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Vol. 145, No. 10, September 2012, pp. 65-76

 

Bullet

 

Authentication of Indian Wines Using Voltammetric Electronic Tongue Coupled with Artificial Neural Networks
 
1 Hepsiba K. ANGA, 1 P. C. PANCHARIYA and 2 A. L. SHARMA

1 Digital Systems Group, CSIR-Central Electronics Engineering Research Institute, Pilani-333031, India

Tel.: +91-1596-252267, fax:+91-1596-242294

2School of Instrumentation, Devi Ahilya University

Takshila Campus, Khandwa Road, Indore-452001, India

E-mail: pcp@ceeri.ernet.in

 

 

Received: 9 October 2012   /Accepted: 29 October 2012   /Published: 31 October 2012

Digital Sensors and Sensor Sysstems

 

Abstract: An electronic tongue based on voltammetry (VE-tongue) was developed and its application towards discriminating the Indian wines based on their non volatile chemical profiles is reported in this paper. Eight types of Indian wine were analyzed and classified using the E-tongue by principal component analysis (PCA) and Artificial neural networks (ANN) respectively. A new statistical features based data reduction methodology of voltammetric response signals for classification of Indian wines has been proposed which has reduced the original data size by 99.02 %. An ANN based classifier was trained with the reduced features from the original data for classification of Indian wines. A classification success rate of 97.5 % was achieved for all the eight brands of Indian wines. The results show that the VE-tongue can discriminate Indian wines into natural and useful groupings and may become an important tool for standardization of wine quality.

 

Keywords: Indian wine, Electronic tongue, Feature extraction, Principal component analysis (PCA), Artificial neural networks (ANN)

 

 

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