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GC-IMS screening to cluster the sensory grades of virgin olive oils

Authors: CASADEI, ENRICO; Filippo Panni; Enrico Valli; Alessandra Bendini; Michele Gianelli; Diego Luis Garcia Gonzalez; Tullia Gallina Toschi;

GC-IMS screening to cluster the sensory grades of virgin olive oils

Abstract

In this work, the use of a gas chromatography coupled to an ion mobility spectrometer with a tritium source was investigated for the discrimination of virgin olive oils previously sensory assessed (EU Reg. 1227/2016) and characterized by different quality grades (extra virgin, virgin, lampante). The samples were injected by a headspace system and, after the gas chromatographic separation, the ion mobility data coming from the eluted volatiles were processed with various chemometric tools. The preliminary elaboration evidenced a promising capacity to discriminate the samples according to their quality grade. The proposed approach is also sustainable and fast. This work was developed in the context of the project OLEUM “Advanced solutions for assuring authenticity and quality of olive oil at global scale“ funded by the European Commission within the Horizon 2020 Programme (2014–2020, grant agreement no. 635690). The information expressed in this abstract reflects the authors’ views; the EC is not liable for the information contained therein. The authors are grateful to the six sensory panels of the OLEUM consortium for the sensory evaluation of samples.

Country
Italy
Keywords

GC-IMS, sensory analysis, virgin olive oils, chemiometric

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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