection: 1 µL splitless at 250 °C
• Column: Rxi-5ms (30 m × 0.25 mm × 0.25 µm)
• Carrier Gas: Helium at 1.0 mL/min
• Oven Program: 2 min at 40 °C, ramp 5 °C/min to 280 °C, hold 10 min
• Transfer Line: 250 °C
• Mass Spectrometer: LECO Pegasus HT TOFMS
• Ion Source: 250 °C, mass range 33–500 m/z, acquisition rate 20 spectra/s
• Data Processing: ChromaTOF software with True Signal Deconvolution and NIST library matching

Methodology

Three commercial perfumes (brand and two imitations) were diluted 50:1 in ethanol. After splitless injection, chromatographic separation was achieved on a non-polar column with a temperature gradient. Full-spectrum TOFMS data were collected at high speed and processed using automated peak finding (S/N >50), spectral deconvolution, and library matching (similarity score >700).

Main Results and Discussion

Non-targeted profiling of the brand sample yielded ~200 peaks, 119 of which were tentatively identified by NIST. Key findings included:

• Benzyl acetate, a floral odorant not listed on packaging, was present at high levels in all samples.
• Diethyl phthalate appeared exclusively in both imitation products, suggesting packaging leachables or diluents with toxicological relevance.
• True Signal Deconvolution resolved a coelution into α-santalol (woody aroma) and kharismal (floral aroma), both enriched in the brand sample.
• Distinct musk compounds: natural muscone in the brand; synthetic musk ketone in imitation A; ethylene brassylate in imitation B.

These observations underscore the value of non-targeted TOFMS for detecting undeclared or regulatory-relevant compounds and for detailed sensory profiling.

Benefits and Practical Applications

Employing full-scan TOFMS with advanced deconvolution extends beyond targeted assays by revealing hidden or unexpected constituents. This approach enhances product authentication, quality assurance, formulation optimization and competitive benchmarking in the fragrance industry.

Future Trends and Applications

Integration of high-resolution TOFMS data with chemometric and machine learning workflows will streamline classification, adulteration detection and predictive quality control. Portable and miniaturized MS systems may enable rapid on-site fragrance authentication and real-time process monitoring.

Conclusion

The LECO Pegasus HT GC-TOFMS platform, combined with True Signal Deconvolution, effectively differentiates complex perfume formulations. This non-targeted workflow identifies both declared and unexpected analytes, supporting advanced quality control, product development and competitive analysis.