Experimental validation of new empirical models of the thermal properties of food products for safe shipping

Thumbnail Image
File version
Accepted Manuscript (AM)
Hamid, Hanan H
Mitchell, Mark
Jahangiri, Amirreza
Thiel, David V
Griffith University Author(s)
Primary Supervisor
Other Supervisors
File type(s)

Temperature controlled food transport is essential for human safety and to minimise food waste. The thermal properties of food are important for determining the heat transfer during the transient stages of transportation (door opening during loading and unloading processes). For example, the temperature of most dairy products must be confined to a very narrow range (3–7 °C). If a predefined critical temperature is exceeded, the food is defined as spoiled and unfit for human consumption. An improved empirical model for the thermal conductivity and specific heat capacity of a wide range of food products was derived based on the food composition (moisture, fat, protein, carbohydrate and ash). The models that developed using linear regression analysis were compared with the published measured parameters in addition to previously published theoretical and empirical models. It was found that the maximum variation in the predicated thermal properties leads to less than 0.3 °C temperature change. The correlation coefficient for these models was 0.96. The t-Stat test (P-value >0.99) demonstrated that the model results are an improvement on previous works. The transient heat transfer based on the food composition and the temperature boundary conditions was found for a Camembert cheese (short cylindrical shape) using a multiple dimension finite difference method code. The result was verified using the heat transfer today (HTT) educational software which is based on finite volume method. The core temperature rises from the initial temperature (2.7 °C) to the maximum safe temperature in ambient air (20.24 °C) was predicted to within about 35.4 ± 0.5 min. The simulation results agree very well (+0.2 °C) with the measured temperature data. This improved model impacts on temperature estimation during loading and unloading the trucks and provides a clear direction for temperature control in all refrigerated transport applications.

Journal Title
Heat and Mass Transfer
Conference Title
Book Title
Thesis Type
Degree Program
Publisher link
Patent number
Grant identifier(s)
Rights Statement
Rights Statement
© 2017 Springer Berlin Heidelberg. This is an electronic version of an article published in Heat and Mass Transfer, April 2018, Volume 54, Issue 4, pp 1247–1256. Administration and Policy in Mental Health and Mental Health Services Research is available online at: http://link.springer.com/ with the open URL of your article.
Item Access Status
This publication has been entered into Griffith Research Online as an Advanced Online Version.
Access the data
Related item(s)
Mechanical engineering
Other engineering
Engineering practice and education not elsewhere classified
Persistent link to this record