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Because the quality and shelf life of a frozen food greatly depend on the freezing processing time, its accurate estimation is highly relevant. In addition, the estimation of the freezing time is an enormous task due to the difficulty in developing a robust and accurate mathematical model and the need for appropriate thermophysical properties for an immense variety of foods. The objective of this study was to explore, via simulation, the capability of an inverse method to simultaneously determine the thermal conductivity ( k(T) ) and apparent volumetric specific heat ( C(T) ) of foods in the freezing temperature range (i.e., initial freezing point to −40 °C). Experiments and validation experiments were designed with the purpose of a systematic analysis and assessment of the potential capability of an inverse procedure for simultaneously determining the thermophysical properties of foods in the freezing temperature range. Assuming a one-dimensional freezing process and known thermophysical properties of the food material, temperatures were generated at different locations of the food sample by numerically solving the partial differential equation for heat conduction. The inverse method was designed to obtain the unknown parameters for the equations of the thermophysical properties C(T) and k(T) . The ability of the inverse method to simultaneously determine C(T) and k(T) in the freezing temperature range was investigated, and it was determined that the technique is accurate, rapid and robust to typical measurement errors. This fact was supported by a sensitivity coefficient analysis, which compared the direct-adjustment to the inverse method. [ABSTRACT FROM AUTHOR]

Abstract: A common assumption in heat and mass transfer modelling of processes such as chilling and freezing is to consider water activity (a w) being constant or equal to 1. However, this constant value assumption does not represent the actual variation of water activity during the process. In the present work, the effect of different values of water activity on the freezing/thawing times and weight loss prediction of cured cooked pork and beef, and chicken meat was studied. Experimental sorption data of these meats were previously obtained, and the results were incorporated to the developed computer simulation program. An explicit finite difference scheme, which incorporates the mass transfer and variation of a w was used in the analysis. Experimental data on freezing/thawing times and weight loss were also obtained to verify and compare with the model predictions. The high water activity range (a w =0.85, 0.9, 0.95 and 1) was analysed. In general and for all the meats considered, the lowest error was obtained when variable a w was used. Results indicated that if data on the sorption isotherm are not available a constant water activity value of 0.875 could be used instead to predict the freezing time and weight loss for cooked cured pork and beef, and a value of 0.9 for chicken meat; while for the modelling of the thawing process a w values of 0.95 and 1 are recommended for cured cooked pork and beef and chicken meat, respectively. Hence, water activity is an important factor and should be incorporated in the modelling in order to improve the accuracy of the predictions. [Copyright &y& Elsevier]

The Galerkin finite element numerical model was established to analyse the freezing and thawing process for frozen food processing, to predict the freezing time for any shape foods at different freezing conditions, and to investigate the effect of freezing parameters on the freezing process. It was proved that the method is effective to solve the Stefan problem for its accuracy, stability and convergence. The results obtained show that the food shape and size, freezing air temperature and freezing air velocity are the important factors affecting freezing rate, and the freezing parameters should be matched with the thermal conductivity of food. Based on the analysis, the control values of the final central temperature for three typical shapes were recommended. [Copyright &y& Elsevier]

Protein is not stable under freezing conditions, which may lead to changes in protein aggregates. In this study, liquid whole egg samples were frozen and thawed. The structural changes in the whole egg aggregates were then analyzed. After analyzing samples using tunable resistance pulse sensing, it was found that the number of protein aggregate samples increased nearly six-fold after freezing and thawing. The addition of sucrose reduced the enhancement of particle number. The surface characteristics of whole egg protein aggregates varied during the freezing process. By adding sucrose to the whole egg sample, the variation in aggregate surface characteristics was weakened. The same samples were also investigated using a small-angle X-ray scattering device. The results showed that the inner structure of whole egg protein aggregates became less packed during the freezing process. However, changes in protein aggregates caused by freezing were prevented by the addition of sucrose. In conclusion, freezing unfolded whole egg proteins and reduced protein solubility, which further increased the number of protein aggregates and changed the structure of the aggregates. Sucrose could be a cryoprotectant and inhibit the influence of freezing on whole egg protein aggregates. • Aggregate formation upon freezing of the whole egg solution was investigated. • It found that the particle number concentration increased during the freezing process. • The aggregates became less packed during the freezing process. • It was confirmed that the addition of sucrose reduced the degree of structural change of aggregate during freezing. [ABSTRACT FROM AUTHOR]