Identification and checking of fatty acids in functional foods and cosmetics

Significance of the Topic

Fatty acids are essential ingredients in functional foods and cosmetics, offering nutritional and dermatological benefits. Ensuring their identity and purity during manufacturing is critical to maintain product quality, comply with regulations, and avoid costly production delays.

Objectives and Study Overview

This study demonstrates the use of a handheld Raman spectrometer for the rapid identification and verification of common fatty acids and fatty alcohols. The main goals are to compare conventional library matching against a chemometric verification approach and to establish a reliable workflow for quality control in nutraceutical and cosmetic production.

Methodology and Instrumentation

The analysis employs the Metrohm Instant Raman Analyzer Mira M-3 with the following configuration:

• Laser power: 5
• Average scans: 1
• Auto integration time
• Orbital-Raster-Scan (ORS) technology
• FDA 21 CFR Part 11 compliance

The workflow consists of two main steps:

1. Library Matching: Acquiring spectra of lauric, myristic, palmitic, stearic acids and stearyl alcohol, building a spectral library, and identifying unknowns via Pearson correlation.
2. Verification via Chemometrics: Collecting ~20 spectra per compound, creating training sets, applying Principal Component Analysis to compute p-values, and classifying samples as “Pass” or “Fail” at a 95% confidence threshold.

Main Results and Discussion

Library matching yielded high hit quality indices but struggled to differentiate closely related fatty acids, with correlation values often differing by only 0.01–0.03. In contrast, the chemometric verification approach consistently accepted the correct compound and rejected similar ones. For example, palmitic acid true positives were confirmed with a 33.1% likelihood within the 95% confidence interval, while non-matching samples were clearly excluded.

Benefits and Practical Applications

The chemometric verification method offers:

• Clear pass/fail outcomes that reduce interpretive ambiguity.
• Enhanced detection of subtle spectral differences among similar compounds.
• Rapid, non-destructive analysis suitable for in-line or at-line quality control.

These advantages support manufacturers in verifying raw materials, ensuring compliance with internal specifications and regulatory standards, and minimizing production disruptions.

Future Trends and Opportunities

Advancements may include:

• Expanded spectral libraries covering a broader range of nutraceutical and cosmetic ingredients.
• Integration of real-time data transmission and cloud-based analytics.
• Improved chemometric algorithms leveraging machine learning for even greater discrimination power.
• Automated process monitoring to enable continuous quality assurance in production lines.

Conclusion

Handheld Raman spectroscopy combined with chemometric verification provides a robust solution for authenticating fatty acids in functional foods and cosmetics. While traditional library matching is useful for distinct materials, the p-value based approach delivers higher confidence when analyzing closely related compounds, supporting reliable quality control and regulatory compliance.