Optimization Of Livestock Product Freeze-Drying Process And Study On The Re-Hydration Quality Of Dried Products

The physical, chemical and biological changes during food manufacturing, storage and transportation result in unsatisfactory changes of food color, structure, aroma components and nutrition substances. The choice of the right method of preservation can be the key for a successful operation. Drying is an old method for food’ preservation, however, conventional methods such as hot air drying often make food quality inferior. Freeze-drying is an important drying process based on the sublimation phenomenon which has the following advantages compared to the conventional drying process: the material structure is maintained, moisture is removed at low temperature, product stability during the storage is increase, and the fast transition of the moisturized product to be dehydrated minimizes several degradation reactions. However, the cost of freeze-drying is 4-8 times as that of hot air drying. Especially, the sublimation operation needs 50% of the whole energy. Therefore, it is important to improve heat transfer, to shorten drying time, and thus to reduce vacuum energy consumption by optimizing operation conditions. The optimization is an important tool to maximize the amount of removed water and minimize the time of the freeze drying process with significant impact on the energy consumption and hence in the process costs. But the freeze-drying experiments are time consuming and are usually expensive to be carried out in all possible operating ranges. Because of that, expecting great reduction of experiments considerable increase in the development and use of mathematical models that can predict the behavior of the freeze,drying process satisfactorily is observed. Freeze-drying is a process affected by many factors, of which material thickness, shelf temperature, chamber pressure could be controlled. In this research, the freeze-drying processes of cooked beef slice, yoghourt and quail-eggs were optimized though the use of the statistical models and experimental study. The another objective of this study was to track the changes of the moisture content, frozen layer temperature and sample surface temperature with drying time, and establish the models to predict the dynamic parameters for primary freeze drying of cooked beef slice and yoghourt. Freeze-dried products were re-hydrated by dipping them in water and their rehydration characteristics examined. The contents and results are as follows.1. Development of optimization models during freeze-dryingThe deterministic mathematical models for drying period, productivity and energy consumption during freeze-drying of cooked beef slice were development based on the models originally developed by Lichtfield and Liapis （1979）. The drying period, productivity and energy consumption were calculated when the three main influential parameters （sample thickness, chamber pressure and shelf temperature） under five different levels of the other two. By nonlinear regression analysis of the calculation data, using statistical software SPSS 13.0, the statistical models for the drying period, the productivity and the energy consumption, with the freeze-drying sample thickness, chamber pressure and shelf temperature were also established and the optimal objective values were solved by statistical software LINGO 4. Finally, the freeze-drying process of cooked beef slices and yoghourts was optimized though the use of the statistical models LINGO 4. The results of the freeze drying of cooked beef were that: the minimum energy consumption 19164 KJ·Kg^-1 （H₂O）, the drying period 6.52h, the productivity 172.29 g·m^-2h^-1, with sample thickness 10 mm, chamber pressure 10 Pa, shelf temperature 78℃. The results of the freeze drying of yoghourts were that: the minimum energy consumption 38263 KJ·Kg^-1 （H₂O）, the drying period 14h, the productivity 77.89 g·m^-2h^-1, with sample thickness 10 mm, chamber pressure 10 Pa, shelf temperature 51℃.2. Experimental study on optimization of freeze-drying process of livestock productsThe eutectic and co-melting temperatures of cooked beef slices, yoghourt and quail-eggs were measured and their terminal freezing temperatures were determined. The relationship between the freezing and drying velocities of cooked beef slices, yoghourt and quail-eggs were studied through single factor experiments, and optimal freezing technologies were determined. The relationship between drying velocities and chamber presses, heating board temperatures and sample thickness were also studied through single factor experiments. The relationship between the drying time, productivities, energy consumption and the sample thickness, chamber pressure, of the heating board temperature have been determined through mathematical optimization previous mentioned. At last the optimal combination of the parameters for the freeze-drying technology of cooked beef slices, yoghourt, were determined through experiments. They are as follows: the temperatures of the heating board are 78℃and 52℃, respectively, the chamber pressures are 10Pa, the freezing velocities are -0.33℃/rain and -0.62℃/min, respectively, and material thickness are 10mm. The absolute errors of the drying periods, productivities and energy consumptions between calculated and experimental data for cooked beef slices were low than 0.13h, 3.5g·m^-2h^-1 and 382.63 KJ·Kg^-1 （H²O）, respectively, and for yoghourts were lower than 0.23h, 1.5 g·m^-2h^-1, 278 KJ·Kg^-1（H₂O）, respectively. The relatively errors between calculated and experimental data for cooked beef slices were low than 1.63 %, 1.78% and 1.1%, respectively, and for yoghourt, were low than 2.0%, 4.5% and 1.4%, respectively. It indicates that the optimization models established in the paper are feasible to optimize freeze drying process. The optimal parameters of cooked quail-eggs freeze drying was obtained through single factor experiment. They are as follows: the heating board temperature is 85℃, the chamber pressure is 10Pa, the freezing velocity is-0.77℃/min.3. Prediction and validation of dynamic parameters during freeze dryingThe predictive models were established, according to the kinetic theory of gases and heat and mass transfer principles, for quantifying changes of sublimation moisture c_i, sublimation time t_i, and sample surface temperature T_is with frozen layer temperature Ti. The predictive models during de-sorption were also established for quantifying changes of de-sorption time ti, central temperature in the sample Ti and the temperature on the sample surface T_is with de-sorption moisture ci. The changes of moisture content c_i, T_i and T_is in 6ram cooked beef slice with time during freeze,drying were simulated. Meanwhile, the models were used to predict the changes of c_i, T_i and T_is in 10mm and 4ram samples during freeze-drying. The results showed that the predicted c_i, T_i and T_is with time were nearest to the measured. Therefore, the established models could effectively predict the dynamicparameters for freeze drying of cooked beef slice and concentrated yoghourt.4. Rehydration quality of freeze dried productsFreeze-dried products were re-hydrated by dipping them in water at different temperature and their rehydration characteristics, such as shape, color and taste properties were examined. The samples were found to restore up to 90% of their original moisture content, depending on the type of products and various other factors like the freezing condition. The water uptake happened rapidly during the first 30s and then slowed down with time until it finally stopped altogether. Microstructure and volatility component of freeze drying products were not seriously affected by freezing, while the drying step resulted in an overall structural weakening of the reconstituted products, possibly as a consequence of the mechanical energy required for mixing with water. However, its physical properties were retained and the original strength could be recovered by modulating the amount of water. The freeze-drying process affected survival of the lactic acid bacteria, resulting in a 2-3 log population reduction.