Title :
Neural network based electronic nose for apple ripeness determination
Author :
Hines, E.L. ; Llobet, E. ; Gardner, J.W.
Author_Institution :
Sch. of Eng., Warwick Univ., Coventry, UK
fDate :
5/13/1999 12:00:00 AM
Abstract :
It is possible to non-destructively determine apple ripeness using a simple electronic nose. The instrument employs tin oxide resistive gas sensors and neural networks (fuzzy ARTMAP, LVQ and MLP) to classify the samples into three states of ripeness with 100% accuracy. Fuzzy ARTMAP was found to be the best classifier in the presence of simulated Gaussian noise
Keywords :
ART neural nets; Gaussian noise; gas sensors; multilayer perceptrons; LVQ; MLP; apple ripeness determination; classifier; fuzzy ARTMAP; neural network based electronic nose; resistive gas sensors; simulated Gaussian noise;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19990547
