Abstract

The undeclared blending of EVOO with soft-refined oils is one of the main issue in the olive oil sector. Despite the efforts, reliable markers related to soft-refinement processes have not been found yet. In the present work, two rapid headspace-based techniques, namely gas-chromatography ion mobility spectrometry and flash gas chromatography electronic nose, were proposed and tested as rapid screening tools for the detection of this fraud practice. Since real counterfeited samples are not commercially available, soft refined and deacidified olive oils were recreated at a laboratory scale and mixed with EVOO at different percentages. Commercial EVOOs sampled over three harvesting seasons (2015/2016, 2016/2017 and 2017/2018), along with the in-house prepared blends, were analysed by means of the above-mentioned techniques. SIMCA was chosen as classification algorithm to discern the illicit mix from the authentic EVOOs. Both the analytical techniques exhibited notable robustness and stability over the time in terms of intra- and inter-day reproducibility. Concerning the samples discrimination, the final outcome was found to be greatly affected by the inclusion (or exclusion) of the EVOO15/16 group in the model training. When EVOO from more recent harvests (i.e. EVOO16/17, EVOO17/18) were used to calibrate the model, a practically 100% specificity was achieved by both the techniques and even the lowest-percentage adulterated samples (i.e. 10%) were recognized to be non-authentic EVOOs. On the other hand, poorer classification was achieved including the EVOO15/16 in the model training. The present work demonstrated that focusing on the volatile fraction might be the right strategy to overcome the lack of clear and specific process-related marker formed upon soft-refinement processes. At the same time, it highlighted how the EVOO chemical (in)stability would be a crucial aspect to be considered in the development of fingerprinting methods.

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