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Maintaining the nutritional quality and preserving pomegranate seeds is a major challange due to the fast degradation of the texture, color and overall quality of pomegranate seeds. In order to investigate the freezing of coated pomegranate seeds with chitosan and determine its quality during freezing storage, an experiment was conducted, in a factorial arrangement in a completely randomized design with three replications. Factors were: chitosan at three levels (0, 1 and 2%), freezing temperature at two levels (-14 ° -24 ° C) and time at 5 different storage times (14 days, 30 days, 60 days, 90 days, and 120 days). The highest tissue firmness was observed for 14 days of storage under both chitosan concentrations. Interaction of different levels of chitosan coating and time had an increasing effect on the color component changes, so that the most color changes in the brightness (L*), redness (a*), and yellowness (b*) was related to the use of chitosan coating 2%, were maintained at 60 days. The highest total soluble solids were related to 1% chitosan under 4 months of storage at -14°C. Maximum total acidity (1.36 mg / L) was also attributed to coated pomegranate seeds during 120 days of storage under both freezing temperatures of -14°C and -24°C. The results of mean compares showed that the total phenol stability under freezing temperature was higher at -14°C and after 120 days of storage, more phenol content was observed in the seeds in -24^° C. The overall results indicated a positive effect of chitosan on maintaining the quality of pomegranate seeds during freezing, and the freezing temperature of -24^° C with decreasing color changes during storage, played an important role in reducing metabolic activity and reducing anthocyanin degradation and was effective in maintaining fruit quality.
 

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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.