This paper deals with the application of inverse concepts to the drying of bodies that undergo changes in their dimensions. Simultaneous estimation is performed of moisture diffusivity, together with the thermal conductivity, heat capacity, density, and phase conversion factor of a drying body, as well as the heat and mass transfer coefficients and the relative humidity of drying air. This was accomplished by using only temperature measurements. A mathematical model of the drying process of shrinking bodies has been developed where the moisture content and temperature fields in the drying body are expressed by a system of two coupled partial differential equations. The shrinkage effect was incorporated through the experimentally obtained changes of the specific volume of the drying body in an experimental convective dryer. The proposed method was applied to the process of drying potatoes. For the estimation of the unknown parameters, the transient readings of a single temperature sensor located in the midplane of the potato slice, exposed to convective drying, have been used. The Levenberg–Marquardt method and a hybrid optimization method of minimization of the least-squares norm are used to solve the present parameter estimation problem. Analyses of the sensitivity coefficients and of the determinant of the information matrix are presented as well.

The moisture adsorption isotherms of pear were determined at 15?C, 30?C and 45?C using the standard static gravimetric method over a range of water activity from 0.112 to 0.920. The experimental data were fitted with isotherm equations recommended in ASAE Standard D245.5. In order to find which equation gives the best results, large number of numerical experiments were performed. After that, several statistical criteria proposed in scientific literature for estimation and selection of the best sorption isotherm equations were used. For each equation and experimental data set, the average performance index was calculated and models were ranked afterwards. After that, some statistical rejection criteria were checked (D?Agostino-Pearson test of normality, single-sample run test and significance and precision of the model parameters). The performed statistical analysis shows that the Guggenheim-Anderson-de Boer (GAB) equation has the highest value of average performance index, but higher correlation between pair of parameters leads to lower precision of estimated parameters.[Projekat Ministarstva nauke Republike Srbije, br. TR 31058]

The moisture adsorption isotherms of quince were determined at four temperatures 15, 30, 45, and 60 C over a range of water activity from 0.110 to 0.920 using the standard static gravimetric method. The experimental data were fitted with generated three parameter sorption isotherm models on Mitrevski et al., and the referent Anderson model known in the scientific and engineering literature as Guggenheim-Anderson-de Boer model. In order to find which models give the best results, large number of numerical experiments was performed. After that, several statistical criteria for estimation and selection of the best sorption isotherm model was used. The performed statistical analysis shows that the generated three parameter model M11 gave the best fit to the sorption data of quince than the referent three parameter Anderson model.

In this study, a power series which can generate different families of new water sorption isotherm models were presented. Experimentally obtained values for equilibrium moisture content of pear for three different temperatures, 15, 30 and 45C, and water activities, from 0.112 to 0.920, as well as literature experimental values for equilibrium moisture content of potato for three different temperatures, 30, 45 and 60C, and water activities, from 0.112 to 0.900, were fitted with the newly generated sorption isotherm models plus the referent Anderson model known in the literature as Guggenheim‐Anderson‐de Boer (GAB) model. In order to find which model gives the best results for approximation of experimental sorption data, several statistical criteria proposed in scientific literature were used. For each model and experimental data set, the average performance index was calculated and models were ranked afterwards. After that, some statistical rejection criteria were checked (D’Agostino‐Pearson test of normality, single‐sample run test, confidence intervals of estimated parameters, significance and precision of the model parameters). The performed statistical analysis shows that the two newly generated three‐parameter models, M32 and M34, give the better fit to the sorption data of pear than the referent three‐parameter Anderson model, while M32 gives the best fit to the sorption data of potato. Practical Applications The sorption isotherms of food materials are of great importance in the food industry and technology, especially for the design and optimization of the drying equipment and in the approach to the prediction of shelf life stability of material. The new generated three‐parameter models, M32 and M34, can be successfully used in practical calculations of the equilibrium moisture content, which is an important parameter in storage conditions of dry food materials. With the incorporation of M32 or M34 in the drying model, more accurate values of transient moisture and temperature profiles on the dried materials will be obtained.

In this study, a thin - layer drying of pear slices as a function of drying conditions were examined. The experimental data set of thin - layer drying kinetics at five drying air temperatures 30, 40, 50, 60 and 70?C, and three drying air velocities 1, 1.5 and 2 m s-1 were obtained on the experimental setup, designed to imitate industrial convective dryer. Five well known thin - layer drying models from scientific literature were used to approximate the experimental data in terms of moisture ratio. In order to find which model gives the best results, numerical experiments were made. For each model and data set, the statistical performance index, (?), and chi-squared, (?2), value were calculated and models were ranked afterwards. The performed statistical analysis shows that the model of Midilli gives the best statistical results. Because the effect of drying air temperature and drying air velocity on the empirical parameters was not included in the base Midilli model, in this study the generalized form of this model was developed. With this model, the drying kinetic data of pear slices can be approximated with high accuracy. The effective moisture diffusivity was determined by using Fick?s second laws. The obtained values of the effective moisture diffusivity, (Deff), during drying ranged between 6.49 x 10-9 and 3.29 x 10-8 m2 s-1, while the values of activation energy (E0) varied between 28.15 to 30.51 kJ mol-1.