• DocumentCode
    190315
  • Title

    Application of electronic tongues in the qualitative and quantitative analysis of beers

  • Author

    Ceto, Xavier ; del Valle, Manel

  • Author_Institution
    Dept. of Chem., Univ. Autonoma de Barcelona, Bellaterra, Spain
  • fYear
    2014
  • fDate
    2-5 Nov. 2014
  • Firstpage
    2143
  • Lastpage
    2146
  • Abstract
    Applicability of electrochemical sensors to the analysis of food and beverages seems established, as also their integration in electronic tongues (ETs). ETs are formed, apart from a proper chemometric data processing tool, by arrays of sensors that chiefly can be of potentiometric nature, or voltammetric. By using the two electrode types in different arrays, qualitative models to identify beer could be generated by using simple pattern recognition like linear discriminant analysis. Furthermore, in order to show also quantitative applications of ETs, beer alcohol content was predicted from the data generated with a potentiometric array employing an artificial neural network model; while in a more complex approach, using a BioET, permitted the resolution and quantitative determination of individual phenolic compounds in ternary mixtures.
  • Keywords
    beverages; electrochemical sensors; electronic tongues; neural nets; pattern recognition; potentiometers; production engineering computing; quality control; BioET; artificial neural network; beer alcohol content; beverages; chemometric data processing tool; electrochemical sensors; electronic tongues; food; linear discriminant analysis; pattern recognition; phenolic compounds; potentiometric array; qualitative analysis; quantitative analysis; sensor arrays; ternary mixtures; Artificial neural networks; Biosensors; Compounds; Electrodes; Sensor arrays; Tongue; Electronic tongue; beer; classification; phenolic compounds; potentiometric sensors; voltammetric sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SENSORS, 2014 IEEE
  • Conference_Location
    Valencia
  • Type

    conf

  • DOI
    10.1109/ICSENS.2014.6985462
  • Filename
    6985462