An inverse heat conduction problem (IHCP) approached was used to model heat transfer for conduction-canned food with headspace. A one dimensional heat conduction model was solved numerically for the heat flux at the surface using internal temperature history measurements at 1 cm below the surface of the model food (8% Bentonite suspension). The IHCP solution was performed using sequential function specification method with r=4. The estimated heat flux was then used to solve the direct problem for the temperature profile in the axial direction including at the sensor position. The results showed that the estimated heat flux is very accurate due to the excellent agreement between the measured and calculated temperature at the sensor position in addition to the low value of the mean squares of the error. The results reveal that the cold spot is located at 59% of the model food height from the bottom of the can for the three levels of the headspace investigated (10%, 14% and 20%). The implication of this result is that the cold spot could be above or below the geometric center depending on the size of the headspace.
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