Method development of high throughput lipid analysis in foods by direct analysis in real time mass spectrometer (DART-MS)

Significance of the Topic

Acylglycerols are key contributors to food quality and nutrition. Conventional lipid analyses involve complex preparation steps and lengthy instrument runs that limit throughput. The development of a rapid direct analysis strategy addresses the need for high-throughput profiling of oils and fats in various food matrices.

Objectives and Study Overview

The study aimed to establish a method for direct high-throughput analysis of food lipids using Direct Analysis in Real Time Mass Spectrometry (DART-MS). Food samples including soybean milk, margarine, butter, and margarine supplemented with butter were evaluated to detect characteristic acylglycerol patterns and differentiate sample origin.

Methodology and Instrumentation

A Shimadzu LCMS-2020 system equipped with a DART-OS ion source was employed. Samples were adsorbed onto glass sticks and exposed to the DART gas stream for approximately 10 seconds without prior chemical treatment. The mass spectrometer operated in fast polarity switching mode (15 ms) with a scan rate of up to 15000 u/s over a 10–1000 m/z range, enabling sample-to-sample intervals under one minute.

Main Results and Discussion

Positive ion spectra of plant-derived samples (soybean milk, margarine) showed triacylglycerols and diacylglycerols predominantly containing oleic and palmitic acids. Animal-derived samples (milk, butter) exhibited a broader distribution of medium- and long-chain acylglycerols. Margarine with added butter produced a composite spectrum reflecting both plant and animal lipid signatures. In negative mode, a chloride adduct at m/z 215, attributed to monosaccharides, was observed in all samples except soybean milk. Extracted ion chromatograms confirmed varying abundance of this marker across matrices.

Benefits and Practical Applications

This DART-MS approach delivers rapid lipid profiling suitable for food authenticity testing, quality control, and process monitoring. The ability to distinguish plant and animal lipid sources enhances detection of adulteration and supports nutritional labeling verification.

Future Trends and Opportunities

• Integration of chemometric tools for automated classification of lipid profiles
• Extension of direct analysis to minor lipid classes such as phospholipids and sterols
• On-line coupling of DART sources with separation techniques for complex matrices
• Application to a broader range of food products and real‐time process control

Conclusion

DART-MS with high-speed polarity switching and minimal sample preparation enables high-throughput analysis of acylglycerols in foods. The method effectively differentiates plant and animal lipid profiles and offers significant potential for routine food analysis workflows.

References

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