Majid Rasouli
Abstract
In this study, artificial neural networks (ANNs) was utilized for modeling and the prediction of moisture content (MC) of garlic during drying. The application of a multi-layer perceptron (MLP) neural network entitled feed forward back propagation (FFBP) was used. The important parameters such as air ...
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In this study, artificial neural networks (ANNs) was utilized for modeling and the prediction of moisture content (MC) of garlic during drying. The application of a multi-layer perceptron (MLP) neural network entitled feed forward back propagation (FFBP) was used. The important parameters such as air drying temperature (50, 60 and 70°C), slice thickness (2, 3 and 4 mm) and time (min) were considered as the input parameters, and moisture content as the output for the artificial neural network. Experimental data obtained from a thin-layer drying process were used testing the network. The optimal topology was 3-25-5-1 with LM algorithm and TANSIG threshold function for layers. With this optimized network, R2 and mean relative error were 0.9923 and 9.67 %, respectively. The MC (or MR) of garlic could be predicted by ANN method, with less mean relative error (MRE) and more determination coefficient compared to the mathematical model (Weibull model).
Jalal Dehghan nia; Hamed Bagheri-Darvish-Mohammad; Babak Ghanbarzadeh
Abstract
Introduction: Deep-fat frying is a process of cooking foods through immersing them in edible oils at temperatures above the boiling point of water (150-200°C). During this complex unit operation, heat and mass transfer occur simultaneously.During frying, heat is transferred from edible oil to surface ...
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Introduction: Deep-fat frying is a process of cooking foods through immersing them in edible oils at temperatures above the boiling point of water (150-200°C). During this complex unit operation, heat and mass transfer occur simultaneously.During frying, heat is transferred from edible oil to surface of the food and then transferred into it and at the same time, moisture is transferred from inside the food to outside.As a result of these phenomena and by continuing the process, food temperature increases and its moisture content decreases. This, in turn, creates favorable characteristics such as color, texture and taste of the product.Moisture content is one of the important features in the quality of fried products.In the frying process, moisture loss from food occurs by the mechanisms of molecular diffusion, capillary flow and pressure driven flow.The driving force of moisture loss is the partial water vapor pressure difference between the inside and the surface of the food product due to turning the water into vapor.Rate of moisture loss from the food during the frying process decreases exponentially with frying time and increases with increasing temperature.For information about therelationshipsbetweenvarious variables during the frying process, moisture loss kinetics modelingcan bea suitable steptowards improving thequality offried products.To our knowledge, there has been no study in literature associated with the effect of ultrasound and microwave on moisture loss during deep-fat frying of foods. This study aimed to evaluate the effect of these waves on moisture loss kinetics during frying of potato strips.Materials and Methods: Potatoes (Agria variety) were purchased from a local market and kept in a cold room at 0°C. A mixture of sunflower, soy and cottonseed oil (Behshahr Industrial company), was used for frying potato strips.Inthis study, effect ofultrasound pretreatment at frequencies of 28 and 40 kHz for 15 min and microwave pretreatment at powers of 3 and 6 W/g for 10 min on moisture content of the fried potato slices at 150, 170 and 190°C for 60, 120, 180 and 240 s was investigated.The moisture content of the samples was measured by drying them in a convection oven at 105°C until the weight was constant.Moisture loss experimental data during frying were fitted with six empirical models proposed in this study as well as the Fick’s law of diffusion.The effective moisture diffusion coefficient was calculated based on the Fick's law. To calculate the effect of temperature on the effective moisture diffusion coefficient, the Arrhenius equation was used.Results and Discussion: By increasing frying temperature, moisture content of the potato slices decreased; however the decrease was not significant at a probability level of 5 percent. The positive effect of oil temperature on moisture loss during deep-fat frying of potato strips has been well documented. This is due to the high kinetic energy of water molecules at higher temperatures, leading to a rapid loss of moisture. The moisture loss by diffusion of water molecules as well as the oil uptake during the frying process lead to the formation of cracks in the structure of the solid food. This, in turn, leads to structural damages and significant changes in terms of structural characteristics including porosity.On the other hand, moisture content of the samples significantly decreased in an exponential manner by increasing the process time. Rapid moisture loss in the first moments of frying is associated with the removal of surface moisture. By decreasing surface moisture over time, the rate of moisture loss was reduced accordingly.Results also showed that both the ultrasound and microwave pretreatments at all the studied levels significantly reduced the final moisture content of the samples at a probability level of 5 percent. The difference between the samples pretreated with two ultrasound frequencies of 28 and 40 kHz was not significant (P > 0.05), but with increasing frequency of the pretreatment, the moisture content decreased to a greater extent. Lower final moisture contents of the samples pretreated with ultrasound were probably due to the creation of microscopic channels in the food structure, which may facilitate moisture loss during frying. On the other hand, application of microwave pretreatment at powers of 3 and 6 watts per gram, decreased initial moisture content of the samples by 38 and 80%, respectively. This resulted in significant (P < 0.05) reduction of the final moisture contents of the samples pretreated with microwave. More moisture loss at higher microwave power is probably due to the high intensity of electromagnetic energy as a result of microwave volumetric heating.In addition, the applied modelswerewell fitted toexperimentaldata having high R2 and low RMSE. The effective moisture diffusion coefficient ranged between 3.57×10-8 to 11.08×10-8 m2/s. Results also demonstrated that the effective moisture diffusion coefficient is increased and the activation energy is decreased by implementing the ultrasound and microwave pretreatments.
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.
Hamed Sigari; Mohammad Tabasizadeh; Mohammad Hossein Abaspour fard; Mahmood Reza Golzarian
Abstract
Introduction: Harvesting of Kiwifruit (Actinidiadeliciosa, family: Actinidiaceae) is usually performed in mid-October in Iran. The average weight of this fruit is about 70 g. Hayward is the most popular kiwifruit variety in the world mainly due to its large size, oval shape and high shelf life. Drying ...
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Introduction: Harvesting of Kiwifruit (Actinidiadeliciosa, family: Actinidiaceae) is usually performed in mid-October in Iran. The average weight of this fruit is about 70 g. Hayward is the most popular kiwifruit variety in the world mainly due to its large size, oval shape and high shelf life. Drying fresh products is a long-standing method for conservation of food products. This method reduces water-borne and microbiological activities in fresh products while only minor physical and chemical changes occur in these products. Drying, therefore, is regarded as a common method used for food product conversation. There have been several researches on modeling drying of food products. Wang et al. (2007) worked on a mathematical modeling for drying apple slices in a hot air drying process and determining the effective thermal diffusivity. These researchers stated that Midili model was found to be the best for predicting the moisture content changes during drying. Torgul (2005) confirmed this finding in modeling the drying of apple slices in an infrared drying system. How ever not much research has been carned out on drying kiwifruit slices. Therefore, in this research, the drying process of kiwi slices in a vacuum dryer was examined in order to understand their behavior during the process and to determine a best predictive model for drying and also study the diffusivity coefficient for this product. Materials and Methods: In thes research Hayward variety of kiwifruit for was used Sinco this variety is commonly grown in Iran. The fruits were purchased from local market in mid-October and transferred to a cool storage (50 C) in a lab at the Department of Biosystems Engineering at the Ferdowsi University of Mashhad. The samples used in this study were of medium size and suitable for cutting in a cylinder-shape cutter.The initial moisture content was determined by so-called oven-drying method on wet basis according to the following equation (Mohesnin, 1986):〖%MC〗_wb=(Initial weight-Final weight (after drying in oven))/(Initial weight) 100 (1) The moisture content was determined as 80.23% on a wet basis. The kiwifruits were sliced at 3 mm thickness using a 35 mm-diameter cylinder and weighed with a digital scale. The slices were moved out of the dryer and weighed every 30 min to monitor their moisture content. Weighing continued until the sample’s moisture content reached to 15-20% on a wet basis. Moisture ratio of kiwifruit slices during drying process was determined according to the follow equation:……………… ……….(2)where MR is moisture ratio (dimensionless), Mt is moisture content at any desirable time, Me equilibrium moisture content, percent, dry basis, and M0 is the initial moisture content (kg H2O/kg of dry matter). The value of Me is very small compared with Mt and M0, hence, the error involved in the simplification of above equation by omitting Me is negligible. The experimental drying data were fitted in various drying models commonly used for monitoring the trend of being-dried products. A few of which models are as follows:MR=exp (-kt) : Newton modelMR = exp (_ktn): Page modelMR = 1 + a.t + bt2: Wang and Singh modelMR = a.exp (_ktn) + b.t: Midilli modelIn this research, two statistical proameters were used to evaluate the goodness of fit of the tested models to the experimental data: the coefficient of determination (R2) and root mean square error (RMSE) between the experimental and the predicted moisture ratio values. Diffusivity coefficient for each slice was determined from the following equation:MR=8/π^2 ∑_(n=0)^∞▒〖1/(2n+1)^2 exp[-(π^2 (2n+1)^2)/4 (D_eff t)/a^2 ] 〗 (3) where a is sample thickness (in meter), t drying time (in seconds), n is the number of observations and Deff is effective diffusivity coefficient (in m2.s-1).In long drying process, the following simplified equation is used:MR=8/π^2 exp[-(〖π^2 D〗_eff t)/(4a^2 )] (4) The diffusivity coefficient is the slope of the straight line when experimental drying data in terms of Ln (MR) is plotted versus drying time (t).Results and Discussion: The results of this research revealed that the best prediction curve of moisture content against time was drawn using of MTLAB software. In this regards the rational function with first degree in both numerator and denominator and the third degree polynomial function with maximum coefficient of determination (R2) of 0.9991 and 0.9977 and minimum root mean square error (RMSE) of 0.01267 and 0.02412 were the best prediction models, respectively (Table 2). Furthermore, the drying time becomes shorter as the thickness of kiwifruit slices becomes thinner. This is mainly due to the higher thermal gradient within the thinner slices and hence faster moisture removal due evaporation. The heat diffusivity coefficient was also determined from “Ln (MR) – Time” curves (Figure 3). It was observed that with increase of fruit’s thickness, the heat diffusivity coefficient increases. This phenomenon may be related to the molecular dynamics and the surface tension of materials being dried. In other words the minimum and maximum values of the diffusivity coefficient were observed as 2.0904E-6 and 7.1303E-6 m2.s-1 for fruit thicknesses of 3 and 9 mm, respectively (table 3).Conclusion: The trend of moisture content evolution against drying time during vacuum drying of kiwifruit was investigated using MTLAB software. Different prediction models were examined for the prediction of moisture removal during vacuum drying of kiwifruit. The rational and polynomial functions were determined as the most accurate prediction models with the coefficient of determination (R2) of higher than 0.99 and RMSE of about 0.02. Furthermore, the heat diffusivity coefficient of kiwifruit slices was investigated as a function of slice thickness. A general increasing trend observed for this coefficient as the thickness of the slices increased.
