• DocumentCode
    1139953
  • Title

    Coffee analysis with an electronic nose

  • Author

    Pardo, Matteo ; Sberveglieri, Giorgio

  • Author_Institution
    Dept. of Chem. & Phys., Univ. of Brescia, Italy
  • Volume
    51
  • Issue
    6
  • fYear
    2002
  • fDate
    12/1/2002 12:00:00 AM
  • Firstpage
    1334
  • Lastpage
    1339
  • Abstract
    We present the Pico-1 electronic nose based on thin-film semiconductor sensors and an application to the analysis of two groups of seven coffees each. Cups of coffee were also analyzed by two panels of trained judges who assessed quantitative descriptors and a global index (called Hedonic Index, HI) characterizing the sensorial appeal of the coffee. Two tasks are performed by Pico-1. First, for each group, we performed the classification of the seven different coffee types using principal component analysis and multilayer perceptrons for the data analysis. Classification rates were above 90%. Secondly, the panel test descriptors were predicted starting from the measurements performed with Pico-1. The standard deviations for the prediction of the HI are comparable to the uncertainty of the HI itself (0.2 on a 1 to 9 scale for one group of coffees).
  • Keywords
    food processing industry; gas sensors; multilayer perceptrons; pattern classification; principal component analysis; semiconductor devices; thin film devices; PCA; Pico-1 electronic nose; SnO2; classification rates; coffee analysis; data analysis; gas sensors; multilayer perceptrons; principal component analysis; thin-film semiconductor sensors; Biological materials; Chemical sensors; Crystalline materials; Data analysis; Electronic noses; Multilayer perceptrons; Organic materials; Semiconductor thin films; Sensor arrays; Thin film sensors;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/TIM.2002.808038
  • Filename
    1177933