Triglyceride Profile of Cooking Oil Using a Thermo Scientific™ Acclaim™ C30 Column vs an Acclaim C18 Column

Importance of the Topic

Cooking oils are complex mixtures of triglycerides that vary in fatty acid chain length and unsaturation. Accurate profiling of these compounds is essential for quality control, authenticity verification, and nutritional assessment.

Reversed-phase liquid chromatography offers high resolution and detailed lipid fingerprints, making it valuable for both research and industrial applications.

Objectives and Overview

This study compares the separation performance of two stationary phases—Thermo Scientific Acclaim C30 and Acclaim C18 columns—in profiling triglyceride components of peanut oil. The aim is to assess shape selectivity, resolution, and overall analytical efficiency.

Used Instrumentation

• Columns: Acclaim C30 (5 µm, 4.6 × 150 mm) and Acclaim 120 C18 (5 µm, 4.6 × 150 mm)
• Mobile Phase: Gradient of acetonitrile, isopropanol, and 0.1 M ammonium acetate buffer (pH 5.0)
• HPLC Conditions: Flow rate 1.0 mL/min, column temperature 40 °C, injection volume 2 µL
• Detector: Thermo Scientific Dionex Corona ultra Charged Aerosol Detector (gain 100 pA, medium filter, 25 °C nebulizer)
• Sample: Peanut oil at 5 mg/mL in isopropanol

Main Results and Discussion

Separation using the C30 column displayed superior resolution of triglyceride species compared to the C18 column, attributed to the extended alkyl chains and enhanced shape selectivity. The chromatograms revealed well-resolved peaks corresponding to major and minor triglycerides, allowing a detailed compositional fingerprint. The C18 column, while effective, showed co-elution of certain components, limiting its discriminative power.

Benefits and Practical Applications

• Enhanced triglyceride resolution supports more accurate quantification of lipid species
• Detailed fingerprints enable detection of adulteration and assessment of oil authenticity
• Applicable to quality assurance in food, pharmaceutical, and cosmetic industries

Future Trends and Opportunities

Advancements may include coupling high-selectivity columns with mass spectrometry for structural elucidation, development of greener solvent systems, and automation of data analysis using machine learning algorithms. Novel stationary phases could further improve selectivity for complex lipid profiling.

Conclusion

The Acclaim C30 column outperforms the C18 column in triglyceride profiling of cooking oils, offering higher resolution and detailed lipid characterization. Its implementation can significantly enhance quality control protocols in various industries.