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Sensors 2016, 16(10), 1745;

Chocolate Classification by an Electronic Nose with Pressure Controlled Generated Stimulation

Bioelectronics Section, Department of Electrical Engineering, CINVESTAV, Mexico City 07360, Mexico
Author to whom correspondence should be addressed.
Academic Editors: Takeshi Onodera and Kiyoshi Toko
Received: 30 August 2016 / Revised: 4 October 2016 / Accepted: 13 October 2016 / Published: 20 October 2016
(This article belongs to the Special Issue Olfactory and Gustatory Sensors)
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In this work, we will analyze the response of a Metal Oxide Gas Sensor (MOGS) array to a flow controlled stimulus generated in a pressure controlled canister produced by a homemade olfactometer to build an E-nose. The built E-nose is capable of chocolate identification between the 26 analyzed chocolate bar samples and four features recognition (chocolate type, extra ingredient, sweetener and expiration date status). The data analysis tools used were Principal Components Analysis (PCA) and Artificial Neural Networks (ANNs). The chocolate identification E-nose average classification rate was of 81.3% with 0.99 accuracy (Acc), 0.86 precision (Prc), 0.84 sensitivity (Sen) and 0.99 specificity (Spe) for test. The chocolate feature recognition E-nose gives a classification rate of 85.36% with 0.96 Acc, 0.86 Prc, 0.85 Sen and 0.96 Spe. In addition, a preliminary sample aging analysis was made. The results prove the pressure controlled generated stimulus is reliable for this type of studies. View Full-Text
Keywords: E-noses; olfactometer; metal oxide gas sensors E-noses; olfactometer; metal oxide gas sensors

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Valdez, L.F.; Gutiérrez, J.M. Chocolate Classification by an Electronic Nose with Pressure Controlled Generated Stimulation. Sensors 2016, 16, 1745.

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