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Ethanol quantification in pineapple waste by an electrochemical impedance spectroscopy-based system and artificial neural networks

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Ethanol quantification in pineapple waste by an electrochemical impedance spectroscopy-based system and artificial neural networks

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Conesa Domínguez, C.; Gil Sánchez, L.; Seguí Gil, L.; Fito Maupoey, P.; Laguarda-Miro, N. (2017). Ethanol quantification in pineapple waste by an electrochemical impedance spectroscopy-based system and artificial neural networks. Chemometrics and Intelligent Laboratory Systems. 161:1-7. doi:10.1016/j.chemolab.2016.12.005

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Title: Ethanol quantification in pineapple waste by an electrochemical impedance spectroscopy-based system and artificial neural networks
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Química y Nuclear - Departament d'Enginyeria Química i Nuclear
Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments
Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
Issued date:
Embargo end date: 2019-02-15
Abstract:
[EN] Electrochemical impedance spectroscopy (EIS) technique has been applied to determine the ethanol concentration in pineapple waste samples. To do this, six different concentrations of ethanol were added to the pineapple ...[+]
Subjects: Electrochemical impedance spectroscopy , Ethanol , Pineapple waste , Artificial neural networks
Copyrigths: Reserva de todos los derechos
Source:
Chemometrics and Intelligent Laboratory Systems. (issn: 0169-7439 )
DOI: 10.1016/j.chemolab.2016.12.005
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.chemolab.2016.12.005
Thanks:
Financial support from the European FEDER and the Spanish government (MAT2012-34829-C04-04), the Generalitat Valenciana (PROMETEOII/2014/047) and the FPI-UPV Program funds are gratefully acknowledged.
Type: Artículo

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