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Analysis of Phenolic Content in Grape Seeds and Skins by Means of a Bio-Electronic Tongue

A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase combined with electron medi...

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Detalles Bibliográficos
Autores principales: Garcia-Cabezon, Cristina, Gobbi Teixeira, Guilherme, Dias, Luís Guimaraes, Salvo-Comino, Coral, García-Hernandez, Celia, Rodriguez-Mendez, Maria Luz, Martin-Pedrosa, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435477/
https://www.ncbi.nlm.nih.gov/pubmed/32727151
http://dx.doi.org/10.3390/s20154176
Descripción
Sumario:A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase combined with electron mediators. The presence of the phenoloxydase promotes the selectivity and specificity towards phenols. The results of multivariate analysis allowed discriminating seeds and skins according to their polyphenolic content. Partial least squares (PLS) has been used to establish regression models with parameters related to phenolic content measured by spectroscopic methods i.e., total poliphenol content (TPC) and Folin–Ciocalteu (FC) indexes. It has been shown that electronic tongue can be successfully used to predict parameters of interest with high correlation coefficients (higher than 0.99 in both calibration and prediction) and low residual errors. These values can even be improved using genetic algorithms for multivalent analysis. In this way, a fast and simple tool is available for the evaluation of these values. This advantage may be due to the fact that the electrochemical signals are directly related to the phenolic content.