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In this study, three mathematical models (Plank, Pham and numerical model (finite element)) were used to predict the freezing time of potato samples. In order to develop the numerical model, thermophysical properties (density, thermal conductivity and specific heat) were predicted as a function of sample composition and temperature. Convective heat transfer coefficient was also estimated using the inverse problem method and dimensionless numbers. The results showed that the time calculated by the numerical model was the most accurate among three models and in the next step the best model was Pham model. In addition, an excellent agreement was obtained between observed temperature and temperature predicted by the numerical method in different freezing methods. In conclusion, the developed numerical model predicts the freezing temperature of potato samples correctly and can be used to simulate the freezing of suspended food in the air. In addition, the inverse problem method developed to predict convective heat transfer coefficient can be used in different freezing systems in order to choose the best system or optimize the process of food freezing.

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Fried potato products are very popular due to their desired quality properties, taste and texture, but their high fat content has caused concern in society. The use of edible coatings before frying is effective in reducing oil absorption. In this research, the effect of different concentration (0, 0.5 and 1%) of pectin and carboxymethyl cellulose (CMC) gums as a coating agent on oil absorption and quality properties of French Fries was investigated and optimized by the response surface methodology. Result showed that the moisture content of the samples increased as the concentration of pectin and CMC gums increased, but the amount of oil absorption, water loss during frying and the amount of required maximum shearing force for cuting the produced French fries decreased. Colorimetric results showed that, with increasing CMC gum concentration (Up to 1.2%), the brightness (L) and color difference (DE) of the produced French fries increased, but, the use of CMC gum concentrations higher than 1.2% reduced the color parameters of L and DE of the final product. Results showed that using pectin and CMC gums increased the color parameters a and b of the produced French fries. coating potato stripes with 0.69% pectin gum and 1.49% CMC gum are the optimum conditions for coating process of potato strips and at this condition, the quality parameters of the produced French fries are maintained optimally. Application of pectin and CMC gums lead to produce low fat French fries without adverse effect on quality attributes of final product.

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By controlling dehydration and rehydration conditions, optimal reconstitution properties can be achieved. Therefore, mathematical models that describe the kinetics of moisture removal and moisture uptake are important in designing and optimizing that process. In this study, the drying process of pear slices at 5 different temperatures was investigated and the effective diffusion coefficient of the samples was determined. Drying data were also fitted with 9 mathematical models. The hydration process of the dried samples at 50‌°‌C was also fitted with 4 different models. The results showed that the effective diffusion coefficient has an increasing trend with increasing temperature and its temperature dependence can be described by Arrhenius equation. Among the dehydration models, two models (logarithmic and Weibull) were better than other models in predicting changes in sample moisture during drying and the best model for the rehydration process was Peleg model. In the last step, the temperature dependence of the constants of these equations were fitted with Arrhenius and exponential decay models.

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The efficiency of several theoretical models to predict the moisture content of pear slices during drying were evaluated and compared. Pear slices were dried at 5 different temperatures (30-40-50-60-70‌‌^oC) and the moisture diffusivity and convective mass transfer coefficient were estimated. In the next step, mass transfer model was developed by using mathematical solution of Fickchr('39')s second law of diffusion with different numerical and analytical models. The results of the studied models indicated that the both numerical‌ models were substantially more accurate than analytical model in describing the experimental drying curves. However, the best result was obtained with the combined model developed in this study. This model presents the highest coefficient of determination (R²) value (0.999), and the lowest root mean square error (RMSE) value (0.06). The higher accuracy of this model can be attributed to the fact that this model takes into account the term that simulate the convective moisture transport and chooses the appropriate boundary conditions. By applying this model, it is possible to predict moisture variations in pear slices with high accuracy as a function of internal variables (thickness, chemical composition) and external factors (temperature, relative humidity and air velocity).

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Quality losses during blanching can be minimized by adequately selecting the time-temperature schedule. In this study, the blanching process of blackberry fruits at 3 selected temperatures were investigated. The thermophysical properties were estimated based on the chemical composition of the sample. Convective heat transfer coefficient was also estimated using a new novel technique called inverse problem method. In order to determine the best model that can describe the shape of the fruit and predict accurately temperature changes during blanching, three analytical models based on solution of Fourierchr('39')s second law for heat transfer on regular shapes (sphere, 2D rectangle and finite cylinder) and a numerical model based on the real geometry of the sample were developed. The results showed that among the analytical models, the two-dimensional rectangle can better predict temperature changes at the center point of the sample than others. However, the developed numerical model was recognized as the best model due to the highest coefficient of determination (R²>99) and the lowest root mean square error (RMSE=0.37). By applying this model, temperature variations in the fruit can be predicted with high accuracy as a function of internal (thickness, and chemical composition) and external variables (temperature, and water bath velocity).

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Egg contamination by Salmonella enteritidis is one of the most important causes of foodborne gastroenteritis throughout the world and the common method which can be used to inactivate this bacteria is pasteurization. In this study, the pasteurization of intact egg was mathematically modelled using a CFD technique. The results were compared with experimental data and it was found that the model could reasonably forecast the temperature of egg during pasteurization (R²>0.98). The model showed that in order to predict the temperature variation of the slowest heating zone (SHZ) with higher accuracy, it is necessary to to incorporate the influence of natural convection currents induced by the hot eggshell walls in the pasteurization process. Results indicated that the SHZ keeps moving during pasteurization and eventually stays in a region that is about 25% of the egg height from the bottom after 300 s of heating. These results also show that the time required to reduce the Salmonella enteritidis population in cold point of eggs to 5D is approximately 28 minutes. This model could serve as an important tool in better understanding of the pasteurization process, choosing the best process parameters and facilitate process optimization of intact egg pasteurization towards industrial implementation

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In this study, water absorption characteristics of white rice during soaking at 25-65 oC was investigated. In the next step, the efficiency of fundamental and empirical models to predict the moisture content of grain during soaking were evaluated and compared. The fundamental models were developed by using analytical and numerical solutions of Fick’s second law of diffusion based on regular shapes (cube and cylinder) and the real geometry of the white rice, respectively. Five empirical models (Henderson and Pabis model, exponential model, Page model, modified Page model and two-term exponential model) for explaining the soaking behavior of rice were also studied. The results of the studied models indicate that the numerical model were substantially more accurate than analytical model in describing the water absorption curves. The higher accuracy of numerical model can be attributed to the fact that this model selected appropriate shape to represent rice grains in the mathematical model. The average value of the effective water diffusivity at 25-65 oC was estimated to be in the order of 8.83×10-11 m2/s, by minimizing the error between experimental and numerically predicted results. Among the empirical models, the two-term exponential model was better than others in predicting changes in sample moisture during soaking. Overall, although both modeling approaches were able to predict the changes in moisture content of the sample during soaking, the numerical model was found to be more appropriate because it provided a more comprehensive understanding of the underlying physics of the process and the model parameters were directly related to measurable physical quantities. 

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