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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/52836

    Título
    Improving the performance of a bioelectronic tongue using silver nanowires. Application to milk analysis
    Autor
    Salvo Comino, CoralAutoridad UVA
    Martín Bartolomé, Patricia
    Pura Ruiz, José LuisAutoridad UVA
    Pérez González, ClaraAutoridad UVA
    Martín Pedrosa, FernandoAutoridad UVA Orcid
    García Cabezón, Ana CristinaAutoridad UVA Orcid
    Rodríguez Méndez, María LuzAutoridad UVA Orcid
    Año del Documento
    2022
    Editorial
    Elsevier
    Descripción
    Producción Científica
    Documento Fuente
    Sensors and Actuators B: Chemical, 2022, vol. 364, 131877
    Resumen
    Recent advances in the field of electronic tongues (ET) are linked to the development of devices dedicated to a particular application. Following this idea, we have developed a voltammetric bioelectronic tongue (bioET) specifically dedicated to analyze milk. The performance of the multisensor system has been improved by incorporating biosensors combining specific enzymes for the detection of sugars present in milk (β-galactosidase, glucose oxidase and galactose oxidase) with silver nanomaterials. It has been demonstrated that silver nanowires (AgNWs) provide a more effective platform for the immobilization of biomolecules than silver nanoparticles (AgNPs), inducing unique performance characteristics in terms of sensitivity and detection limits. Two multisensor systems have been developed; one based on combinations of AgNWs and enzymes (AgNW/bioET) and a second based on combinations of AgNPs and enzymes (AgNP/bioET). Principal component analysis (PCA) demonstrates that the bioET based on combinations of AgNWs and enzymes (AgNW/bioET) can discriminate 9 classes of milk with different fat content (skimmed, semi-skimmed and whole), as well as different nutritional compositions (classic, calcium-enriched and lactose-free), with a higher capacity than the bioET based on combinations of AgNPs and enzymes (AgNP/bioET). Support vector machine (SVMR) models show excellent correlation coefficients between the responses of the bioETs and physicochemical parameters commonly used to evaluate the quality of milk (acidity, density, fat, proteins, lactose, total dry matter and non-fat dry matter). The good results obtained support the dairy industry’s interest in dedicated bioETs, not only for classification purposes but also to obtain information concerning several physicochemical parameters in a single
    Palabras Clave
    Electronic tongue
    Lengua electrónica
    Electrochemical sensors
    Sensores electroquímicos
    Milk
    Leche
    ISSN
    0925-4005
    Revisión por pares
    SI
    DOI
    10.1016/j.snb.2022.131877
    Patrocinador
    Ministerio de Economía, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (project RTI2018-097990-B-100)
    Junta de Castilla y León - Fondo Europeo de Desarrollo Regional (project VA202P20)
    Infraestructuras Red de Castilla y León (INFRARED) UVA01 - Unión Europea - Fondo Europeo de Desarrollo Regional (project CLU-2019-04)
    Ministerio de Ciencia, Innovación y Universidades (fellowship AGL 2015-67482_R)
    Version del Editor
    https://www.sciencedirect.com/science/article/pii/S0925400522005196?via%3Dihub
    Propietario de los Derechos
    © 2022 The Authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/52836
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • BioEcoUVa - Artículos de revista [195]
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