Determination of the fatty acid composition in refined oils and fats by alkaline transesterification

Determination of Fatty Acid Composition in Refined Oils and Fats by Alkaline Transesterification Using FAME Workstation

Importance of the Topic

Accurate profiling of fatty acid composition in edible oils and fats is critical for nutritional labeling, quality control and compliance with regulatory requirements such as EU food information regulation. Identification of cis and trans isomers informs health warnings and purity assessment. Automated high-throughput approaches reduce human error, improve reproducibility and enhance laboratory productivity in food, pharmaceutical and industrial analytics.

Objectives and Overview of the Study

This application note describes the automation of two alkaline transesterification protocols from AOCS Ce 2-66 methods 3 and 4 using a fully integrated FAME Workstation. The goals were to minimize sample handling, eliminate carryover, decrease reagent consumption, and match or exceed performance of manual procedures while enabling continuous 24 h operation.

Methodology and Instrumentation

Sample preparation is based on splitting triglycerides and converting free fatty acids into fatty acid methyl esters. Two workflows were automated:

• Method 3: Alkaline esterification with 0.5 M methanolic NaOH, methylation with methanolic BF3, heating, n-heptane extraction, saline wash and sodium sulfate drying.
• Method 4: Base-catalyzed transesterification with 2 M methanolic KOH, heptane dissolution, water wash, sodium sulfate drying and direct dilution.

Instrumentation:

• Agilent 7890 GC with FID, S/SL injector, BPX-70 60 m column
• CTC Analytics PAL RTC 120 cm autosampler with agitator, vortex mixer, wash station, solvent module and racks
• Automation software CHRONOS with scheduling, interlacing and Clarity for chromatography evaluation

Main Results and Discussion

Chromatographic conditions (injector 250 °C, split 1:30, gradient from 70 °C to 220 °C at 5 °C/min) yielded baseline separation of C14:0 to C24:1 methyl esters. A standard of 11 FAME analytes and a 37-component standard demonstrated robust peak resolution. Automated analysis of olive oil and industrial food-grade oil samples matched literature and manufacturer data within expected variability (± 20 %). Continuous interlaced sequences allowed processing of up to 40 samples in 24 h without manual intervention.

Benefits and Practical Applications of the Method

• Fully automated sample preparation reduces operator exposure to corrosive reagents and risk of carryover.
• Minimal reagent volumes and waste generation lower operational costs.
• High throughput enables routine QC of multiple batches in food, feed and lubricants.
• Modular autosampler configuration can adapt to other derivatization or extraction workflows.

Future Trends and Possibilities for Use

Integration of centrifugation modules could further accelerate phase separations and raise throughput to 70 samples per day. Expansion of the platform to include in-line derivatization, on-column concentration or coupling with mass spectrometry would extend applicability to trace level profiling, lipidomics and advanced isomer discrimination.

Conclusion

The CHRONOS-driven FAME Workstation achieves reliable, carryover-free determination of fatty acid profiles in oils and fats. By fully automating both sample derivatization and GC-FID analysis, the system supports continuous high-yield operation with performance comparable to manual methods.

Reference

Data based on International Olive Council Trade Standard for Olive Oil and Olive Pomace Oil, 1998