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Integrated analysis of chilling processes in food industry

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F08%3APU76828" target="_blank" >RIV/00216305:26510/08:PU76828 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Integrated analysis of chilling processes in food industry

  • Original language description

    Food related processes are usually difficult to measure as e.g. meat parameters varies significantly. However, cost analysis of such processes is very important because of market competitiveness. A classical quantitative (analytical and/or statistical) analysis is therefore not appropriate for some ill defined and/or very complex food engineering problems. The paper presents a model based on the following parameters: .. Type of Chilling equipment .. Temperature of air in chamber/tunnel .. Air velocity in chamber/tunnel .. Time in chamber/tunnel .. Chilling temperature .. Chilling air velocity .. Time of chilling .. Meat sort .. Mean weight side .. Quality grade .. Weight loss A fuzzy model will utilize data which are to a certain level inconsistent. Tominimize an information loss of valuable knowledge, conventional pre-processing (usually statistical analysis) of this knowledge is eliminated.

  • Czech name

    Integrated analysis of chilling processes in food industry

  • Czech description

    Food related processes are usually difficult to measure as e.g. meat parameters varies significantly. However, cost analysis of such processes is very important because of market competitiveness. A classical quantitative (analytical and/or statistical) analysis is therefore not appropriate for some ill defined and/or very complex food engineering problems. The paper presents a model based on the following parameters: .. Type of Chilling equipment .. Temperature of air in chamber/tunnel .. Air velocity in chamber/tunnel .. Time in chamber/tunnel .. Chilling temperature .. Chilling air velocity .. Time of chilling .. Meat sort .. Mean weight side .. Quality grade .. Weight loss A fuzzy model will utilize data which are to a certain level inconsistent. Tominimize an information loss of valuable knowledge, conventional pre-processing (usually statistical analysis) of this knowledge is eliminated.

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    AH - Economics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2008

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    CHISA 2008

  • ISBN

    978-80-02-02052-3

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

  • Publisher name

    Process Engineering Publisher

  • Place of publication

    Praha

  • Event location

    Praha

  • Event date

    Aug 24, 2008

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article