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Sensors 2011, 11(6), 6435-6453; doi:10.3390/s110606435

An Electronic Nose for Reliable Measurement and Correct Classification of Beverages

1
Institute of Microengineering and Nanotechnology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi Selangor, Malaysia
2
Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi Selangor, Malaysia
*
Author to whom correspondence should be addressed.
Received: 29 April 2011 / Revised: 29 May 2011 / Accepted: 16 June 2011 / Published: 17 June 2011
(This article belongs to the Special Issue Bioinspired Sensor Systems)

Abstract

This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results.
Keywords: electronic nose design; beverage classification; principal component analysis; multi layer perception electronic nose design; beverage classification; principal component analysis; multi layer perception
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Mamat, M.; Samad, S.A.; Hannan, M.A. An Electronic Nose for Reliable Measurement and Correct Classification of Beverages. Sensors 2011, 11, 6435-6453.

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