Discrimination of Honeys by Electronic Tongue and Different Analytical Techniques

Author

Wei, Zhenbo ; Wang, Jun

Author_Institution

Dept. of Agric. Eng., Zhejiang Univ., Hangzhou, China

fYear

2009

fDate

17-19 Oct. 2009

Firstpage

1

Lastpage

5

Abstract

A study aimed at classification of honey samples from different floral origins by electronic tongue. The analytical data of 196 samples from different floral (eight) origins have been processed by Principal Component Analysis (PCA), Discriminant function analysis (DFA) and BP artificial neural network (BP-ANN). Using the electronic signal of sensors as input and floral origins as output, a twelve-hidden-layer BP Neural Network model was developed. It is shown that 100% of the training set and more than 98.4% of the testing set were classified by BP-ANN (network topology 7-12-12).

Keywords

backpropagation; electronic tongues; neural nets; pattern classification; principal component analysis; BP artificial neural network; PCA; discriminant function analysis; electronic tongue; honey sample classification; principal component analysis; Agricultural engineering; Artificial neural networks; Chemical sensors; Data analysis; Doped fiber amplifiers; Electrodes; Mass spectroscopy; Principal component analysis; Sensor arrays; Tongue;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-4129-7

Electronic_ISBN

978-1-4244-4131-0

Type

conf

DOI

10.1109/CISP.2009.5300908

Filename

5300908