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Spreadsheet (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")
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Spreadsheet (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")
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Spreadsheet (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)
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Spreadsheet (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)
Repository staff only License: Creative Commons: Attribution 4.0 (CC BY 4.0) Download (77kB) | Request a copy |
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.