Thermal diffusivity is an important transport property needed in modeling and computations of transient heat transfer in basic food processing operations. In addition, the prediction of nutritional and microbial changes occurring in food during thermal processing requires knowledge of thermal diffusivity of foods. The objectives of this study were to develop a new nonisothermal and nonlinear determination method of thermal diffusivity and to measure the thermal diffusivity of low-moisture foods using that new method. Thermal diffusivities of 5 kinds of low-moisture foods (almond meal, corn meal, wheat flour, chocolate fudge, and peanut butter) were estimated using an inverse technique. Samples were canned and heated at the surface in a water bath at about 70 °C. The 1-dimensional transient heat conduction problem for radial coordinates was solved with a finite-difference model. The thermal diffusivity of each of the 5 samples was determined by the ordinary least squares and sequential estimation methods, respectively. Predicted and observed temperature matched well, with maximum residuals of 0.9 °C. The thermal diffusivity values of the samples ranged from 9.8 × 10-8 to 1.3 × 10-7 m2 /s. The advantages of this method are that the device and the estimation method are simple, inexpensive, rapid, and can handle large spatial temperature gradients, such as those experienced during heating of low-moisture foods. The results obtained in this study will be useful in the design of equipment and in calculations for the thermal processing of low-moisture foods.
Keywords: finite-difference method; inverse problem; low-moisture food; parameter estimation; thermal diffusivity.
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