Catalonia, located in the northeast of Spain, comprises five extra virgin olive oil (EVOO) protected designations of origin (PDOs). Despite the proximity between them, these PDOs represent unique pedoclimatic conditions and traditional olive cultivars that are briefly reviewed in the present manuscript. In addition to the compliance with quality standards fixed by product specifications, EVOOs show singular and distinctive composition and sensory profiles. With the aim to describe the characteristics of Catalan EVOOs, their sensory and analytical traits are reviewed with the support of data collected between 2009 and 2017 in more than 42 milling facilities from the five Catalan PDOs, within the frame of official surveys launched by the Catalan Government. ; info:eu-repo/semantics/acceptedVersion
8 Páginas.-- 4 Figuras.-- 3 Tablas ; Sensory quality, assessed following a standardized method, is one of the parameters defining the commercial category of virgin olive oil. Considering the difficulties linked to the organoleptic evaluation, especially the high number of samples to be assessed, setting up instrumental methods to support sensory panels becomes a need for the olive oil sector. Volatile fingerprint by Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry can be an excellent fit-for-purpose tool as the volatile fraction is responsible for virgin olive oil sensory attributes. A fingerprinting approach was applied to the volatile profile of 176 virgin olive oils previously graded by six official sensory panels. The classification strategy consisted in two sequential Partial Least Square-Discriminant Analysis models built with the aligned chromatograms: the first discriminated extra virgin and non-extra virgin samples; the second classified the latter into virgin or lampante categories. Results were satisfactory in the cross-validation by leave 10%-out (97% of correct classification). For external validation, an uncertainty range was set for the prediction models to detect boundary samples, which would be further assessed by the sensory panels. By doing this, a considerable decrease of the panel workload (around 80%) was achieved, while maintaining a highly reliable classification of samples (error rate <10%). ; 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 Program (2014–2020, grant agreement no. 635690). The information and views set out in this article are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. B. Quintanilla-Casas thanks the Spanish Ministry of Science, Innovation and Universities predoctoral fellowship FPU16/01744. A. Tres thanks the Spanish Ministry of Economy, Industry and Competitivity "Juan de la Cierva" postdoctoral fellowship (JCI-2012_13412) and the Ministry of Science, Innovation and Universities "Ramón y Cajal" postdoctoral fellowship (RYC-2017-23601). ; Peer reviewed
14 Páginas.-- 3 Tablas.-- 2 Figuras ; The commercial category of virgin olive oil is currently assigned on the basis of chemical-physical and sensory parameters following official methods. Considering the limited number of samples that can be analysed daily by a sensory panel, an instrumental screening tool could be supportive by reducing the assessors' workload and improving their performance. The present work aims to in-house validate a screening strategy consisting of two sequential binary partial least squares-discriminant analysis (PLS-DA) models that was suggested to be successful in a proof-of-concept study. This approach is based on the volatile fraction fingerprint obtained by HS-SPME–GC–MS from more than 300 virgin olive oils from two crop seasons graded by six different sensory panels into extra virgin, virgin or lampante categories. Uncertainty ranges were set for the binary classification models according to sensitivity and specificity by means of receiver operating characteristics (ROC) curves, aiming to identify boundary samples. Thereby, performing the screening approach, only the virgin olive oils classified as uncertain (23.3%) would be assessed by a sensory panel, while the rest would be directly classified into a given commercial category (78.9% of correct classification). The sensory panel's workload would be reduced to less than one-third of the samples. A highly reliable classification of samples would be achieved (84.0%) by combining the proposed screening tool with the reference method (panel test) for the assessment of uncertain samples. ; 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 Program (2014–2020, grant agreement no. 635690). The information and views set out in this article are those of the authors and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. B. Q-C. and A.T. thanks the Spanish Ministry of Science, Innovation and Universities predoctoral fellowship FPU16/01744 and "Ramón y Cajal" postdoctoral fellowship (RYC-2017-23601), respectively. ; Peer reviewed
