Fast Ingredient Analysis of Edible Oils Using a Portable Raman Spectrometer

Importance of the Topic

Edible oils are central to nutrition and the food industry owing to their fatty acid profiles. The rising demand for vegetable oils rich in mono- and polyunsaturated acids drives the need for fast, reliable analytical methods. Conventional approaches like GC-MS are accurate but slow and laboratory-bound, creating bottlenecks in at-line quality control and process monitoring.

Objectives and Study Overview

The application note details the rapid quantification of key constituents in five edible oils—olive, camellia, peanut, sunflower, and canola—using a portable Raman spectrometer paired with chemometric analysis. The primary aim was to demonstrate that at-line testing of fatty acid content can be achieved in seconds without sample preparation, and that portable Raman technology can track lipid oxidation processes during storage or processing.

Methodology and Experimental Design

A total of 150 oil samples (30 per type) were analyzed. Reference concentrations of oleic, linoleic, mono- and polyunsaturated, and saturated fatty acids were obtained by GC-MS. Raman spectra were collected over 175–2600 cm⁻¹ with 9 s integration. Spectral preprocessing included background removal and Savitzky-Golay smoothing to enhance signal-to-noise ratio. Partial least squares (PLS) regression models were built in dedicated chemometric software using key spectral regions corresponding to saturation, unsaturation, and backbone vibrations.

Instrumentation Used

• Portable i-Raman® spectrometer with 785 nm laser excitation and CleanLaze® stabilization
• Raman shift range: 175–2600 cm⁻¹; spectral resolution ≤3 cm⁻¹
• TE-cooled 2048-pixel CCD detector; fiber-optic interface allowing measurements to 65 cm⁻¹ from the Rayleigh line
• Liquid sample holder (BCR100A) with 10 mm optical path

Results and Discussion

The PLS models yielded strong performance: correlation coefficients ranged from 0.84 (saturated fatty acids) to 0.98 (polyunsaturated fatty acids), with RMSEP values between 0.15 and 0.24. Key findings include:

• High accuracy for oleic (R=0.95, RMSEP=0.24) and linoleic acids (R=0.97, RMSEP=0.17)
• Superior prediction of polyunsaturated fatty acids (R=0.98, RMSEP=0.15)
• Identification and removal of outliers improved the saturated fatty acid model

This confirms that portable Raman spectroscopy combined with chemometrics can match GC-MS precision while reducing analysis time and eliminating sample preparation.

Benefits and Practical Applications

• Rapid, non-destructive quantification of oil constituents directly in vials
• Field-portable solution for at-line quality control in food processing
• Capability to monitor lipid oxidation and compositional changes during storage
• Reduced operational costs and increased throughput compared to laboratory methods

Future Trends and Possible Applications

The approach may be extended to tailor models for individual fatty acids for even higher accuracy. Integration with automated sampling systems and expansion to other food matrices or lipid-based products represents a promising avenue. Advances in portable spectroscopy and real-time data analytics will further enhance process control and traceability in the food industry.

Conclusion

This study demonstrates that portable Raman spectroscopy with multivariate analysis can rapidly and accurately quantify fatty acid profiles in edible oils. The method offers a practical alternative to GC-MS for at-line testing, supporting efficient quality control and deeper insight into lipid chemistry in industrial settings.

References

• Bernuy B., Meuren M., et al. Determination by Fourier Transform Raman Spectroscopy of Conjugated Linoleic Acid in I2-Photoisomerized Soybean Oil. J. Agric. Food Chem., 2009, 57(15):6524–6527.
• Muik B., Lendl B., Molina-Diaz A. Direct monitoring of lipid oxidation in edible oils by Fourier transform Raman spectroscopy. Chem. Phys. Lipids, 2005(2).
• B&W Tek. BWIQ Raman quantitative software, 2012. Available from www.bwtek.com/products/bwiq/.