Literature DB >> 15626626

Determination of phenolic compounds by a polyphenol oxidase amperometric biosensor and artificial neural network analysis.

A Gutés1, F Céspedes, S Alegret, M del Valle.   

Abstract

The determination of phenolic compounds is significant given its toxicity, even at very low concentration levels. Amperometric determination of phenols is a simple technique available. Direct oxidation of phenols can be used, but another possibility is the use of polyphenol oxidase (tyrosinase) enzyme biosensors that oxidises the phenolic compounds into their corresponding quinones. Reduction of the resulting quinones accomplishes the amplification of the amperometric signal, as long as the result of the reduction process is the corresponding cathecol, this being able to be oxidised again by the polyphenol oxidase immobilized on the surface of the biosensor. In this communication, simultaneous determination of different phenols was carried out combining biosensor measurements with chemometric tools, in what is known as electronic tongue. The departure information used was the overlapped reduction voltammogram generated with the amperometric biosensor based on polyphenol oxidase. Artificial Neural Networks (ANN) were used for extraction and quantification of each compound. Phenol, cathecol and m-cresol formed the three-analyte study case resolved in this work. Good prediction ability was attained, and so, the separate quantification of these three phenols was accomplished.

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Year:  2005        PMID: 15626626     DOI: 10.1016/j.bios.2004.07.026

Source DB:  PubMed          Journal:  Biosens Bioelectron        ISSN: 0956-5663            Impact factor:   10.618


  7 in total

1.  Discrimination of Rice with Different Pretreatment Methods by Using a Voltammetric Electronic Tongue.

Authors:  Li Wang; Qunfeng Niu; Yanbo Hui; Huali Jin
Journal:  Sensors (Basel)       Date:  2015-07-22       Impact factor: 3.576

2.  Micelle-assisted synthesis of Al2O3·CaO nanocatalyst: optical properties and their applications in photodegradation of 2,4,6-trinitrophenol.

Authors:  Ayesha Imtiaz; Muhammad Akhyar Farrukh; Muhammad Khaleeq-ur-rahman; Rohana Adnan
Journal:  ScientificWorldJournal       Date:  2013-11-07

Review 3.  Application of Chemometrics in Biosensing: A Review.

Authors:  Ekaterina Martynko; Dmitry Kirsanov
Journal:  Biosensors (Basel)       Date:  2020-08-17

4.  Potential applications of halophilic microorganisms for biological treatment of industrial process brines contaminated with aromatics.

Authors:  Thomas Mainka; David Weirathmüller; Christoph Herwig; Stefan Pflügl
Journal:  J Ind Microbiol Biotechnol       Date:  2021-04-30       Impact factor: 4.258

5.  Quantitative Structure-Activity Relationship, Ontology-Based Model of the Antioxidant and Cell Protective Activity of Peat Humic Acids.

Authors:  Maria V Zykova; Konstantin S Brazovskii; Kristina A Bratishko; Evgeny E Buyko; Lyudmila A Logvinova; Sergey V Romanenko; Andrey I Konstantinov; Sergei V Krivoshchekov; Irina V Perminova; Mikhail V Belousov
Journal:  Polymers (Basel)       Date:  2022-08-12       Impact factor: 4.967

6.  Pesticide residue screening using a novel artificial neural network combined with a bioelectric cellular biosensor.

Authors:  Konstantinos P Ferentinos; Costas P Yialouris; Petros Blouchos; Georgia Moschopoulou; Spyridon Kintzios
Journal:  Biomed Res Int       Date:  2013-07-28       Impact factor: 3.411

7.  Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence.

Authors:  Elmer Ccopa Rivera; Jonathan J Swerdlow; Rodney L Summerscales; Padma P Tadi Uppala; Rubens Maciel Filho; Mabio R C Neto; Hyun J Kwon
Journal:  Sensors (Basel)       Date:  2020-01-23       Impact factor: 3.576

  7 in total

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