A comparison between an electronic nose and human olfaction in a selected case study

Author

Di Natale, C. ; Macagnano, A. ; Paolesse, R. ; Tarizzo, E. ; D´Amico, A. ; Davide, F. ; Boschi, T. ; Faccio, M. ; Ferri, G. ; Sinesio, F. ; Bucarelli, F.M. ; Moneta, E. ; Quaglia, G.B.

Author_Institution

Dept. of Electron. Eng., Rome Univ., Italy

Volume

2

fYear

1997

fDate

16-19 Jun 1997

Firstpage

1335

Abstract

An electronic nose is now becoming available as a commercial product. Nevertheless its performances are not fully understood and interpreted. Also the differences between electronic noses and the human olfaction have not yet been sufficiently studied. This is an important issue in many industrial sectors, such as food analysis. In this paper a comparison between the performances of an electronic nose and a panel of human tasters is presented in a selected case (tomato paste). An extensive set of tools for data analysis was available. A number of chemometrics based methods (principal component analysis and cluster analysis) and neural networks (feedforward backpropagation trained networks, self organizing maps, adaptive resonance theory based networks) have been utilized to analyze electronic nose data in order to extract the relevant information. The electronic nose and the human panel show strong similarities but the former displays a more concise classification capability for the data

Keywords

ART neural nets; backpropagation; biology computing; chemical engineering computing; chemical sensors; chemioception; feedforward neural nets; food processing industry; pattern classification; self-organising feature maps; adaptive resonance theory based networks; chemometrics based methods; classification capability; cluster analysis; commercial product; data analysis; electronic nose; feedforward backpropagation trained networks; food analysis; human olfaction; human tasters panel; industrial sectors; neural networks; performances; principal component analysis; self organizing maps; tomato paste; Backpropagation; Data analysis; Electronic noses; Feedforward neural networks; Food industry; Humans; Information analysis; Neural networks; Principal component analysis; Self organizing feature maps;

fLanguage

English

Publisher

ieee

Conference_Titel

Solid State Sensors and Actuators, 1997. TRANSDUCERS '97 Chicago., 1997 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

0-7803-3829-4

Type

conf

DOI

10.1109/SENSOR.1997.635483

Filename

635483