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dc.contributor.authorArroyo-Manzanares, N.-
dc.contributor.authorMarkiv, B.-
dc.contributor.authorHernández, J.D.-
dc.contributor.authorLópez-García, I.-
dc.contributor.authorGuillén, I.-
dc.contributor.authorVizcaíno, P.-
dc.contributor.authorHernández Córdoba, Manuel-
dc.contributor.authorViñas López-Pelegrín, Pilar-
dc.contributor.otherFacultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Química Analíticaes
dc.date.accessioned2021-11-03T17:15:41Z-
dc.date.available2021-11-03T17:15:41Z-
dc.date.issued2019-08-15-
dc.identifier.citationFood Chemistry, 2019, Volumen 289, Paginas 461-467.es
dc.identifier.issn0308-8146-
dc.identifier.urihttp://hdl.handle.net/10201/113643-
dc.description.abstractHead-space (HS) gas chromatography (GC) coupled to mass spectrometry (MS) is proposed for the assessment of the contamination of mayonnaise as an alternative to plate counting, which is the technique commonly used for evaluating microbial contamination. More specifically, this method was applied in the detection of Candida metapsilosis and Zygosaccharomyces bailii, both of great importance in term of food spoilage since they are resistant to many of the common methods of food preservation. Different chemometric models were investigated using the data obtained by GC-MS (m/z profile, area of the chromatographic peaks and entire chromatographic profile), in order to obtain the highest classification success. The best results were obtained using the chromatographic profile (success rate of 92%). Contaminated samples could also be classified according to the concentration of yeast, obtaining a success rate of 87.5%. Finally, a chemometric model was constructed in an attempt to differentiate between strains.es
dc.formatapplication/pdfes
dc.format.extent20es
dc.languageenges
dc.publisherElsevier B.V.es
dc.relation- Nombre del proyecto: Advances in Analytical Chemistry: microextraction techniques for simplification and miniaturization of the analytical process. Código: 19888/GERM/15. Agencia/entidad financiadora: Comunidad Autónoma de la Región de Murcia. Programa de Generación de conocimiento Científico de Excelencia de la Fundación Séneca. Ámbito del proyecto: Regional. - Nombre del proyecto: Estrategias basadas en sistemas de microextracción para la mejora de la calidad del laboratorio analítico. Código: CTQ2015-68049-R. Agencia/entidad financiadora: Ministerio de Economía y Competitividad. Ámbito del proyecto: Nacionales
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGas chromatographyes
dc.subjectMass spectrometryes
dc.subjectMayonnaisees
dc.subjectYeast determinationes
dc.subjectChemometricses
dc.subject.otherCDU::5 - Ciencias puras y naturales::54 - Química::543 - Química analíticaes
dc.titleHead-space gas chromatography coupled to mass spectrometry for the assessment of the contamination of mayonnaise by yeastses
dc.typeinfo:eu-repo/semantics/articlees
dc.relation.publisherversionhttps://doi.org/10.1016/j.foodchem.2019.03.083es
dc.identifier.doi10.1016/j.foodchem.2019.03.083-
Aparece en las colecciones:Artículos: Química Analítica

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