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)

Abstract

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
Volume31
Issue number2
Publication statusPublished - Feb 1997

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Thermal Conductivity
Porosity
thermal conductivity
Vegetables
porosity
raisins
Pyrus
Fruit
vegetables
Vitis
water content
pears
Temperature
fruits
prediction
Water
temperature
Malus
Solanum tuberosum
corn starch

ASJC Scopus subject areas

  • Food Science

Cite this

An improved thermal conductivity prediction model for fruits and vegetables as a function of temperature, water content and porosity. / Rahman, M. S.; Chen, X. D.; Perera, C. O.

In: Journal of Food Engineering, Vol. 31, No. 2, 02.1997, p. 163-170.

Research output: Contribution to journalArticle

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