Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approach
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Other documents of the author: Sales Martínez, Carlos; Portoles, Tania; Johnsen, L. G.; Danielsen, M.; Beltran Arandes, Joaquin
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comunitat-uji-handle2:10234/33596
comunitat-uji-handle3:10234/33597
comunitat-uji-handle4:
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Title
Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approachAuthor (s)
Date
2019-01-15Publisher
ElsevierBibliographic citation
SALES MARTÍNEZ, Carlos; PORTOLÉS NICOLAU, Tania; JOHNSEN, L. G.; DANIELSEN, M.; BELTRÁN ARANDES, Joaquim (2018). Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approach. Food Chemistry, v. 271, p. 488-496Type
info:eu-repo/semantics/articlePublisher version
https://www.sciencedirect.com/science/article/pii/S0308814618313554Version
info:eu-repo/semantics/publishedVersionSubject
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 determi-
nation ... [+]
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 determi-
nation of volatile components of olive oil. This technique has shown a great potential for olive oil quality
classi
fi
cation by using an untargeted approach. The data processing strategy consisted of three di
ff
erent 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 classi
fi
cation method as a complementary tool to the o
ffi
cial established
method
“
PANEL TEST
”
but also a correlation between these compounds and di
ff
erent types of defect.
Classi
fi
cation method was
fi
nally validated using blind samples. An accuracy of 85% in oil classi
fi
cation was
obtained, with 100% of extra virgin samples correctly classi
fi
ed [-]
Is part of
Food Chemistry (2019), v. 271Investigation project
1) Generalitat Valenciana, Spain, as research group of excellence (PROMETEO II/ 2014/023); 2) Collaborative Research on Environment and Food-Safety (ISIC/2012/016); 3) University Jaume I, Spain (UJI-B2016-10); 4) Juan de la Cierva Incorporation Program from Ministry of Economy and Competitivenes, Spain (IJCI-2014-20588).Rights
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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