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dc.contributor.authorPérez González, Clara
dc.contributor.authorSalvo Comino, Coral 
dc.contributor.authorMartín Pedrosa, Fernando 
dc.contributor.authorGarcía Cabezón, Ana Cristina 
dc.contributor.authorRodríguez Méndez, María Luz 
dc.date.accessioned2022-10-17T12:48:01Z
dc.date.available2022-10-17T12:48:01Z
dc.date.issued2022
dc.identifier.citationFood Control, Volume 145, 2023, 109425es
dc.identifier.issn0956-7135es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/55976
dc.descriptionProducción Científicaes
dc.description.abstractBioelectronic tongues (bioET) made of sensors combining enzymes and nanomaterials have been shown to be advantageous due to the specificity offered by the biosensors and the enhanced sensitivity provided by the nanomaterials. In this work, an innovative bioET for milk analysis is developed using potentiometric biosensors based on lactic dehydrogenase, galactose oxidase and urease specific for the detection of compounds of interest in milk (lactic acid, galactose and urea). The performance of the biosensors has been fostered by covalently immobilizing the enzymes on membranes of carboxylated polyvinyl chloride combined with gold nanoparticles. The design and composition of the biosensors contributes to preserving the enzymatic activity, allowing limits of detection in the range of 10−5 – 10−6 M with excellent sensitivity and reproducibility (variation coefficients ranged from 1 to 5.1%). The three biosensors, combined in a single device and coupled to a pattern recognition software, can discriminate efficiently twelve classes of milk with different fat content (skimmed, semi-skimmed and whole milk) and nutritional characteristics (calcium enriched, lactose free and folic acid-enriched). The bioET shows an excellent classification capability with an accuracy of up to 99.7%. By applying Support Vector Machine (SVM) analysis, the BioET can perform the simultaneous assessment of eight physicochemical parameters (acidity, fat, proteins, lactose, density, urea, dry matter and nonfat dry matter) with satisfactory correlation coefficients and low residual errors. The results are further improved by implementing ensemble methodologies. The proposed strategy has been demonstrated to be useful for improving the performance of bioETs in the dairy industry.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationBioelectronic tonguees
dc.subject.classificationLengua bioelectrónicaes
dc.subject.classificationMilkes
dc.subject.classificationLechees
dc.subject.classificationBiosensorses
dc.subject.classificationBiosensoreses
dc.subject.classificationGold nanoparticleses
dc.subject.classificationNanopartículas de oroes
dc.titleBioelectronic tongue dedicated to the analysis of milk using enzymes linked to carboxylated-PVC membranes modified with gold nanoparticleses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2022 Elsevieres
dc.identifier.doi10.1016/j.foodcont.2022.109425es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0956713522006181?via%3Dihubes
dc.peerreviewedSIes
dc.description.projectMinisterio de Ciencia, Innovación y Universidades - Fondo Europeo de Desarrollo Regional (project RTI2018-097990-B-100)es
dc.description.projectJunta de Castilla y León - Fondo Europeo de Desarrollo Regional (project VA202P20)es
dc.description.projectUnión Europea - Fondo Europeo de Desarrollo Regional (project CLU-2019-04)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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