Publication: Electronic tongue system based on non-specific metal oxides/carbon nanotubes electronical sensors for orange juice classification
Issued Date
2020-01-01
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01252526
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2-s2.0-85090645031
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Mahidol University
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SCOPUS
Bibliographic Citation
Chiang Mai Journal of Science. Vol.47, No.4 Special Issue 2 (2020), 776-785
Suggested Citation
Arthit Jityen, Rawat Jaisuthi, Tanakorn Osotchan Electronic tongue system based on non-specific metal oxides/carbon nanotubes electronical sensors for orange juice classification. Chiang Mai Journal of Science. Vol.47, No.4 Special Issue 2 (2020), 776-785. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/58996
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Title
Electronic tongue system based on non-specific metal oxides/carbon nanotubes electronical sensors for orange juice classification
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Abstract
© 2020, Chiang Mai University. All rights reserved. Various metal oxide (MO) powders have been explored for electrochemical sensor as liquid or gas phase sensor. These materials can show ideal or near-ideal Nernstian responses due to their high conductivity, good chemical stability, and most importantly their superior biocompatibility. In this work, various MOs were used as non-specific sensor array for electronic tongue system. To fabricate the sensor, carbon nanotube (CNT) was mixed with several MO powders consisting of zinc oxide, cobalt oxide, copper oxide, iron oxide and copper iron oxide powders with the ratio of 1:1 by weight. These sensor arrays were used as array of working electrode for cyclic voltammetry (CV) measurement in electronic tongue system. To investigate the classification ability, the five different species of orange juice including Shogun, Tangerine, Valencia, Sainumpeung and Mandarin were used to perform the measurement. The 0.1M of NaOH, as electrolyzed solution, was added to enhance electrical conductivity with the ratio of 1:1 by volume. The CV signals were performed the preprocessing and extracted main feature by using wavelet analysis. In order to distinguish different types of orange juice, the extracted signals were classified by using principal component analysis. The result showed that these CNT electrodes modifying with MOs can be utilized to the electronic tongue application for orange juice classification with high stability.