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This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 613688

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GC-IMS and FGC-Enose fingerprint as screening tools for revealing extra virgin olive oil blending with soft-refined olive oils

GC-IMS and FGC-Enose fingerprint as screening tools for revealing extra virgin olive oil blending with soft-refined olive oils

GC-IMS and FGC-Enose fingerprint as screening tools for revealing extra
virgin olive oil blending with soft-refined olive oils: A feasibility study
Tito Damiani, Daniele Cavanna, Andrea Serani, Chiara Dall'Asta, Michele Suman

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.