Measurement Time Reduction by Means of Mathematical Modeling of Enzyme Mediated RedOx Reaction in Food Samples Biosensors
dc.contributor.author | Florez, Arantzazu | |
dc.contributor.author | Murga, Elena | |
dc.contributor.author | Ortiz de Zarate, Itziar | |
dc.contributor.author | Jaureguibeitia, Arrate | |
dc.contributor.author | Artetxe, Arkaitz | |
dc.contributor.author | Sierra Araujo, Basilio ![]() | |
dc.date.accessioned | 2021-05-19T11:56:42Z | |
dc.date.available | 2021-05-19T11:56:42Z | |
dc.date.issued | 2021-04-24 | |
dc.identifier.citation | Sensors 21(9) : (2021) // Article ID 2990 | es_ES |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10810/51486 | |
dc.description.abstract | The possibility of measuring in real time the different types of analytes present in food is becoming a requirement in food industry. In this context, biosensors are presented as an alternative to traditional analytical methodologies due to their specificity, high sensitivity and ability to work in real time. It has been observed that the behavior of the analysis curves of the biosensors follow a trend that is reproducible among all the measurements and that is specific to the reaction that occurs in the electrochemical cell and the analyte being analyzed. Kinetic reaction modeling is a widely used method to model processes that occur within the sensors, and this leads to the idea that a mathematical approximation can mimic the electrochemical reaction that takes place while the analysis of the sample is ongoing. For this purpose, a novel mathematical model is proposed to approximate the enzymatic reaction within the biosensor in real time, so the output of the measurement can be estimated in advance. The proposed model is based on adjusting an exponential decay model to the response of the biosensors using a nonlinear least-square method to minimize the error. The obtained results show that our proposed approach is capable of reducing about 40% the required measurement time in the sample analysis phase, while keeping the error rate low enough to meet the accuracy standards of the food industry. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | chemical and biological sensors | es_ES |
dc.subject | mathematical modeling | es_ES |
dc.subject | optimization | es_ES |
dc.subject | kinetic modeling | es_ES |
dc.subject | parameter estimation | es_ES |
dc.title | Measurement Time Reduction by Means of Mathematical Modeling of Enzyme Mediated RedOx Reaction in Food Samples Biosensors | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2021-05-13T14:33:42Z | |
dc.rights.holder | 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/21/9/2990/htm | es_ES |
dc.identifier.doi | 10.3390/s21092990 | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala |
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Except where otherwise noted, this item's license is described as 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).