Research Commons
      • Browse 
        • Communities & Collections
        • Titles
        • Authors
        • By Issue Date
        • Subjects
        • Types
        • Series
      • Help 
        • About
        • Collection Policy
        • OA Mandate Guidelines
        • Guidelines FAQ
        • Contact Us
      • My Account 
        • Sign In
        • Register
      View Item 
      •   Research Commons
      • University of Waikato Research
      • Science and Engineering
      • Science and Engineering Papers
      • View Item
      •   Research Commons
      • University of Waikato Research
      • Science and Engineering
      • Science and Engineering Papers
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Effective thermal conductivity prediction of foods using composition and temperature data

      Carson, James K.; Wang, Jianfeng; North, Mike F.; Cleland, Donald J.
      Thumbnail
      Files
      Carson wang et al JFE accepted manuscript.pdf
      Accepted version, 1.158Mb
      DOI
       10.1016/j.jfoodeng.2015.12.006
      Find in your library  
      Citation
      Export citation
      Carson, J. K., Wang, J., North, M. F., & Cleland, D. J. (2016). Effective thermal conductivity prediction of foods using composition and temperature data. Journal of Food Engineering, 175, 65–73. https://doi.org/10.1016/j.jfoodeng.2015.12.006
      Permanent Research Commons link: https://hdl.handle.net/10289/13283
      Abstract
      Thermal conductivity data are important for food process modelling and design. Where reliable thermal conductivity data are not available, they need to be predicted. The most accurate ‘first approximation’ methodology for predicting the isotropic thermal conductivity of foods based only on data for composition, initial freezing temperature and temperature dependent thermal conductivity of the major food components was sought. A key feature of the methodology was that no experimental measurements were to be required. A multi-step prediction procedure employing the Parallel, Levy and Effective Medium Theory models sequentially for the components other than ice and air, ice and then air respectively is recommended. It was found to provide the most accurate predictions over the range of foods considered (both frozen and unfrozen, porous and non-porous). The Co-Continuous model applied in a single step also provided prediction accuracy within ±20% (on average), except for the porous frozen foods considered. For greater accuracy more rigorous modelling approaches based on knowledge of the foods structure would be required.
      Date
      2016
      Type
      Journal Article
      Publisher
      Elsevier
      Rights
      This is an author’s accepted version of an article published in the journal: Journal of Food Engineering. © 2016 Elsevier.
      Collections
      • Science and Engineering Papers [3084]
      Show full item record  

      Usage

      Downloads, last 12 months
      139
       
       
       

      Usage Statistics

      For this itemFor all of Research Commons

      The University of Waikato - Te Whare Wānanga o WaikatoFeedback and RequestsCopyright and Legal Statement