نوع مقاله : مقاله پژوهشی
1 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه محقق اردبیلی
2 دانشگاه محقق اردبیلی، اردبیل، ایران
عنوان مقاله [English]
Structural heterogeneity of fruits and vegetables makes it difficult to understand the associated physicochemical changes that occur during drying. Due to its heterogeneous structure, food is one of the most complex types of metamorphic materials. The porosity and hygroscopic nature of fruits and vegetables increase their shrinkage during the drying process, which is a physical process commonly observed during drying. Shrinkage has a significant effect on the mechanical and textural properties of fruits and vegetables. Most importantly, shrinkage is an important factor that has a great impact on drought rate and drought kinetics. Because of these factors, food researchers emphasize that shrinkage should not be ignored when predicting volume and heat transfer during drying. The shrinkage model is better suited to the experimental data during drying than the non-shrinkage model. Food shrinkage depends on several factors such as material properties, mechanical properties, and process status. Knowledge of porosity during drying can also help to accurately predict the transfer phenomenon and quality characteristics. Some researchers have used mathematical equations to predict the porosity of food as a function of moisture content, which can be classified into two categories: (1) theoretical models based on understanding of fundamental physics and the mechanisms involved in pore formation have been established, and (2) experimental models have been developed using parameters in experimental data. Many previous studies on experimental or laboratory shrinkage have predicted porosity as linear, quadratic, and exponential equations. On the other hand, theoretical modeling can provide a better understanding of the shrinkage that occurs simultaneously with heat and volume transfer during drying. However, limited efforts have been made in the theoretical modeling of the contraction of fruits and vegetables, due to the complexity of creating physics-based models. The first porosity model was introduced in the 1950s. Kilpatrick and colleagues proposed a simple model considering the volumetric contraction of fruits and vegetables during drying. Many models in previous research have considered shrinkage to be ideal, during which the reduction of the geometric volume of the product is exactly equal to that of water lost. But in fact, this linear relationship between the decrease in physical volume and the volume of water lost during the drying period is not observed. Cell loss and shrinkage of food tissues occur during the drying process of food. There is a fine distinction between shrinkage and loss, in that shrinkage refers to a reduction in food sample size, but loss indicates irreversible breakdown of cellular and tissue structure. Structural changes at the cellular level occur due to the transfer phenomenon during the dry period. As mentioned earlier, porosity and shrinkage during drying affect the transfer process as well as other quality characteristics. Accurate prediction of porosity and shrinkage helps design an advanced drying system to ensure quality products.
Careful examination of theoretical and experimental models of porosity indicates the need for a simple model that can compensate for some of the limitations of theoretical models and use them for drying products and processes. Therefore, the aim of this study is to create a real contraction model with minimal use of experimental coefficients. A simple model considering heat gradient and humidity, glass transfer temperature, and drying time can be a potential way to predict structural changes during drying. Therefore, in this study, a new approach to contraction velocity is introduced. Therefore, paying attention to these parameters in shrinkage rate, process parameters, and material properties are considered in predicting metamorphism during drying. The physical meaning of shrinkage velocity is as follows: The velocity of the outer surface of the specimen during drying.
Apples were selected as the study sample in this study. Apples have high initial porosity and change of porosity during the drying period is very important. Therefore, it is expected that the experimental measurement of porosity changes and confirmation of the proposed model for this sample will be better. Kohn rose apples were prepared from a local supermarket and stored in a refrigerator at 2 ° C. The apples were selected from a box to have the same degree of ripeness. The treatment step was calculated using a liquid refractometer (BPTR-100 V3.0). The average ripeness of apples was 14.20 ± 0.20. The initial moisture content of fresh apples was calculated to be 77 ± 0.50% wb. 10 samples were used to measure the moisture content. Apples were removed from the refrigerator and washed at room temperature for one and a half hours. The skin of the samples was taken and cut into round pieces 10 mm thick and 40 mm in diameter. A hot air dryer with a fan was used. The drying temperature varied from 50 to 65 ° C and airspeed was set at 1 m / s. Particle density was measured using a gas (helium) pycnometer. The density of the mass was measured from the volume of the sample and the weight of the sample so that the sample was first coated with organic solvents to cover the open pores because there were numerous open pores that were large enough to be glass beads. They could have entered them. The density of the same sample was calculated before and after coating. The density of the glass beads was calculated from the weight of the required glass beads. The simulation was performed using COMSOL Multiphysics 18.104.22.1680 Win / Linux. This software facilitates all stages of the modeling process including geometric structure definition, lattice, physical dimensioning, solving, and displaying results. COMSOL Multiphysics can manage variable properties that are a function of independent variables. A two-dimensional symmetry mode is also provided to facilitate the simulation process. There will be a small amount of 3D effects that can be ignored, and 3D consideration can complicate matters.
The physical quality of dried food depends on the degree of metamorphosis during drying. Shrinkage also has a significant effect on mechanical and textural properties as well as drying speed and kinetics. Accurate prediction of shrinkage can lead to better food quality and optimal drying process design. Food shrinkage depends on several factors including material properties, microstructure, mechanical properties, and process conditions. Experimental models can be created quickly that have a high impact. However, they do not show physical changes in the process. Physics-based models, on the other hand, are used as predictive models not only in food drying but also in other food industries. However, the theoretical model for predicting porosity is a complex one, due to the need for a number of properties that change under drying conditions. In this study, in order to counter the limitations of experimental and theoretical models, a simple shrinkage model based on the shrinkage rate was developed, which considers the main factors affecting porosity. The results show that the proposed model accurately predicts shrinkage and porosity, and this shows that the simulated shrinkage of the apple is related to the experimental results. For example, the porosity of the apple sample simulation is 0.6, which is consistent with laboratory data. The influence of desiccant air temperature and air velocity was also investigated. Studies show that process parameters (including air velocity and temperature) have a significant effect on the final porosity of the dried food. The porosity model proposed in this study requires the least experimental parameters. Future research could use this model to examine other foods because the structure of different foods is different, and this affects the porosity detection mechanism. Different types of process conditions can be used in future research to develop a general model for pore formation.