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
Comments