Method Development and Identification of Triacylglycerols Species with Supercritical Fluid Chromatography and Method Scouting Software

Importance of the topic

Triacylglycerols (TAGs) are the main components of natural oils and fats and play a critical role in determining nutritional quality, functionality, and process performance in food, pharmaceutical and cosmetic industries. Conventional methods such as GC and normal phase HPLC face challenges due to the large number of isomeric TAG species. Supercritical Fluid Chromatography (SFC) offers rapid separations with high resolution at elevated linear velocities, making it an attractive alternative for detailed lipid profiling.

Aims and study overview

This study aimed to develop and optimize an SFC–MS/MS method for comprehensive identification and quantitation of TAG species. A method scouting software was employed to systematically explore critical parameters (modifier concentration, back pressure, and column temperature) to achieve optimal separation in complex oil matrices, demonstrated here on palm oil samples.

Methodology and Instrumentation

• Chromatography: Nexera UC SFC system with Shim-pack XR-ODSIII column (150×2.0 mm I.D., 2.2 μm); supercritical CO₂ mobile phase with acetonitrile modifier (10–20%); back pressure 10–20 MPa; column oven temperature 25–35 °C; flow rate 0.8 mL/min.
• Mass spectrometry: LCMS-8050 triple quadrupole; ammonium adduct [M+NH₄]+ precursor; multiple reaction monitoring via neutral loss scans; DUIS interface; positive ion mode; make-up solvent methanol with 10 mmol/L ammonium acetate at 0.2 mL/min.
• Software: Method Scouting Solution for automated generation and comparison of 27 analytical methods.

Main results and discussion

Systematic evaluation of 27 SFC conditions identified optimal settings (10 MPa back pressure, 10% acetonitrile, 25 °C) yielding the best resolution and shortest analysis time. Under these conditions, 28 distinct TAG species were resolved and characterized in palm oil by MS/MS (e.g., TAG 16:0/16:0/18:1, TAG 16:0/16:0/16:0, TAG 16:0/16:0/18:2). Quantitative profiling revealed TAG 16:0/16:0/18:1 as the most abundant component (approximately 36%), followed by TAG 16:0/16:0/18:2 (about 9.5%) and TAG 16:0/16:0/16:0 (about 6.7%).

Benefits and practical applications

• Significantly shorter run times compared to normal phase HPLC while maintaining high resolution.
• Automated method scouting accelerates parameter optimization, reducing development time.
• Robust profiling of TAG species supports quality control, nutritional analysis, and product development in edible oil and lipid-based formulations.

Future trends and applications

Integration of SFC–MS/MS with advanced data analysis approaches such as chemometrics and machine learning will enable deeper lipidome coverage and real-time monitoring. Expansion to other lipid classes and complex biological matrices is anticipated. The adoption of automated method optimization platforms will further streamline high-throughput quality control in industrial settings.

Conclusion

An optimized SFC–MS/MS workflow combined with method scouting software effectively separates and identifies diverse TAG species in palm oil. This approach delivers rapid, high-resolution lipid profiling, offering a powerful tool for research and industrial quality assurance.

References

No references were provided in the original document.