OLEUM Project. Classification of virgin olive oils based on quality grades and presence of defects using HS-GC-IMS as a rapid screening tool.

Panni, Filippo ; Casadei, Enrico ; Valli, Enrico ; Barbieri, Sara ; Cevoli, Chiara ; Bendini, Alessandra ; García González, Diego L. ; Gallina Toschi, Tullia (2019) OLEUM Project. Classification of virgin olive oils based on quality grades and presence of defects using HS-GC-IMS as a rapid screening tool. University of Bologna. DOI 10.6092/unibo/amsacta/6294. [Dataset]
Full text disponibile come:
[thumbnail of README file] Documento di testo(rtf) (README file)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0)

Download (143kB)
[thumbnail of Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects"] Foglio di Calcolo (Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects")
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0)

Download (37kB)
[thumbnail of Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects"] Foglio di Calcolo (Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects")
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0)

Download (25kB)
[thumbnail of Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects"_data matrix] Foglio di Calcolo (Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects"_data matrix)
Accesso riservato (solo Staff)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0)

Download (58kB) | Richiedi una copia
[thumbnail of Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects"_data matrix] Foglio di Calcolo (Underlying data set of the scientific publication "HS-GC-IMS as a rapid screening tool: classification of virgin olive oils based on quality grades and presence of defects"_data matrix)
Accesso riservato (solo Staff)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0)

Download (77kB) | Richiedi una copia

Abstract

This data set contains the underlying data of the scientific publication: Valli, E.; Panni, F.; Casadei, E.; Barbieri, S.; Cevoli, C.; Bendini, A.; García-González, D.L.; Gallina Toschi, T. An HS-GC-IMS Method for the Quality Classification of Virgin Olive Oils as Screening Support for the Panel Test. Foods 2020, 9(5), 657; https://doi.org/10.3390/foods9050657. Sensory analysis, carried out by Panel test, is essential for the quality classification of virgin olive oils (VOOs). The presence and perceived intensity of fruity attribute and sensory defects are linked with the occurrence of specific volatile compounds. Instrumental screening methods based on analysis of volatiles can support the Panel test through fast pre-classification of samples with a known probability, thus increasing the efficiency of quality control. A Headspace Gas Chromatography Ion Mobility Spectrometer (HS-GC-IMS) was used to analyze commercial VOOs by a semi-targeted approach. PLS-DA models were built by data matrices composed of 15 selected volatile compounds with which was possible to classify the samples based on quality grades and presence of defects.

Abstract
Tipologia del documento
Dataset
Autori
AutoreAffiliazioneORCID
Panni, FilippoUniversity of Bologna
Casadei, EnricoUniversity of Bologna
Valli, EnricoUniversity of Bologna
Barbieri, SaraUniversity of Bologna
Cevoli, ChiaraUniversity of Bologna
Bendini, AlessandraUniversity of Bologna
García González, Diego L.Instituto de la Grasa - CSIC
Gallina Toschi, TulliaUniversity of Bologna
Settori scientifico-disciplinari
DOI
Contributors
Contributor
Affiliazione
Tipo
Bendini, Alessandra
University of Bologna
Contact person
Data di deposito
19 Dic 2019 13:25
Ultima modifica
10 Giu 2020 13:17
Risorse collegate
Tipologia
Relazione
Identificativo
Nome del Progetto
OLEUM - Advanced solutions for assuring the overall authenticity and quality of olive oil
Programma di finanziamento
EC - H2020
URI

Altri metadati

Statistica sui download

Statistica sui download

Gestione del documento: Visualizza il documento

^