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Most test methods and research into the authenticity of edible oils are focussed on differentiating different plant species or on different grades of olive oil.  There has been relatively little focus on different grades of sunflower oil.  Commercial sunflower oil is sold as three different grades with increasing price premium; standard Sunflower Oil (SFO), Medium Oleic Acid (MOSFO) and High Oleic Acid (HOFSO).  HOFSO is more stable to repeated heating/cooling cycles and so is the grade typically required for fast food restaurants.  It is also available as a premium product sold direct to consumers.

In this paper (open access) the researchers used Spatially Offset Raman Spectrocopy (SORS, a portable non-invasive sensor) to build statistical models that could differentiate HOFSO from those that were not HOFSO (i.e. either MOSFO or SFO).  Although the reference samples used to build the model were purchased from commercial outlets rather than being of verified authenticity, the fact that two different unsupervised mathematical plus a number of supervised approaches all led to similar classification models, and that the models were validated with samples independent of the training sets, gave increased confidence in the model.

The authors conclude that the use of  SORS in combination with the developed chemometric models is an effective tool for the HOSFO authentication. The approach is simple and rapid, with instrumental fingerprints from portable analyser in less than 2 min and without requiring sample preparation.  This approach would class as Green Analytical Chemistry.

Image from the paper

Low Field (LF) Nuclear Magnetic Resonance (NMR) spectrometers have been used for routine inline quality control in the processed meat industry for many years.   Recent advancements have made the technology more accessible for other applications.

This proof-of-concept study (open access) demonstrates the potential of LF NMR for rapid oil authentication in an industrial setting. Their approach was based on solvent-free oil analysis using a single scan ¹H NMR measurement on a LF 80 MHz NMR instrument. The analysis identified the allylic signals at δ 2.0 ppm as a potential diagnostic region, effective in detecting adulteration in the oil samples. They limited the integration to this one spectral region in order to make data analysis rapid and easy to use in a food factory.

The authors demonstrated successful detection of adulteration in two types of vegetable oils rich in polyunsaturated fatty acids (PUFA), rapeseed and sunflower oil, at levels ranging from 5 % to 25 %. Specifically, the study found that adulteration in rapeseed oil could be detected at levels as low as 5 % when adulterated with soybean oil, 10 % when adulterated with sesame and cottonseed oils, and 25 % for corn oil and safflower oil. In the case of sunflower oil, cottonseed oil can be identified at 5 % adulteration, while corn, sesame, and safflower oils can be detected at 25 % adulteration.

The authors consider that the approach is fast, user-friendly, and ecological.  LF NMR could be a valuable tool for identifying adulteration in edible oils, with applications in various industries. This method would benefit from further research to validate the allylic region as a diagnostic region of oil adulteration.

Photo by Fulvio Ciccolo on Unsplash

DNA analysis is rarely used for the verification of edible oil species, because of the low amount of intact DNA in the refined oil and the genetic similarities between different oil varieties.  In this study (open access pre-print, not yet peer-reviewed) the authors compared different DNA extraction kits and PCR protocols and new genetic markers to try and resolve the issue.  They reported that DNA extraction kits such as NucleoSpin Food, DNeasy mericon Food, and Olive Oil DNA Isolation as well as modified CTAB method were found to be able to isolate amplifiable genomic DNA from highly processed oils. Novel uniplex, double, and nested PCR systems targeting the sunflower-specific helianthinin gene were developed for efficient identification of sunflower. New sunflower DNA markers were revealed by uniplex PCRs.

They concluded that a combination of modified CTAB and nested PCR gave the best performance, and was demonstrated as a reliable, rapid, and cost-effective technology for detecting traces of sunflower in highly processed oil, including refined and used cooking oil.