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Sensors 2015, 15(7), 17767-17785; doi:10.3390/s150717767

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

1
School of Electrical Engineering, Henan University of Technology, Zhengzhou 450007, China
2
School of Food Science and Engineering, Henan University of Technology, Zhengzhou 450007, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 25 May 2015 / Revised: 9 July 2015 / Accepted: 17 July 2015 / Published: 22 July 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [1252 KB, uploaded 22 July 2015]   |  

Abstract

In this study, an application of a voltammetric electronic tongue for discrimination and prediction of different varieties of rice was investigated. Different pretreatment methods were selected, which were subsequently used for the discrimination of different varieties of rice and prediction of unknown rice samples. To this aim, a voltammetric array of sensors based on metallic electrodes was used as the sensing part. The different samples were analyzed by cyclic voltammetry with two sample-pretreatment methods. Discriminant Factorial Analysis was used to visualize the different categories of rice samples; however, radial basis function (RBF) artificial neural network with leave-one-out cross-validation method was employed for prediction modeling. The collected signal data were first compressed employing fast Fourier transform (FFT) and then significant features were extracted from the voltammetric signals. The experimental results indicated that the sample solutions obtained by the non-crushed pretreatment method could efficiently meet the effect of discrimination and recognition. The satisfactory prediction results of voltammetric electronic tongue based on RBF artificial neural network were obtained with less than five-fold dilution of the sample solution. The main objective of this study was to develop primary research on the application of an electronic tongue system for the discrimination and prediction of solid foods and provide an objective assessment tool for the food industry. View Full-Text
Keywords: rice; discrimination; variety prediction; voltammetric electronic tongue; cyclic voltammetry; fast Fourier transform; Discriminant Factorial Analysis; radial basis function neural network rice; discrimination; variety prediction; voltammetric electronic tongue; cyclic voltammetry; fast Fourier transform; Discriminant Factorial Analysis; radial basis function neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, L.; Niu, Q.; Hui, Y.; Jin, H. Discrimination of Rice with Different Pretreatment Methods by Using a Voltammetric Electronic Tongue. Sensors 2015, 15, 17767-17785.

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