A New Way of Fingerprinting Fats and Oils

How to tell one vegetable oil from another

Plant and vegetable oils form an important component of our diet, and are also of great industrial importance as a feedstock for everything from soaps to biofuels.

The number of people that routinely need to either confirm the identity of fats and oils or measure the composition of fatty acids and sterols is large and spans a vast range of interests; agriculture, the food industry, clinical scientists, food regulators, and consumer product companies all have an important stake in identifying and/or determining the composition of lipids.

Lipids are natural products and as such exhibit variations in composition that reflect changes in the living organisms that they are derived from.  Quality varies and changes in composition can impact the quality of the end products.

Mass spectrometry, which is often of great analytical utility, here has little to offer due to its inability to generate distinctive mass spectra for many fatty acid features that are very significant (iso and anteiso branched fatty acids being a case in point).

The World of lipid analysis is a World that features highly developed selective capillary columns, flame ionisation detectors and the subjective judgement of humans.  However, significant technical advances are possible and what follows is one such development.

Over the years, columns have been developed that do an excellent job of resolving all of fatty acids.  The temperature and flow control of gas chromatographs has also improved.  In lipid analysis, this translates to significantly better accuracy and precision, which in turn greatly increases the power of GC-FID as a fingerprinting tool, especially if coupled with advanced pattern recognition software.

I recently visited MIDI Inc. in Newark, Delaware, USA; a company that has been identifying fatty acids (GC-FAME) for more than 20 years as a means to identify microorganisms and the scientists at MIDI are now turning their expertise in fatty acid and sterol naming to improved ways of identifying fats and oils.

The key parts of MIDI technology are:

1. A simple, rapid chemistry method for creating fatty acid methyl esters (FAMEs) from the lipids.
2. The means to lock down variables in the sample preparation and analysis to achieve outstanding precision, both run to run and over the long term.
3. Sophisticated pattern recognition software that can combine data on the sample fatty acid composition with data from other sources, (sterol profiles for example) to further refine the fingerprinting process (in microbial identification, the software can combine data from an organisms DNA profiles).
4. The ability to compare samples to each other for relatedness or to compare with a custom library set (from external sources) for verification.

Even though MIDI has been selling the Sherlock® Microbial Identification System since 1991, their focus has always been on bacterial identification.  In order to perform accurate bacterial identification, (more than 1,500 species) the Sherlock software names fatty acids to within 1/10,000th of a minute.  This level of precision is unparalleled in GC-FAME analysis.

MIDI doesn’t quite have a final product yet, but they are getting close, so I have invited Craig Kunitsky of MIDI to present this work at our Conferences in June.

MIDI are looking for collaborators on this project, so if it sounds of interest, please come along to one of our events, or call me on +44 (0)1223 279210, and I will put you in touch.