• Title of article

    Neural network as tool for virgin olive oil elaboration process optimization Original Research Article

  • Author/Authors

    A. Jiménez Marquez، نويسنده , , M.P. Aguilera Herrera، نويسنده , , M. Uceda Ojeda، نويسنده , , G. Beltr?n Maza، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    7
  • From page
    135
  • To page
    141
  • Abstract
    A neural network has been designed in order to optimize the virgin olive oil elaboration process. The qualitative parameters of the fruit: fat and moisture, and the technological variables of process: olive paste temperature, olive paste injection flow to the Decanter, addition of micronized talc as coadyuvant, olive paste dilution degree at the input of the Decanter and oil off-carrier point in the Decanter were used as input. This optimization has been based on the optimal operation of the centrifugal separator, using the data of the loss of fat and moisture in the by-product olive pomace and the loss oil moisture at the exit of the Decanter, as indicators of its operation. The obtained network has been able to predict the fat content on dried matter of the olive pomace and the oil moisture with errors of RMSEP = 0.75% and 0.04%, and a lineal correlation of r = 0.949 and 0.981, respectively.
  • Keywords
    Decanter , Olive oil , Optimization , Neural networks , Elaboration
  • Journal title
    Journal of Food Engineering
  • Serial Year
    2009
  • Journal title
    Journal of Food Engineering
  • Record number

    1168389