• DocumentCode
    1523452
  • 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
  • Volume
    35
  • Issue
    10
  • fYear
    1999
  • fDate
    5/13/1999 12:00:00 AM
  • Firstpage
    821
  • Lastpage
    823
  • 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;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19990547
  • Filename
    771441
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1523452