DIFFERENTIAL SCANNING CALORIMETRY DETECTION OF HIGH OLEIC SUNFLOWER OIL AS AN ADULTERANT IN EXTRA-VIRGIN OLIVE OIL

Advanced techniques in edible oil authentication: A systematic review and critical analysis

Adulteration of edible substances is a potent contemporary food safety issue. Perhaps the overt concern derives from the fact that adulterants pose serious ill effects on human health. Edible oils are one of the most adulterated food products. Perpetrators are adopting ways and means that effectively masks the presence of the adulterants from human organoleptic limits and traditional oil adulteration detection techniques. This review embodies a detailed account of chemical, biosensors, chromatography, spectroscopy, differential scanning calorimetry, non-thermal plasma, dielectric spectroscopy research carried out in the area of falsification assessment of edible oils for the past three decades and a collection of patented oil adulteration detection techniques. The detection techniques reviewed have some advantages and certain limitations, chemical tests are simple; biosensors and nuclear magnetic resonance are rapid but have a low sensitivity; chromatography and spectroscopy are highly accurate with a deterring price tag; dielectric spectroscopy is rapid can be portable and has on-line compatibility; however, the results are susceptible to variation of electric current frequency and intrinsic factors (moisture, temperature, structural composition). This review paper can be useful for scientists or for knowledge seekers eager to be abreast with edible oil adulteration detection techniques.

Rapid screening for hazelnut oil and high-oleic sunflower oil in extra virgin olive oil using low-field nuclear magnetic resonance relaxometry and machine learning

BACKGROUND

As extra virgin olive oil (EVOO) has high commercial value, it is routinely adulterated with other oils. The present study investigated the feasibility of rapidly identifying adulterated EVOO using low-field nuclear magnetic resonance (LF-NMR) relaxometry and machine learning approaches (decision tree, K-nearest neighbor, linear discriminant analysis, support vector machines and convolutional neural network (CNN)).

RESULTS

LF-NMR spectroscopy effectively distinguished pure EVOO from that which was adulterated with hazelnut oil (HO) and high-oleic sunflower oil (HOSO). The applied CNN algorithm had an accuracy of 89.29%, a precision of 81.25% and a recall of 81.25%, and enabled the rapid (2 min) discrimination of pure EVOO that was adulterated with HO and HOSO in the volumetric ratio range of 10-100%.

CONCLUSIONS

LF-NMR coupled with the CNN algorithm is a viable candidate for rapid EVOO authentication. © 2020 Society of Chemical Industry.

Olive oil authentication: A comparative analysis of regulatory frameworks with especial emphasis on quality and authenticity indices, and recent analytical techniques developed for their assessment. A review

Over the last decades, olive oil quality and authenticity control has become an issue of great importance to consumers, suppliers, retailers, and regulators in both traditional and emerging olive oil producing countries, mainly due to the increasing worldwide popularity and the trade globalization of this product. Thus, in order to ensure olive oil authentication, various national and international laws and regulations have been adopted, although some of them are actually causing an enormous debate about the risk that they can represent for the harmonization of international olive oil trade standards. Within this context, this review was designed to provide a critical overview and comparative analysis of selected regulatory frameworks for olive oil authentication, with special emphasis on the quality and purity criteria considered by these regulation systems, their thresholds and the analytical methods employed for monitoring them. To complete the general overview, recent analytical advances to overcome drawbacks and limitations of the official methods to evaluate olive oil quality and to determine possible adulterations were reviewed. Furthermore, the latest trends on analytical approaches to assess the olive oil geographical and varietal origin traceability were also examined.

Authentication analysis of cod liver oil from beef fat using fatty acid composition and FTIR spectra

This study aimed to authenticate cod liver oil (CLO) from beef fat (BF) by determining the level of BF as a fat adulterant in CLO. Two instrumental techniques, namely GC-FID for fatty acid analysis and Fourier transform infrared (FTIR) spectroscopy, were exploited for such authentication. The decreased level of some fatty acids, especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), could be used as an indicative means to detect the adulteration of CLO with BF. In addition, FTIR spectroscopy combined with partial least-squares (PLS) at frequency regions of 1200-1000 cm(-1) was successfully developed for the quantification of BF in CLO. Using the PLS model, the errors obtained in calibration and prediction samples were 0.55% and 0.82% v/v, respectively.