Use of a bioelectronic tongue for the monitoring of the photodegradation of phenolic compounds

Xavier Cetó; Andreu González-Calabuig; Manel del Valle

doi:10.1002/elan.201400394

Use of a bioelectronic tongue for the monitoring of the photodegradation of phenolic compounds

Xavier Cetó, Andreu González-Calabuig, Manel del Valle

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© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. The application of a voltammetric bioelectronic tongue for the simultaneous monitoring of catechol, m-cresol and guaiacol in wastewater is reported. Voltammetric responses obtained from an array of bulk modified (bio)sensors, containing enzymes such as tyrosinase and laccase, were combined with chemometric tools such as artificial neural networks (ANNs) for building the quantitative prediction model. To this end, the chemometric model was first built employing a factorial design, validated employing an external test set of samples (n=14; total NRMSE of 0.076), and afterwards applied to the monitoring of the mineralization of the three phenol pollutants during a photo-Fenton advanced oxidation process.

Idioma original	Anglès
Pàgines (de-a)	225-233
Revista	Electroanalysis
Volum	27
Número	1
DOIs	https://doi.org/10.1002/elan.201400394
Estat de la publicació	Publicada - 1 de gen. 2015

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10.1002/elan.201400394

https://ddd.uab.cat/record/144739Llicència: Creative Commons Reconeixement No Comercial - Sense Obra Derivada

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title = "Use of a bioelectronic tongue for the monitoring of the photodegradation of phenolic compounds",

abstract = "{\textcopyright} 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. The application of a voltammetric bioelectronic tongue for the simultaneous monitoring of catechol, m-cresol and guaiacol in wastewater is reported. Voltammetric responses obtained from an array of bulk modified (bio)sensors, containing enzymes such as tyrosinase and laccase, were combined with chemometric tools such as artificial neural networks (ANNs) for building the quantitative prediction model. To this end, the chemometric model was first built employing a factorial design, validated employing an external test set of samples (n=14; total NRMSE of 0.076), and afterwards applied to the monitoring of the mineralization of the three phenol pollutants during a photo-Fenton advanced oxidation process.",

keywords = "Artificial neural network, Electronic tongue, Phenolic compounds, Voltammetric biosensor, Wastewater",

author = "Xavier Cet{\'o} and Andreu Gonz{\'a}lez-Calabuig and {del Valle}, Manel",

year = "2015",

month = jan,

day = "1",

doi = "10.1002/elan.201400394",

language = "English",

volume = "27",

pages = "225--233",

journal = "Electroanalysis",

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publisher = "Wiley-VCH Verlag",

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TY - JOUR

T1 - Use of a bioelectronic tongue for the monitoring of the photodegradation of phenolic compounds

AU - Cetó, Xavier

AU - González-Calabuig, Andreu

AU - del Valle, Manel

PY - 2015/1/1

Y1 - 2015/1/1

N2 - © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. The application of a voltammetric bioelectronic tongue for the simultaneous monitoring of catechol, m-cresol and guaiacol in wastewater is reported. Voltammetric responses obtained from an array of bulk modified (bio)sensors, containing enzymes such as tyrosinase and laccase, were combined with chemometric tools such as artificial neural networks (ANNs) for building the quantitative prediction model. To this end, the chemometric model was first built employing a factorial design, validated employing an external test set of samples (n=14; total NRMSE of 0.076), and afterwards applied to the monitoring of the mineralization of the three phenol pollutants during a photo-Fenton advanced oxidation process.

AB - © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. The application of a voltammetric bioelectronic tongue for the simultaneous monitoring of catechol, m-cresol and guaiacol in wastewater is reported. Voltammetric responses obtained from an array of bulk modified (bio)sensors, containing enzymes such as tyrosinase and laccase, were combined with chemometric tools such as artificial neural networks (ANNs) for building the quantitative prediction model. To this end, the chemometric model was first built employing a factorial design, validated employing an external test set of samples (n=14; total NRMSE of 0.076), and afterwards applied to the monitoring of the mineralization of the three phenol pollutants during a photo-Fenton advanced oxidation process.

KW - Artificial neural network

KW - Electronic tongue

KW - Phenolic compounds

KW - Voltammetric biosensor

KW - Wastewater

U2 - 10.1002/elan.201400394

DO - 10.1002/elan.201400394

M3 - Article

SN - 1040-0397

VL - 27

SP - 225

EP - 233

JO - Electroanalysis

JF - Electroanalysis

IS - 1

ER -

Use of a bioelectronic tongue for the monitoring of the photodegradation of phenolic compounds

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