An improved thermal conductivity prediction model for fruits and vegetables as a function of temperature, water content and porosity

M. S. Rahman, X. D. Chen, C. O. Perera

Research output: Contribution to journalArticle

37 Citations (Scopus)


An improved general thermal conductivity prediction model has been developed for fruits and vegetables as a function of water content, porosity and temperature. Thermal conductivity values of apple, pear, corn starch, raisin and potato were used to develop the model using 164 data points obtained from the literature. Raisin has the maximum mean percent deviation of 15.1% (standard deviation 10.1) and pear gave minimum mean percent deviation of 6.8% (standard deviation 7.3). The errors for predicting the thermal conductivity using this improved model for fruits and vegetables are therefore within the range of 6.8-15.1%, which is acceptable for general engineering practice.

Original languageEnglish
Pages (from-to)163-170
Number of pages8
JournalJournal of Food Engineering
Issue number2
Publication statusPublished - Feb 1997


ASJC Scopus subject areas

  • Food Science

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