Food Engineering
Behdad Shadidi; Reza Amiri Chayjan
Abstract
The drying of food can extend the shelf life of food, reduce transportation and storage costs. Fick's second law is commonly used to evaluate the mass data in the drying process in a standard way and is based on many assumptions. Understanding the meaning of mass transfer in products can improve the ...
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The drying of food can extend the shelf life of food, reduce transportation and storage costs. Fick's second law is commonly used to evaluate the mass data in the drying process in a standard way and is based on many assumptions. Understanding the meaning of mass transfer in products can improve the drying process and product quality. Computational fluid dynamics (cfd) models fluid flow situations utilizing powerful computer and applied mathematics in order to predict mass transfer in industrial processes. The aim of this research was numerical study of the drying behavior of pistachio nut using CFD method and evaluating the numerical results in the bed condition of fluid, semi fluid and fix bed as well as air temperatures of 90, 75, 60 and 45°C. During drying using computational fluid dynamic and the Fluent CFD code, the external flow and temperature fields around the cylindrical object (7.5× 10 millimeter) will be predicted in the numerical analysis. A laboratory fluid bed dryer was used for drying experiments. The main parts of the dryer are forward radial fan, drying chamber, electrical heater, inverter, temperature controller. The dryer attachment tools are input and output temperature sensors, anemometer and computer. The numerical part was verified and juxtaposed with the experimental data. The numerical solution result at 60, 75 and 90°C were so close to experimental results except for air temperature of 45°C. Mean absolute error in fix bed, at 60, 75 and 90°C were 0.2123, 0.1257 and 0.0337 which were lower than 45°C temperature and R2 values for these temperatures were 0.9903, 0.9705 and 0.9807, respectively. As the temperature decreased, the values of Eabs and X2 increased in all bed conditions. The average value of R2 for all applied bed conditions was 0.9850. This value showed high correlation between experimental and numerical results.
Hamid Bakhshabadi; Habibollah Mirzaee; Alireza Ghodsvali; Seyed Mahdi Jafari; Aman Mohammad Ziaiifar
Abstract
Introduction: Black Cumin seed (Nigella sativa L.) as one of the novel edible oil resources used commonly nowadays as seasoning in food product industries due to considerable medicinal properties and high nutritional impacts. Oil extraction by pressing method as an approach compared to other methods ...
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Introduction: Black Cumin seed (Nigella sativa L.) as one of the novel edible oil resources used commonly nowadays as seasoning in food product industries due to considerable medicinal properties and high nutritional impacts. Oil extraction by pressing method as an approach compared to other methods including solvent extraction is faster, safer and cheaper. In the oil extraction process, the preparation of the seeds is a substantial stage for obtaining oil with high quality and efficiency. Microwaves are electromagnetic waves that have a frequency ranged from 300 MHz to 300 GHz with corresponding wave lengths ranged from 1 mm to 1 m. On the other hand the artificial neural network as a powerful predictive tool in a wide scale of process parameters has been studied on an industrial scale in this research in order to achieve a simple, rapid, precise as well as effective model in the oil extraction of Nigella sativa L seed.
Materials and Methods: In the present study Black Cumin seeds after preparation including cleaning and passing resistance of the samples in front of air and moisture were stored in a plastic bag until the day of experiments. Then, they have been pre-treated with microwave within different processing times (90, 180 and 270 S) and powers (180, 540, and 900 W). Afterwards, seeds’ oil was extracted by screw rotational speed levels approach (11, 34 and 57 rpm). Different selected parameters including extraction efficiency, oil acidity value, color and oxidative stability were determined. To predict the alterations trend, the artificial neural network (ANN) design in MATLAB R2013a software was used.
Results and Discussion: According to MSE and R2 values obtained in this study, feed forward neural network with transfer function sigmoid hyperbolic tangent and Levenberg- Marquardt learning algorithm with topology of 3-10-5 (input layer with 3 neurons– a hidden layer with 10 neurons – output layer with 5 neurons) were selected as the optimal neural network with R2 more than 0.995 and MSE equal to 0.0005. Also, the results of the optimized and selected models were evaluated and these models with high correlation coefficients (over 0.949), were able to predict the changes' trend. According to the complexity and multiplicity of the effective factors in food industry processes and the results of this research, the neural network can be introduced as an acceptable model for modeling these processes. By determining the activation function in neural networks which was a function of sigmoid hyperbolic tangent in this study and also, with having the amounts of weight and bias, the connections created by the neuro-fuzzy model can be extracted. By defining this simple created mathematical equation, in computer software such as Excel, we can have a useful, simple and accurate program for predicting the desired parameters in the process of oil extraction by using microwave pre-treatment. Due to high accuracy of neural model we can trust the prediction of these models with high confidence, and this model can be used to optimize and control the process, which can lead to saving in energy and time, and on the other hand, can create a better final product.
Enayat-Allah Naghavi; Sadegh Rigi
Abstract
Lemon verbena leave is a flavoring food additive as well as a good source of valuable compounds such as essential oils, flavonoids and phenolic acids. However, similar to many other aromatic plants, lemon verbena leave is perishable due to its high moisture content. The aim of this work was to study ...
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Lemon verbena leave is a flavoring food additive as well as a good source of valuable compounds such as essential oils, flavonoids and phenolic acids. However, similar to many other aromatic plants, lemon verbena leave is perishable due to its high moisture content. The aim of this work was to study the effect of air temperature (45, 55, and 65°C) on the quality attributes of lemon verbena leaves during hot-air drying (HAD). The drying kinetics were also modeled. The results showed that higher drying temperature led to a significant decrease (p˂0.05) in the rehydration ratio due to a change in the structural features of the dried leaves. The essential oil content of dried samples was also significantly different (p˂0.05) from that of the fresh leaves due to high loss of volatile components and ranged from 0.42 to 0.85. Moreover, a significant increase in the value of effective moisture diffusivity (Deff) and color change was observed when the samples were dried at 65°C compared to 45°C. The value of Deff varied from 1.140×10-10 to 2.280×10-9 m2/s and the activation energy was found to be 31.04 kJ/mol. The greatest R2 (≥0.999) and the lowest RMSE and SSE were obtained for the Naghavi et al. model (proposed in this research)
Fatemeh Roshani; Sara Movahhed; Hossein Ahmadi Chenarbon
Abstract
Introduction: Potato is raw food stuff with high popularity worldwide when deep fried. Deep frying is a fast budget process used for preparing savory food. In this process, oil is used both as a heating intermediate and as an ingredient producing calorific products. Nutrition has become a major health ...
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Introduction: Potato is raw food stuff with high popularity worldwide when deep fried. Deep frying is a fast budget process used for preparing savory food. In this process, oil is used both as a heating intermediate and as an ingredient producing calorific products. Nutrition has become a major health concern, particularly in developmental countries where obesity has turned into an ever-increasing problem, mostly among children. Deep frying is a widely-practiced method for cooking fast foods with desirable sensory properties. Frying is a process of simultaneous heat and mass transfer where heat is transferred by a combination of convection and conduction. At high temperatures, a great amount of moisture content is also lost as vapor, compensated by oil uptake in foods. Oil uptake of foods is an important concern associated with their moisture loss. Thus, it is important to examine moisture loss during frying. Today, the interest in production and consumption of low-fat French fries is on the rise. At the same time, the frying method has a great effect on quantitative and qualitative characteristics of foods. The final moisture content in French fries is about 38% of the product’s final weight. sufficient moisture content is therefore required in French fries to achieve both a soft moist core and a crunchy tasty crust. Numerous methods or pretreatments such as ultrasound and drying may improve these properties. Moreover, finding relationships between different variables during deep frying by modelling may provide an optimal control over process conditions thereby improving the quality of the final fried product. In the present study, effects of ultrasound and drying pretreatments on moisture content, oil uptake, activation energy and effective moisture diffusion coefficient in Satina potato slices during deep frying were investigated. Material and methods: 10kg of Satina potatoes were provided and stored at room temperature. Bahar vegetable frying oil containing cotton seed, sunflower and soybean oils was used for frying. For each experiment, potatoes were washed, peeled and sliced by a household French fry cutter with 1.2×1.2×4 cm dimensions. The cut samples were placed in a plate to avoid moisture loss and were washed with distilled water to remove surface starch before frying. The excess surface water was also removed by a hygroscopic paper. Then ultrasonic pretreatments at two frequencies of 20 and 40 kHz were applied for 15min, and the drying pretreatment was also conducted at 60°C for 15min. To fry the samples the fryer was filled with 1.5 lit of oil. The deep fryer was set to adjust temperature and frying time automatically. When the temperature reached the set value, 100-120g potato samples were placed in the frying basket, which was then submerged in oil automatically. The pretreated samples were fried at 170°C and 190°C for 5, 7 and 10 min. Oil uptake and moisture loss during frying were recorded at certain time intervals. Next, the fried samples were removed from the deep fryer and were placed on a mesh tray to remove the excess oil. The oil uptake and moisture content were analyzed. Oil content was measured by the Soxhlet method. It is based on extracting fat from foods using proper solvents. Moisture content was measured by drying in a convection oven at 105°C until reaching a constant weight. Moisture content and oil uptake of potatoes slices during deep frying were also modeled versus time. The factorial experiment was laid out in a completely randomized design with three replications, and means were compared using Duncan’s multiple-range test. SPSS 14 was used for statistical analyses. Results & Discussion: According to the results, samples pretreated with 20 kHz ultrasound at the same temperature and time conditions had higher moisture content than those treated with the 40 kHz frequency. The highest moisture content was found in samples pretreated with 20 kHz at 170°C for 5min. On the other hand, samples receiving 40 kHz ultrasound pretreatment showed higher effective moisture diffusion coefficient and activation energy than those receiving the 20 kHz pretreatment. The highest diffusion coefficient was achieved using 40 kHz at 190°C for 5min, whereas the highest activation energy was observed with 40 kHz at 170°C for 10 min. It should be mentioned that the effective diffusion coefficient was within the 6.95 × 10-8 – 8.80×10-8 m2/s (R2=0.99) range. Activation energy was also in the range of 13.161 – 16.307 kJ/mol (R2=0.99). Conclution: Samples pretreated with 40 kHz ultrasound showed the lowest oil uptake as compared with those pretreated with 20 kHz frequency. The highest oil uptake was observed for samples pretreated with 20 kHz at 170°C for 10 min. Through the multivariable regression analysis, it was found that the exponential model had the best fitting in predicting changes in moisture content and oil absorption.
Ronak Gholami; Jalal Dehghan nia; Babak Ghanbarzadeh
Abstract
Introduction: In recent years, demand for edible and biodegradable films has increased. One reason for this increase is the pollution caused by synthetic polymers. Edible films are produced from different biopolymers such as lipids, polysaccharides and proteins. Starch is a common polysaccharide in the ...
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Introduction: In recent years, demand for edible and biodegradable films has increased. One reason for this increase is the pollution caused by synthetic polymers. Edible films are produced from different biopolymers such as lipids, polysaccharides and proteins. Starch is a common polysaccharide in the preparation of edible films which is taken into consideration because of its low price and easy access. Structure and composition of starch-based films affects the resulting film properties such as moisture sorption, gas permeability, plasticizer crystallization, glass transition temperature and its mechanical properties. Starch films have usually poor mechanical properties and are permeable to water vapor. The use of nanofillers such as cellulose nanocrystal (CNC) in the structure of starch films and production of nanocomposite films is one way to modify properties of the films. The most important purpose of the application of edible films is to prevent moisture or other compounds such as carbon dioxide or volatile components transfer between the product and the environment or between different layers of the product. Modeling mass transfer and moisture permeability of edible films can be effective in predicting film properties and packaged product during storage. For example, it can be predicted that at a certain temperature, relative humidity and time, how much moisture packaging material will absorb. Therefore, before using edible film as a protective coating for food, calculation of the amount of moisture sorption and permeability to water vapor is essential. The purpose of this study was to investigate mass transfer in starch - CNC nanocomposite films. The effect of adding different percentages of CNC on the water vapor permeability and moisture sorption kinetics of nanocomposite films was studiedMaterials and Methods: First, 100 ml of potato starch solution with a concentration of 4% (w/v) was prepared by dispersion of the starch in distilled water and was gelatinized at 90ºC for 5 min. Different levels of CNC (0, 3, 5, 7 and 9% w/w) were dissolved in distilled water and were added to the gelatinized starch after treatment with ultrasound for 10 min. Then, glycerol, as a plasticizer, with concentrations of 0.2, 0.3 and 0.4% (w/w) were added to the solution. The film solutions were distributed on polystyrene surfaces and the resulting films were dried in an oven at 40°C for 24 hours. The Fickʹs second law and four empirical equations were used for moisture sorption modeling of samples. The effect of glycerol concentration on water vapor permeability was investigated and the experimental data were fitted with an exponential model.Results and Discussion: By increasing the concentration of CNC, moisture content of the nanocomposite films declined. Effective moisture diffusion coefficient values for nanocomposite samples were higher than the pure starch film. The coefficient increased from 0.293×10-13 to 0.547×10-13 m2/s by increasing CNC concentration from 0 to 9%. This result can be attributed to the influence of cellulose nanofibers on the polymer matrix and gaps creation in the polymer amorphous regions. This, in turn, would facilitate moisture diffusivity into the polymer structure. It should be noted that plasticizer presence in the nanocomposite structure can be an important factor. Regarding that plasticizer lead to increase in polymer chain mobility, simultaneous presence of CNC and plasticizer could lead to create gaps in the structure of nonocompositefim. As expected, in the absence of plasticizer, the effective moisture diffusion coefficient in nanocomposite samples decreased by increasing the concentration of nanoparticles due to high immobility of polymer chains. In addition, the initial stages of moisture sorption were well described by the Fickʹs law but due to the polymer relaxation between 2.5 - 9 h interval, its behavior was deviated from this law. Finally, after about 9 hours, it was observed that the equilibrium moisture content of the nanocomposite samples were consistent with the values predicted by the Fickʹs model. Equilibrium moisture content depends on the hydrophilic locations of the nanocomposite structure. These locations have the ability to absorb moisture and this ability is not influenced by changes in the structure of the polymer during the moisture sorption process. Despite higher levels of effective moisture diffusion coefficients in starch-nanocrystalline cellulose nanocomposites compared to pure starch film, moisture content was lower in nanocomposite films. These results are probably due to the nature of nanocrystalline cellulose which is resistant to water and is compatible with the starch polymer. Nanocrystalline cellulose has the ability to make many hydrogen bonds with the hydrophilic polymer matrix. This results in decreasing hydrophilic property of starch. On the other hand, in all samples, the permeability to water vapor reduced with increasing nanoparticles concentration. For example, in the starch film which contained 0.4% glycerol, water vapor permeability was 2.62×10-7g.m/m2.h.Pa; with the addition of nanocrystalline cellulose to 9%, its value was decreased to 1.8×10-7g.m/m2.h.Pa. Moreover, the permeability to water vapor in all cases increased by increasing the concentration of plasticizer. Results also showed that there is an exponential relationship between the water vapor permeability and plasticizer content.Conclusion: By increasing the concentration of CNC, moisture content of the nanocomposite films declined. Effective moisture diffusion coefficient values for nanocomposite samples were higher than the pure starch film. The coefficient increased by increasing CNC concentration. The initial stages of moisture sorption were well described by the Fickʹs law but due to the polymer relaxation, its behavior was deviated from this law. Finally, after about 9 hours, it was observed that the equilibrium moisture content of the nanocomposite samples were consistent with the values predicted by the Fickʹs model. In addition, in all samples, the permeability to water vapor reduced with increasing nanoparticles concentration. However, the permeability to water vapor increased by increasing the concentration of plasticizer. Results also showed that there is an exponential relationship between the water vapor permeability and plasticizer content
