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« Previous AbstractQuality classification of Spanish olive oils by untargeted gas chromatography coupled to hybrid quadrupole-time of flight mass spectrometry with atmospheric pressure chemical ionization and metabolomics-based statistical approach    Next AbstractStudy of the volatile compounds produced by Debaryomyces hansenii NRRL Y-7426 during the fermentation of detoxified concentrated distilled grape marc hemicellulosic hydrolysates »

Food Chem


Title:Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC-MS and multivariate statistical-based approach
Author(s):Sales C; Portoles T; Johnsen LG; Danielsen M; Beltran J;
Address:"Research Institute for Pesticides and Water (IUPA), University Jaume I, Avda. Sos Baynat, E-12071 Castellon, Spain. Research Institute for Pesticides and Water (IUPA), University Jaume I, Avda. Sos Baynat, E-12071 Castellon, Spain. Electronic address: tportole@uji.es. MS-Omics, Birkehegnet 40, Alsgarde, Denmark"
Journal Title:Food Chem
Year:2019
Volume:20180726
Issue:
Page Number:488 - 496
DOI: 10.1016/j.foodchem.2018.07.200
ISSN/ISBN:1873-7072 (Electronic) 0308-8146 (Linking)
Abstract:"The capabilities of dynamic headspace entrainment followed by thermal desorption in combination with gas chromatography (GC) coupled to single quadrupole mass spectrometry (MS) have been tested for the determination of volatile components of olive oil. This technique has shown a great potential for olive oil quality classification by using an untargeted approach. The data processing strategy consisted of three different steps: component detection from GC-MS data using novel data treatment software PARADISe, a multivariate analysis using EZ-Info, and the creation of the statistical models. The great number of compounds determined enabled not only the development of a quality classification method as a complementary tool to the official established method 'PANEL TEST' but also a correlation between these compounds and different types of defect. Classification method was finally validated using blind samples. An accuracy of 85% in oil classification was obtained, with 100% of extra virgin samples correctly classified"
Keywords:Gas Chromatography-Mass Spectrometry/*methods Mass Spectrometry Multivariate Analysis Olive Oil/*chemistry Plant Oils Sensation Volatile Organic Compounds/*analysis Dynamic headspace Foodomics Gc-ms Olive oil Parafac2;
Notes:"MedlineSales, C Portoles, T Johnsen, L G Danielsen, M Beltran, J eng England 2018/09/22 Food Chem. 2019 Jan 15; 271:488-496. doi: 10.1016/j.foodchem.2018.07.200. Epub 2018 Jul 26"

 
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