Automated Analysis and Quantitation of Fish Oil Supplements using the MIDI Sherlock™ Marine Oil Analysis Package

Importance of the topic

The accurate analysis of Omega-3 fatty acids in marine oil supplements is critical for product quality, regulatory compliance, and consumer health. Omega-3s such as EPA and DHA are linked to cardiovascular benefits and are quantified for labeling, nutritional studies, and biomarkers like the HS-Omega-3 Index®. Traditional manual methods vary widely between laboratories and are prone to error, leading to inconsistencies that hinder meaningful comparisons.

Objectives and study overview

This study evaluates the MIDI Sherlock™ Marine Oil Analysis Package to automate fatty acid profiling in fish oil supplements and reduce manual workload. Two supplement types were examined: a natural triglyceride fish oil (NF) and an ethyl ester concentrate (MN). Replicate extractions were performed and analyzed across three different GC instruments to assess precision, accuracy, and throughput improvements.

Methodology and instrumentation

Sample Preparation and Extraction

• Based on AOCS Official Method Ce 1b-89, samples were transesterified using sodium methoxide (NaOCH₃) to avoid hazardous catalysts.
• An internal standard (19:0 phosphocholine) was added at the start to enable reliable quantitation.

Instrumentation and Software

• Shimadzu GC-2010 Plus with AOC-20i/20S autosampler running Shimadzu LabSolutions v.5.85.
• Agilent 6890N and 7890B GCs with 7683 injector and Agilent ChemStation B.04.03.
• MIDI Sherlock Software v.6.3B with the Marine Oil Analysis Package for automated batch control, calibration, compound identification, and quantitation.
• Column: J&W Ultra 2, 25 m × 0.2 mm × 0.33 µm; carrier gas hydrogen; FID at 300 °C; injection 2 µL split 30:1.
• Oven program: 190 °C hold, ramp 10 °C/min to 285 °C (9.5 min), then 60 °C/min to 310 °C (0.42 min).

Main results and discussion

The Sherlock system automatically identified 20–35 fatty acids per sample and quantified EPA, DHA, and other components. In the NF sample, EPA measured ~275 mg/g, DHA ~184 mg/g, and total detected fatty acids ~813 mg/g. Across nine runs (three instruments, triplicate extractions), results stayed within ±10% of the mean. Categorized data confirmed both supplements met or exceeded label claims for EPA, DHA, and total Omega-3. Automated retention time calibration corrected shifts and minimized analyst intervention. Automated compound naming captured minor unsaturated fatty acids that accounted for about 6% of the total profile and 10% of the Omega-3 fraction, which manual reviews often overlook. The NaOCH₃ extraction was robust to ±10 °C variation and matched performance of traditional BF₃/BCl₃ methods without hazardous reagents.

Benefits and practical applications

The automated workflow reduces analysis time and labor, standardizes results across instruments and labs, and minimizes human error in peak naming and calculations. Enhanced detection of minor fatty acids improves profile completeness. The package supports quality control in supplement manufacturing, regulatory testing, and research on nutritional biomarkers.

Future trends and opportunities

Advances may include integration with GC-MS for structural confirmation, machine-learning algorithms for pattern recognition, expansion to additional food and biological matrices, and high-throughput screening capabilities. Connectivity to cloud platforms and regulatory data systems will further streamline compliance and large-scale studies.

Conclusion

The MIDI Sherlock Marine Oil Analysis Package delivers a fully automated, accurate, and reproducible method for marine oil fatty acid profiling. It minimizes manual steps, ensures consistency across laboratories, and meets industry requirements for supplement analysis and research.

References

1. von Schacky C. Omega-3 Index and cardiovascular health. Nutrients. 2014;6:799–814.
2. Harris WS, von Schacky C, Park Y. Standardizing Methods for Assessing Omega-3 Biostatus. In: McNamara RK, editor. The Omega-3 Fatty Acid Deficiency Syndrome. Nova Publishers; 2013. p. 385–398.
3. Sasser M. Identification of bacteria by gas chromatography of cellular fatty acids; Technical Note #101. Microbial ID, Inc.; May 1990.
4. AOCS Official Method Ce 1b-89. Fatty Acid Composition of Marine Oils by GLC. In: Firestone D, editor. AOAC Official Methods and Recommended Practices. 6th ed. AOCS; 2016.