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Article

Supporting the Sensory Panel to Grade Virgin Olive Oils: An In-House-Validated Screening Tool by Volatile Fingerprinting and Chemometrics

1
Departament de Nutrició, Ciències de l’Alimentació i Gastronomia, Campus de l’Alimentació de Torribera, Facultat de Farmacia i Ciències de l’Alimentació, Universitat de Barcelona, 08921 Santa Coloma de Gramenet, Spain
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Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Universitat de Barcelona (UB), 08921 Santa Coloma de Gramenet, Spain
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Instituto de la Grasa (CSIC), 41013 Sevilla, Spain
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Department of Agricultural and Food Science, Alma Mater Studiorum-Università di Bologna, 47521 Cesena, Italy
*
Author to whom correspondence should be addressed.
Foods 2020, 9(10), 1509; https://doi.org/10.3390/foods9101509
Received: 10 September 2020 / Revised: 12 October 2020 / Accepted: 19 October 2020 / Published: 21 October 2020
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. View Full-Text
Keywords: virgin olive oil; sensory quality; volatile compounds; HS-SPME–GC–MS; chemometrics; panel test; validation; untargeted virgin olive oil; sensory quality; volatile compounds; HS-SPME–GC–MS; chemometrics; panel test; validation; untargeted
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MDPI and ACS Style

Quintanilla-Casas, B.; Marin, M.; Guardiola, F.; García-González, D.L.; Barbieri, S.; Bendini, A.; Gallina Toschi, T.; Vichi, S.; Tres, A. Supporting the Sensory Panel to Grade Virgin Olive Oils: An In-House-Validated Screening Tool by Volatile Fingerprinting and Chemometrics. Foods 2020, 9, 1509. https://doi.org/10.3390/foods9101509

AMA Style

Quintanilla-Casas B, Marin M, Guardiola F, García-González DL, Barbieri S, Bendini A, Gallina Toschi T, Vichi S, Tres A. Supporting the Sensory Panel to Grade Virgin Olive Oils: An In-House-Validated Screening Tool by Volatile Fingerprinting and Chemometrics. Foods. 2020; 9(10):1509. https://doi.org/10.3390/foods9101509

Chicago/Turabian Style

Quintanilla-Casas, Beatriz, Marco Marin, Francesc Guardiola, Diego L. García-González, Sara Barbieri, Alessandra Bendini, Tullia Gallina Toschi, Stefania Vichi, and Alba Tres. 2020. "Supporting the Sensory Panel to Grade Virgin Olive Oils: An In-House-Validated Screening Tool by Volatile Fingerprinting and Chemometrics" Foods 9, no. 10: 1509. https://doi.org/10.3390/foods9101509

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