Gas chromatography-mass spectrometry based untargeted volatolomics for smoked seafood classification
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Otros documentos de la autoría: Lacalle-Bergeron, Leticia; Portoles, Tania; Sales Martínez, Carlos; Corell, María Carmen; Domínguez, Fernando; Beltran Arandes, Joaquin; Sancho, Juan V; Hernandez, Felix
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Título
Gas chromatography-mass spectrometry based untargeted volatolomics for smoked seafood classificationAutoría
Fecha de publicación
2020-11Editor
ElsevierCita bibliográfica
LACALLE-BERGERON, Leticia, et al. Gas chromatography-mass spectrometry based untargeted volatolomics for smoked seafood classification. Food Research International, 2020, v. 137, p. 109698.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S0963996920307237Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
With the increase of the demand of low flavouring smoked seafood products, there is a need of methodologies
able to distinguish between different seafood treatments, as not all of them are allowed in all markers.
... [+]
With the increase of the demand of low flavouring smoked seafood products, there is a need of methodologies
able to distinguish between different seafood treatments, as not all of them are allowed in all markers.
Following this objective, in the present work an untargeted volatolomics approach was applied to identify
volatile markers that demonstrate that Cold smoked products can be distinguished from Tasteless smoke neither
Carbon monoxide treated seafood, which are prohibited in the European Union.
The use of dynamic headspace for the volatile extraction followed by thermal desorption in combination with
Gas Chromatography (GC) coupled to single quadrupole Mass Spectrometry (MS) has been employed for the
determination of volatile composition of smoked fish. Data processing consisted on the use of PARADISe software, applied for GC/MS data treatment, followed by the multivariate analysis with PLS_Toolbox (MATLAB), and
finally the creation and validation of statistical classification model.
All 107 variables obtained allowed the construction of a model reaching the correct classification of 97% of the
blind samples, while a simplified model with only 11 variables correctly classified up to 93% of the blind
samples. These 11 compounds were elucidated to develop subsequent target volatolomics approaches, if needed.
Ordered according to the importance in the classification model, the elucidated compounds were: 3-methylcyclopentanone, ethylbenzene, 2-methyl-2-cyclopenten-1-one, 2-methyl-benzofuran, furfuryl alcohol, 2-acetylfuran, acetophenone, guaiacol, 1-hydroxy-2-butanone, 4-vinylguaicol and acetoin.
The results demonstrated the great potential of untargeted volatolomics for smoked seafood treatments
classification. [-]
Publicado en
Food Research International (2020). v. 137Proyecto de investigación
1) Pre-doctoral grant (UJI19I001/03); 2) Ramon y Cajal Program from the Ministry of Economy and Competitiveness, Spain (RYC-2017-22525); 3) Generalitat Valenciana, as research group of excellence PROMETEO/2019/040.Derechos de acceso
info:eu-repo/semantics/openAccess
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