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.
Sedigheh Amiri; Soleiman Abbasi; Hamid Ezzatpanah
Abstract
In this study, microemulsification of orange peel oil (OPO) using Tween 60:propanol with the ratio of 1:1 was studied under different conditions of pH, ionic strength, and sugar concentration.. Results showed that critical temperature (the temperature in which one- phase microemulsion system was still ...
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In this study, microemulsification of orange peel oil (OPO) using Tween 60:propanol with the ratio of 1:1 was studied under different conditions of pH, ionic strength, and sugar concentration.. Results showed that critical temperature (the temperature in which one- phase microemulsion system was still stable) for the microemulsions with higher sucrose concentrations (in the range between 0 to 30%) was lower while by decreasing in sugar concentration, critical temperature shifted to higher temperatures, as it reached to 90°C for the samples without sugar. The prepared microemulsions were stable at 5 and 25°C for seven days, but samples with higher concentrations of sugar (25 and 30%) became turbid at 45°C, whereas all other samples exhibited a one-phase microemulsion system at this temperature. Microemulsions were not stable at -3°C (freezing temperatures). In sensory evaluation, it was observed that the microemulsified OPO was dissolved in water as soon as it was added into the medium, in contrast to free essential oil as it was spreading on the surface of the solution. Encapsulation of OPO caused lower release of aroma, resulting a milder odor and taste (lower intensity) in samples which were preferred by the panelists. The overall acceptability of all samples containing OPO microemulsion was significantly higher than samples with free essential oil.
Atefeh Pourmahdi; Mohebbat Mohebbi; Ashraf Gohari Ardabili; Mehdi Varidi; Mohammad Reza Salahi
Abstract
Introduction: Potato is one of the most consumed and highly nutritious vegetables with high energy, dietary fiber, phytochemicals, vitamins, and minerals which offer great benefit for utilization as functional food ingredient. The dried potato powder can be used in formulation of many foods like soups, ...
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Introduction: Potato is one of the most consumed and highly nutritious vegetables with high energy, dietary fiber, phytochemicals, vitamins, and minerals which offer great benefit for utilization as functional food ingredient. The dried potato powder can be used in formulation of many foods like soups, snacks, sauces, noodles, etc. The foam mat drying involves the dehydration of a thin layer of foam followed by its disintegration in order to obtain a powder which can be easily reconstituted in water when added to other foods. Because of the porous structure of the foamed materials, mass transfer is enhanced leading to shorter drying times and consequently acquiring higher quality in the dried product. Food foams can be considered as biphasic systems where a gas (dispersed phase) is embedded in a continuous liquid phase. The foam properties such as structure, density and stability have important influence on moisture migration during drying and accordingly, the quality of final product. Foams that do not collapse for at least 1h are mechanically or thermally stable for the entire drying process. Response surface methodology (RSM) is a combination of mathematical and statistical techniques which used to investigate the interaction effects of independent variables on responses. There is considerable information on foam-mat dried food powders, but there is not any scientific literature that related to study on foam-mat drying of potato puree. The present research was thus focused on optimizing the foaming conditions (potato puree: gum solution ratio; Arabic gum (AG) concentration as the stabilizer and whipping time [WT]) to minimize foam density (FD) and drainage volume (DV) using RSM. Likewise, choosing a suitable model for thin-layer drying of foam and the effect of different drying temperatures (45, 60 and 80°C) on drying behavior were investigated, and the effective moisture diffusivity and activation energy were calculated. The effects of drying temperatures on water activity (aw) and water binding capacity (WBC) were also investigated.
Material and methods: Fresh potato was purchased from a local market (Mashhad, Iran). Arabic gum was procured from Sigma Chemical Company (USA). For preparation of potato puree, fresh potatoes were washed and peeled by steel knife and were washed again and additional water was taken absolutely and then crushed by Phillips home crusher (600W) with maximum speed for 3 minutes to get a homogeneous puree. Based on preliminary tests, AG solutions were prepared by dissolving a suitable amount of the selected gum powder in distilled water and stirring with a magnetic stirrer to obtain a uniform solution. This solution was refrigerated at 4°C overnight to complete hydration. RSM was used to estimate the main effects of the process variables on FD and DV in potato puree foam. The experiment was established based on a face-centered central composite design (FCCD). The experimental range was chosen on the basis of the results of preliminary tests. The independent variables were consisted of potato puree: gum solution ratio (1:1 –2:1 w/w), AG concentration (0.1–0.9% w/w) and WT (3–9 min). According to the experimental design, to prepare 100 g of samples, appropriate amount of potato puree and AG solution were mixed in a 250-mL beaker. The mixture was then whipped with a kitchen mixer (model no. SM88, Sonny, China) at a maximum speed of 1,500 rpm at ambient temperature during given time which was recommended by Design-Expert software. The density of foamed potato puree was determined in terms of mass over volume and expressed in g/cm3. In order to assess foam stability, the drainage test was performed for 1h. To evaluate drying behavior of the optimized foam, drying was carried out in a batch-type thin-layer dryer at temperatures of 45, 60 and 80°C on 3 mm thickness. Ten thin-layer drying models were evaluated in the kinetics research. The higher value of R2 and lower values of χ2, RMSE and SSE were selected as the basis for goodness of fit. Fick’s diffusion equation for particles with a slab geometry was used for calculation of effective moisture diffusivity. The foamed potato puree spread on a tray was considered as slab geometry. Activation energy was calculated by a simple Arrhenius-type relationship, by plotting the ln (Deff) against the reciprocal of absolute temperature (1/T). Furthermore, the effects of drying temperatures on aw and WBC of powders were investigated.
Results and discussions: The quadratic model was selected as a suitable statistic model for both FD and DV. ANOVA showed that this model is significant for both responses. Moreover, lack-of-fit was not significant for response surface models at 95% confidence level, indicating this model is adequately accurate for predicting responses. The optimum values of variables for best product quality in terms of minimum FD and DV corresponded to potato puree to gum solution ratio 2:1(w/w), AG 0.77% (w/w) and WT 6.80 min. The amount of FD and DV for foam at these optimum conditions were 0.30 g/cm3 and 5 ml, respectively.
The result showed that when the drying temperature increased, the drying time decreased. This was due to the quick removal of moisture at higher temperature. Drying rate (DR) versus moisture content of potato puree foam-mats figure showed that DR was higher during the initial stage as compared with the final stage and foam-mat drying was occurred principally in the constant rate period. Due to the increase in surface area and the porous structure, removal of water from the inner surface of potato puree foam to the outer surface was fast enough to preserve the surface moisture. The rate of movement of moisture from the inner surface to the exposed surface decreased with decreasing moisture content, which indicates that the DR decreased and the falling rate period started. The effective moisture diffusivity varied from 3.286×10-9 to 8.032×10-9 m2/s with activation energy value of 30.97 kJ/mol. Statistical analysis results showed that the Weibull distribution model provide the highest R2 and lowest values of χ2, RMSE and SSE at all drying temperatures. The temperature elevation reduced aw. This is due to the fact that at higher temperatures, the rate of heat transfer to the sample would increase, therefore, it provides greater driving force for moisture evaporation which results the dried foams with reduced aw. Drying temperatures did not show any significant effect on WBC of powders.
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)
Alireza Yousefi
Abstract
Adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm-artificial neural network (GA-ANN) were used for modeling of the hot-air drying kinetics of papaw slices. The ANFIS and GA-ANN were fed with 3 inputs of drying time (0-320 min), drying temperature (40, 50 and 60 °C) and slice thickness ...
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Adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm-artificial neural network (GA-ANN) were used for modeling of the hot-air drying kinetics of papaw slices. The ANFIS and GA-ANN were fed with 3 inputs of drying time (0-320 min), drying temperature (40, 50 and 60 °C) and slice thickness (3, 5 and 7 mm) for prediction of moisture ratio (MR). The triangular membership functions (MFs) were applied and 27 rules were provided for the ANFIS designing. The developed ANFIS predictions were close to the experimental data (R2 = 0.9967 and RMSE = 0.0161). The optimized GA-ANN, which included 7 hidden neurons, predicted the MR with a good precision (R2 = 0.9936 and RMSE = 0.0220). The effective diffusivity for papaw slices was within the range of 6.93 ×10-10 to 1.50×10-9 m2/s over the temperature range. The activation energy was found to be 32.5 kJ/mol indicating the effect of temperature on diffusivity.
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.
Amir Salari; Mostafa Mazaheri Tehrani; Seyed Mohammad Ali Razavi
Abstract
In this study, mathematical modeling of hot air baking-drying of thin-layer crisp bread was investigated. Thin-layer drying process were conducted under three different temperatures of 110, 150 and 190 °C at a constant air velocity of 0.5±0.1 m/s and absolute humidity of 0.6 ± 0.04g ...
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In this study, mathematical modeling of hot air baking-drying of thin-layer crisp bread was investigated. Thin-layer drying process were conducted under three different temperatures of 110, 150 and 190 °C at a constant air velocity of 0.5±0.1 m/s and absolute humidity of 0.6 ± 0.04g water/kg dry air. It was found that the baking-drying process occurred in falling rate period over the baking-drying times. Eight well-known thin-layer baking-drying models were fitted to the baking-drying experimental data of crisp bread, implementing non-linear regression analysis techniques. Based on the coefficient of determination (R²) and root mean square error (RMSE) values, it was concluded that the best models in terms of fitting performance for hot air baking-drying of bran free crisp bread were Wang & Singh and Logarithmic while for whole-wheat crisp bread were Page, Logarithmic and Wang & Singh. The moisture transfer from crisp bread was described using the Fick’s diffusion model. The effective diffusivity was within the range of 2.88×10-8 to 1.11×10-7 m2/s for bran free crisp bread and from 2.47×10-8 to 8.84×10-8 m2/s for whole-wheat crisp bread over the temperature range. The activation energy for bran free and whole-wheat crisp bread was found to be 25.22 and 23.43 kJ/mol, respectively..
Hamed Darabi; Ali Asghar Zomorodian
Abstract
Lemon is one of the most important citrus fruit and is consumed as fresh and dry. In this study the effect of
fruit moisture content on the size, sphericity, geometric mean diameters and kernel density were studied. The
bulk density and porosity were also evaluated in three different arrangements. ...
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Lemon is one of the most important citrus fruit and is consumed as fresh and dry. In this study the effect of
fruit moisture content on the size, sphericity, geometric mean diameters and kernel density were studied. The
bulk density and porosity were also evaluated in three different arrangements. Airflow resistance is a
fundamental parameter for designing an efficient drying and aeration systems for lemon fruit bed. Using a
laboratory test rig, two sets of experiments were carried out: thick and thin layers. In the thick layer experiments
4 bed depths, 11 air flow rates and 4 air temperatures were adopted as independent variables. In the thin layer the
effect of filling arrangements in three patterns: A, B and random, at 5 moisture contents and 11 flow rates on
pressure drop were envisaged. Results showed that all the physical parameters listed decreased by reducing
moisture content. Results indicated that resistance to airflow through a column of lemon fruit increased with
increasing bed depth and airflow rate. In the latter experiment pressure drop decreased with a decrease in
moisture content. Airflow rate was the most significant factor affecting the pressure drop of lemon fruit in the
both experiment. Also the filling arrangement B has a higher affect on pressure drop comparing with other
arrangements. Three applicable models (Shedd, Hukill & Ives, and Ergun) were used to evaluate the pressure
drop data. The Ergun model, with higher values for coefficient of determination and lower values for root mean
square error, is the best model for predicting pressure drop across lemon fruit bed for the conditions studied.
