Food Engineering
Ghazale Amini; Fakhreddin Salehi; Majid Rasouli
Abstract
Introduction: The dispersion of water soluble hydrocolloids (gums) in the aqueous system provides great technical importance, because they can improve the gel or enhance the thickening properties of food products. Wild sage seeds have significant amounts of gum with good functional properties that after ...
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Introduction: The dispersion of water soluble hydrocolloids (gums) in the aqueous system provides great technical importance, because they can improve the gel or enhance the thickening properties of food products. Wild sage seeds have significant amounts of gum with good functional properties that after extracting from seeds (mucilage) and drying, can be used in formulation of various products (Salehi, 2017, 2020a). The physicochemical properties and rheological behaviour of seed gums depend on the method and condition of drying. Also, the color of dried product is an important quality factor, which is affected by drying conditions (Amid and Mirhosseini, 2012; Nep and Conway, 2011). For example, effect of different drying methods (oven drying (40-80°C), freeze drying and vacuum oven drying) on rheological behaviour, color and physicochemical characteristics of BSM were investigated by Salehi and Kashaninejad (2017). Drying is one of the simply available and the most common processing approach that has been used traditionally for preservation of food product. One of the best way to reduce the drying time is to use IR radiation heating. IR methods could be used as substitution to the current drying methods for producing high-quality dried hydrocolloids. IR heating has many advantages include high heat transfer rate, uniform heating, low processing time, high efficiency (80-90%), lower energy consumption, lower energy costs, and improves final product quality (Aktaş et al., 2017; Salehi, 2020c). The performance of artificial neural networks (ANN) as an analytical alternative to conventional modeling techniques was reported by some researchers. They reported that these approaches are able to estimate the drying kinetics of various fruits and vegetableswith high precision. It has been shown that nonlinear approaches based on ANN are far better in generalization and estimation in comparison to empirical models (Bahramparvar et al., 2014; Salehi, 2020b; Zhang et al., 2014). It is difficult to predict the combined effects of treatment time, IR power, lamp distance and mucilage thickness on drying kinetics (moisture content and moisture ratio) of fruits and vegetablesusing conventional models. Therefore, the target of this study was to investigate the effect of IR dryer parameters on moisture content and moisture ratio of wild sage seed mucilage during IR drying and studying the performance of ANN method for estimation of these parameters. Materials and methods: Wild sage seeds was physically cleaned and all foreign stuffs were removed. Then, the pure wild sage seeds were immersed in water for 20 min at a seed/water ratio of 1:20 at 25°C and pH = 7. In the next step, the gum was separated from the inflated seeds by passing the seeds through an extractor (M-J-376-N, Nikko Electric Industry Company, Iran) with a rotating disc which scratches the mucilage layer on the seed surface. The initial moisture content (MC) of WSSM was 99.4% (wet basis). Finally, the obtained WSSM was immediately placed into IR dryer. In this study, for wild sage seed mucilage drying, infrared radiation (IR) method was used. The effect of infrared lamp power (150, 250 and 375 W), distance of samples from lamp (4, 8 and 12 cm) and mucilage thickness (0.5, 1 and 1.5 cm) on drying time of wild sage seed mucilage were investigated. Results and Discussion: The results of wild sage seed mucilage drying using infrared method presented that by increasing the lamp power and decreasing the sample distance from the heat source, drying time was decreased. With lamp distance increasing from 4 to 12 cm, the average drying time of wild sage seed mucilage increased from 72.04 minutes to 160.81 minutes. When it comes to sample thickness, we found that by increasing the thickness of mucilage (0.5 to 1.5 cm) drying time of sample increased from 55.59 to 173.67 min. The process was modeled by an artificial neural network with 4 inputs (radiation time, lamp power, lamp distance and thickness) and 2 output (moisture content (MC) and moisture ratio (MR)). The results presented that mucilage drying time significantly increased by decreasing power of lamp (375 up to 150 W) and increasing the heat source distance from sample (4 to12 cm). The results of artificial neural network modeling showed that the network with 8 neurons in a hidden layer and with using the sigmoid activation function could predict the moisture content and moisture ratio of wild sage seed mucilage during infrared drying in various times (r=0.974 for MC and r=0.997 for MR).
Shahram Beiraghi-Toosi; Mohebbat Mohebbi; Mehdi Varidi
Abstract
Introduction: Extrusion is one of the technologies used for solid foams production. In this process, pressure is the most important parameter and the most important variables affecting pressure are feed mixture, die diameter, barrel temperature and screw speed. A reduction of die diameter or plasticizer ...
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Introduction: Extrusion is one of the technologies used for solid foams production. In this process, pressure is the most important parameter and the most important variables affecting pressure are feed mixture, die diameter, barrel temperature and screw speed. A reduction of die diameter or plasticizer contents such as moisture and fats in the feed mixture or an increase in the screw speed or barrel temperature can increase the extruder barrel pressure. Also, the increased barrel temperature, in addition to changing cooking properties, escalates the temperature difference inside and outside of the die, raising the rate and amount of evaporation from melted mixtures, therefor affecting the solid foam structure and characteristics. On the other hand, the type and amount of feed mixture components are key factors affecting the extrudate properties (Moraru et al., 2003; Plews et al., 2009; O’Shea et al., 2014).
Sesame seed is one of the ancient edible oil seeds used in many food products. In addition to oil, it contains carbohydrate, protein and fiber (Namiki et al., 2001) which can provide a variety of compounds in the feed mixture to change the properties of foam. This study investigates the effect of partial replacement of corn starch with edible oil seed containing a mixture of various compounds and the effect of the extrusion process on the changes in the physicochemical properties of the produced solid foam relative to the foam produced from corn starch. In this regard, different proportions of sesame seeds were added to the corn starch with specific moisture contents, and following the application of the extrusion process, the effect of feed mixture, operation temperature, screw speed and die diameter on physicochemical properties of solid foams was evaluated.
Materials and methods: Solid foams made from corn starch with 0, 10, 20 and 30 percent of sesame seed in the formulation and 15 percent of moisture content were processed in a co-current twin-screw extruder at a screw speed of 120, 150 and 180 rpm, a barrel temperature of 120, 145 and 170°C, a die diameter of 2.5 and 4 mm, and a constant feed rate of 40 kg per hour. A completely randomized design was employed to investigate the effect of these variables on chemical and physical properties of extruded products. The moisture content of samples was measured using oven method at 105°C (AOAC, 1990). Water absorption and water solubility indices were measured through solving the sample powder in distilled water, which was followed by centrifuging, weighing gel, drying supernatant and weighing dried matter (Singh et al., 2015; Huang et al., 2014). In addition, particle density was measured using the rapeseed displacement method (Singh et al., 2015) and solid density was calculated by the weight /volume ratio of the sample powder, as measured by the gradient cylinder (Ushakumari et al., 2004; Yagci et al., 2008). The porosity of samples was measured in terms of the ratio of particle density to solid density (Plews et al., 2009; O’Shea et al., 2014) and the radial expansion ratio was calculated in terms of the ratio of sample diameter, as measured by the caliper, to die diameter (Chanlat et al., 2011; Huang et al., 2014).
Results and discussion: Results showed that adding 10% sesame seed, due to the variety of compounds and their increased interactions, produced foams of maximum expansion and porosity, and minimum particle density. Adding 30% sesame seed had an opposite effect due to increased fat content and reduced pressure effect on the melted mixture in the barrel. Moreover, increased die diameter demonstrated augmented residual moisture content, water absorption index, density and porosity, as well as decreased water solubility index and expansion ratio of solid foams caused by pressure reduction on the melted mixture in the barrel. The increased barrel temperature was associated with greater changes in cooking, escalated temperature difference between inside and outside of the die and production of foams with higher water solubility index and expansion ratio, as well as lower residual moisture content, water absorption index and solid density. The higher screw speed increased the applied energy, and despite decreasing the time of temperature effect, produced foams with properties comparable to those caused by temperature increase.
In general, it can be stated that the process factors that raise the energy applied to the extrusion material leads to the increased water solubility index and the expansion ratio of the solid foams and decreased residual moisture, water absorption index and density. Consequently, by selecting the right type and amount of feed mixture to create proportions in various compounds and determine the appropriate process conditions, solid foams with desired properties can be produced by means of extrusion using available raw materials.
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.
Hossein Majidzadeh; Bagher Emadi; Abdolali Farzad
Abstract
In this study, the moisture content of kiwifruit in vacuum dryer was predicted usingartificial neural networks (ANN) method. The drying temperatures (50, 60 and 70ºC), vacuum pressures(500, 550 and 600 mmHg), thicknesses of kiwifruit slices (3, 5 and 7mm) and drying times were considered as the ...
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In this study, the moisture content of kiwifruit in vacuum dryer was predicted usingartificial neural networks (ANN) method. The drying temperatures (50, 60 and 70ºC), vacuum pressures(500, 550 and 600 mmHg), thicknesses of kiwifruit slices (3, 5 and 7mm) and drying times were considered as the independent input parameters and moisture content as the dependentparameter. Experimental data obtained from vacuum drying process, were used for training and testing the network. Several criteria such as training algorithm, learning rate, momentum coefficient, number of hidden layers, number of neurons in each hidden layer and activation function were given to improve the performance of the ANN. The total number of hidden layers and the number of neurons in each hidden layer were chosen by trial and error. The best training algorithm was LM with the least MSE value. Optimum values of learning rate and momentum for the ANN with GDM training algorithm were set at 0.2 and 0.05, respectively. The optimal topologies were 4-20-1 with Tansig activation function and MSE values of 0.0016 and 4-15-20-1 with Logsig activation function in both hidden layer and MSE values of 0.000147. The correlation between the predicted and experimental values in the optimal topologies was higher than 99.75%.
Rahmatollah Eshtavad; Davood Kalantari
Abstract
In this work, experimental studies of internal friction coefficient and porosity of four high productive rice varieties in Iran (Nemat, Neda, Pajouhesh and Pardis) have been presented. Moisture content varied in four different ranges between 8 and 20%. The obtained results indicated that the internal ...
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In this work, experimental studies of internal friction coefficient and porosity of four high productive rice varieties in Iran (Nemat, Neda, Pajouhesh and Pardis) have been presented. Moisture content varied in four different ranges between 8 and 20%. The obtained results indicated that the internal friction coefficient decreased with increasing the moisture content from 8 to 11%, then decreased with increasing the moisture content. The internal friction angles for Nemat, Neda, Pajouhesh and Pardis at the equilibrium moisture content, i.e., 11%, were 39.3, 37.5, 33.95 and 34.38° respectively. Based on results obtained in this study, the apparent physical properties of the rice varieties, e.g., length of the grain, cross sectional diameter of the grain, relative roughness of the external surface of the grain, etc. have significant influence on the normal stress-shear stress relationship. Meanwhile, porosity of the samples depends on the type of variety and moisture content. Porosities of the samples at equilibrium moisture content were 70.8% for Nemat, 63.9% for Neda, 62.7% for Pajouhesh and 66.5% for Pardis
