TY - JOUR
T1 - An improved thermal conductivity prediction model for fruits and vegetables as a function of temperature, water content and porosity
AU - Rahman, M. S.
AU - Chen, X. D.
AU - Perera, C. O.
PY - 1997/2
Y1 - 1997/2
N2 - 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.
AB - 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.
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U2 - 10.1016/S0260-8774(96)00060-X
DO - 10.1016/S0260-8774(96)00060-X
M3 - Article
AN - SCOPUS:0031070958
SN - 0260-8774
VL - 31
SP - 163
EP - 170
JO - Journal of Food Engineering
JF - Journal of Food Engineering
IS - 2
ER -