Journal of Agricultural Machinery

Abstract In this study, an electronic system was built to determine the mass and volume of orange fruits from their dimensions using ultrasonic sensors. The system hardware parts include a metal box, three ultrasonic sensors, a load-cell sensor, an Arduino board, a memory card module, a voltage converter, a keypad, a display and a power adapter. A computer program was written to obtain data from ultrasonic sensors and determine the mass and volume of fruits using regression relationships in Arduino software. 100 samples of orange fruits (Dezful local variety) were picked randomly from a garden and various measurements were done to determine the main physical properties of fruits including three dimensions, mass (M), and volume (V). The system output values for mass and volume of orange fruits with their actual values had no significant difference at 1% probability level. The root mean square error (RMSE) in determining the oranges mass and volume by the system were 9.02 g and 10.90 cm³, respectively. In general, the proposed system performance was acceptable and it can be used for determining the mass and volume of orange fruits.

Abstract Introduction
Cyclone separators use the centrifugal force generated by the gas flow stream to separate the particles from their carrier gas. Simple design, low capital, and easy maintenance make them ideal for use as a valuable pre-refining or sedimentation device. The cause of the particles moving towards the wall and separating from the fluid phase is the centrifugal force created by the rotational flow in a cyclone.
Computational fluid dynamics (CFD) is one of the most well-known and widely used advanced modeling methods used for a variety of applications, including separation processes, thermal processes such as dryers, as well as a wide range of engineering and agricultural applications. The numerical solution of Navier-Stokes equations is the basis of all CFD techniques, which is the result of the rapid progress of computers and a deep understanding of the numerical solution of turbulence phenomena.
Materials and Methods
The measurement system of experimental data includes a cyclone separator, feeder, piping, and fan. Measurements of velocity and pressure were carried out using a hot wire air flow rate, (Model 8465-TSI with a resolution of 0.07 m.s^-1 and a working range of 0.125 to 150 m.s^-1), as well as a differential pressure gauge (CPE310s- KIMO, with an accuracy of 0.1 Pa), respectively. To investigate the effect of the output flow regulator plate on the cyclone performance, five different positions in addition to the base position (zero degree angle or fully open) including angles of 15, 30, 45, 60, and 75 degrees were evaluated.
The conservation laws governing the various flows and geometries in the CFD include the conservation law of mass, conservation law of momentum, and conservation law of energy.
According to the Mach number value, the pressure base solver was selected. Also, the Reynolds stress model (RSM) was applied to model the flow turbulence. In the discrete phase model (DPM), the fluid phase is solved continuously by solving averaged time equations, while the dispersed phase is calculated by tracing a large number of particles through the flow field.
The boundary conditions used in this study include the inlet velocity boundary condition at the inlet of the cyclone, the outlet pressure boundary condition in the upper and lower outlet sections, and the non-slip wall boundary condition for other surfaces. The particle collision to the wall was also defined as reflective. In the mesh section of the cyclone simulation, five mesh levels were used to check the mesh independence test. The numbers of mesh cells in the five levels were 196810, 283120, 427890, 634940, and 1045290. The selected mesh was 427890 level regarding time consideration.
Results and Discussion
In the first section, the validation of simulation results with experimental results is discussed. The value of the velocity magnitude decreased with increasing the angle of the plate, which is probably due to the reduction of the inlet level as well as the reduction of the exhaust airflow in the cyclone air outlet.
The maximum value of velocity magnitude occurred according to the direction of the air inlet in the cyclone inlet, which is gradually reduced due to the rotational motion inside the cyclone.
The collection efficiency in the cyclone at different levels of regulating plate has values of 85.1% to 95.3%, with maximum collection efficiency at 30° which was 95.3%. The turbulent intensity contours show that turbulence intensity decreases to an angle of 30°, and then reaches an almost constant value for the 30, 45, and 60° angles.
Conclusion
As the angle of the output current regulator plate increased, the magnitude of velocity decreased significantly.
The separation efficiency showed an increasing-decreasing trend for different values of the regulator plate such that up to a 30° angle of the plate had a positive effect on the separation efficiency.
In general, considering the compromise between separation efficiency and pressure drop as two key parameters affecting the performance of the cyclone, an angle of 30 degrees was selected as the best angle among the studied angles for application.

Abstract Introduction
Thermo-compressors or ejectors are used to enhance the vapor enthalpy in the process industry. The low costs of construction and maintenance, and simple structure, have increased by using this equipment in relevant fields of industry and agriculture. The thermo-compressor's inlet parameters, including the thermodynamic properties of the motive steam and suction vapor, are the foremost affecting factor of a thermo-compressor.
The steam used in processing factories loses its capability after passing through evaporators due to the reduction of pressure and temperature, gets cooled again, and returns to the boiler despite having a moderate energy level. Therefore, the use of vapor-recovery equipment can increase the efficiency of energy systems. That will lead to a significant reduction in greenhouse gas emissions and harmful environmental effects, which increase the lifetime of energy resources.
Materials and Methods
The realizable k-ε turbulence model is used to simulate turbulence within the flow. The thermo-compressor geometry has meshed in 2D and 3D modes to apply the conservation laws. For this purpose, quadratic (quad) and hexahedral (hex) types are used for two and three-dimensional meshing, respectively. Structured meshes have a high ability to obtain numerical results due to creation of structural meshes in the flow direction.
The axisymmetric structure of the thermo-compressor leads to a half simulation of geometry. The thermodynamic properties of the input flows and their variations in the output, such as pressure, velocity, Mach number, and mass ratios for different motive steam pressure are extracted and discussed.
Results and Discussion
Different levels of meshes are examined to investigate the mesh-independence test. In axisymmetric two-dimensional analysis, these levels include 33460, 51340, 78620, and 103590 cells, respectively. The relatively insignificant difference in motive flow for the third and fourth mesh levels (which proves less than 5%) clearly shows the independence of the results from the mesh size. Regarding the time considerations, the grid with 78,620 meshes was used in the simulations.
The experimental data from the article by Sriveerakul et al. (2007) are used to validate the numerical results of the present work. Validation shows that the results obtained from the simulations are in good agreement with the experimental data. Since the final results of the two-dimensional analysis are very close to the three-dimensional one, the first one is selected due to the time considerations and higher computational costs of the three-dimensional mesh analysis.
Considering the problem conditions, pressures of 10 and 15 bars are appropriate for practical application. Since the 15 bar motive stem creates a longer development length in the diffuser section, it is a better choice. At this level (15 bar), the temperature field within the thermo-compressor is well distributed in the presence of ideal temperature conditions. The ideal velocity distribution within the thermo-compressor and the uniformity of the motive and suction flows indicate the high performance of the thermo-compressor in these operating conditions. Applying the motive steam of 15 bars, the values of 0.59 and 0.41 for the motive and suction mass ratios of the diffuser output were achieved, respectively.
Conclusion
Geometrically, the study was examined in asymmetrical two-dimension and three-dimension. It was observed that there is a slight difference between the two analysis modes by comparing the velocities along the longitudinal line of the thermo-compressor. Therefore, to save computational and time costs, results are presented for the axisymmetric two-dimensional mode.
The effect of 4 levels of motive steam pressure on the thermodynamic properties within the computational domain, including pressure, temperature, velocity, Mach number, mass ratios of both motive steam, and suction vapor are evaluated. Finally, the values of the performance curve for steam with motive pressures of 3.7, 5, 10, and 15 bars are presented.

Abstract Introduction
Transportation of fresh fruit and vegetables is complicated because it can be affected by various factors. Truck vibration is one of the most prevalent causes of mechanical damage to fresh fruit during transportation. Poor driving performance, road features, package features, truck features, package location, and fruit features are the main factors that affect truck vibration. After the harvest, the crop's quality can be maintained and cannot be improved. Thus, the globalization of fresh produce trade needs better long-distance transportation systems to deliver high-quality products to the consumer. Fruit packaging is an essential factor in reducing the mechanical damages caused by transportation. A wide-ranging of distribution environments could affect designing packages. Accurate information about the traffic and transportation status of any region helps packaging designers to produce a more precise simulation of the existing conditions. Thus, this research was conducted to analyze the vibration levels for truck transport on highway roads using multi-sensor-based computing on packaged fruit in Iran.
Materials and Methods
Towards this goal, a wireless sensor network (WSN) made of three sensor nodes with tri-axial accelerometers was designed to measure the vibration levels of a truck equipped with leaf-spring suspension on highway roads. This WSN solution enabled the sensors to be easily mounted at different locations and provided real-time data monitoring. A GPS receiver and a laptop were used to determine the location of the truck, and data analysis, receptively. To analyze the vibration data a, power spectral density function (PSD) levels were applied. A PSD function shows the strength of the variations (energy) as a function of frequency. Broadly, it shows at which frequencies variations are strong and weak. The vibration levels measurement was carried out on three trucks with leaf-spring suspension. The three selected routes represent different roads type in Iran. The reason for sampling the data acquired in the long route was to obtain information from different geographical locations on the country's roads.
Results and Discussion
The acquired data can be used in laboratory vibration tests if it is independent of the fruit type. Because the acceleration of the truck bed, unlike the one in top rows, does not depend on the fruit type and the acceleration at the end of the truck is higher than at the front, the current study focused on the vibration at the end of the truck bed. Compared to the ASTM 4728 standard, the PSD levels of the truck on highway roads were higher from 1 to 35 Hz and lower from 35 to 200 Hz. The average RMSG values calculated for lateral, longitudinal and vertical directions of heavy trucks were 0.406, 0.236, and 0.654 G, respectively. For trucks with spring suspension, the highest PSD values occurred at frequencies below 6 Hz, and the frequency range of 3-4 Hz was determined as the dominant frequency. Comparing the average RMSG (0.654 G) found with the ones mentioned in previous studies showed that the vertical vibration levels of the truck in Iran are higher than in most countries. Apart from driving quality, these results can be explained by the type of suspension system, amount of load, and road quality.
Conclusion
In sum, the results can be used to simulate the truck transport conditions by programmable vibration simulators to reproduce the vibration conditions for package testing on Iran roads. The findings are highly interested in improving packaging design, reducing fruit damage, maintaining shelf life, smart transportation, and related industries. Thus, potential future works are lab simulations, optimizations of packages, and the development of a real-time vibration monitoring system.

Abstract Introduction
Sour cherry concentration is a significant agro-industry in the world. In 2016, world production was 13.8 million tons and most of which were processed in the form of concentrate or frozen products. Iran has the 6th rank among the producers of sour cherry and experienced a highly rise (45%) in production in 2016. A conventional energy system evaluation is performed using the energy analysis method. The thermodynamic inefficiencies occurring within the system (factors that cause a gap between performance and ideal state) are not identified and evaluated by energy analysis.
Materials and Methods
Pakdis concentrate production line includes a plate heat exchanger (HE) converter to preheat input juice using condensate water energy and crude juice heat outlet, four multipurpose falling evaporators (E1, E2, E3, E4), a distillation tower for raw juice aromatization (DT) and a juice cooling system (JC).
A thermographic camera (G120EXD, NEC Avio, Japan) was used for thermographic recording. Initial examination of the thermography results showed that the external surface temperature of the equipment except for the evaporators (E1, E2, E3, E4), the boilers (B1, B2, B3) and the condensation tank of the evaporation line (CT1) had very little difference with the ambient temperature around them, and therefore, their heat flux was ignored.
Due to limitations, the mass flow rates of the evaporation line (except for inlet juice) were not measurable, and therefore, energy analysis was used to calculate them. Energy analysis involves the simultaneous resolution of mass and energy balances for a system.
Results and Discussion
The heat loss rate from the first evaporator (E1) was calculated to be 21.23 kW from which mass/energy balances and mass flows were extracted. Also, heat loss rate from utilities E2, E3, E4, and CT1 were calculated from mass-energy balances. Streams 32, 49, 52, and 54 are not utilized and exit the system. Hence, they are assigned as heat loss streams within the evaporation line.
The total energy loss rate in the evaporation line was calculated to be 4920.82 kW which contributes 74.8% of total input energy to the line. However, 73.39% of this loss is assigned to the cooling tower (stream 54). Stream 29 from the 4^th stage evaporator enters the condenser, mixes with water, and provides cold water goes to the cooling tower. In the tower, water evaporates and dissipates heat to the environment. Stream 32 is the second loss stream with 14.8%. Also, it should be noted that heat loss from the surface of utilities makes 3.06% of energy loss of the evaporation line which implies that insulations are done properly in utilities.
Evaporation performance may be rated simply and primarily by the steam economy. The value was calculated to be 2.63 in the evaporation line, i.e. 2.63 kg water is evaporated per 1 kg steam injected into the system
Exergy rate in several streams of evaporation line. The exergy rate of fuel and products, exergy efficiency, exergy destruction rate, and exergy destruction ratio for each element of the line were reported. Total input exergy to the evaporation line is 4832.03 kW from which 1045.85 kW is destructed due to irreversibility and 3786.19 kW is dissipated.
Major destruction occurs within barometric condenser (BC), pressure reducing valve (PR), a plate heat exchanger (HE), evaporators 1 and 2 (E1 and E2), cooling tower (CT), and then evaporators 3 and 4 (E3 and E4). The remaining destruction in other utilities is negligible.
Conclusion
Using the first and second laws of thermodynamics and instrumentation procedure, sub-systems of the evaporation unit of Pakdis Company were investigated and energy and exergy balances were coupled and solved. Thermographic assessment of likely zones to energy losses was employed. The whole process was monitored and mass-energy balances were developed. The steam economy as a reliable criterion for evaporation was calculated. To extract inefficiencies and possible optimizable unit operations exergetic analyses were carried out and subsequently the share of exergy loss and destruction and capital cost in the whole process was defined. It was found that capital cost is consistently ignorable compared to exergetic faults such as losses and destructions.

Abstract In this study, the effects of infrared (IR) dryer system parameters such as IR power, the distance of mucilage from lamp surface, mucilage thickness on drying kinetics and, color indexes (L*, a*, b* and ΔE) of wild sage seed mucilage (WSSM) were investigated in an IR dryer system. Experimental moisture ratio (MR) data were fitted to 7 various empirical thin-layer models. It was found that the Page model has the best fit to show the kinetic behavior and acceptably described the IR drying behavior of WSSM with the lowest mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and standard error (SE) values and the highest correlation coefficient (r) value. The values of MSE, RMSE, and MAE for all experiments were in the range of 0.1×10^-3-1.1×10^-3, 1.04×10^-2-3.25×10^-2 and 8.7×10^-3-27.1×10^-3, respectively. The average effective moisture diffusivity (D_eff) increased from 4.61×10^-9 m²s^-1 to 15.8×10^-9 m²s^-1 with increasing lamp power from 150 W to 375 W, while it was decreased from 14.4×10^-9 m²s^-1 to 5.16×10^-9 m²s^-1 and 13.2×10^-9 m²s^-1 to 4.31×10^-9 m²s^-1 with increasing the distance of mucilage from 4 to 12 cm and the reduction of mucilage thickness from 1.5 to 0.5 cm, respectively. Increasing in IR radiation power has a positive influence on the yellowness (increasing 19.78% in b^* index) of dried WSSM. Also, it increased the color changes index (ΔE) from 16.05 to 17.59.

Abstract Introduction
One of the most important and sensitive steps after walnut harvesting is the separation of the kernel from its shell. Walnut rupture force is an appropriate criterion for design with high performance and better quality, which can be used as the basis for designing and adjusting the various parts of machines that are in contact with walnut. The lower rupture force caused the less energy requirement to separate the walnut kernel from the shell. The use of ultrasound in ambient fluids is well known to cause turbulence and biological cell rupture. These effects arise principally from the phenomenon known as cavitation which can scour surfaces and damage cellular material. Therefore the object of this study is to find the effect of ultrasound factors on the amount of walnut rupture force and quality of kernel extraction.
Materials and Methods
Walnut paper variety was selected from a Qazvin province orchard for this study. To determine the initial moisture content of the nuts, the samples were dried in an oven at 105°C for 24 h. Initial moisture content was found 5.5 (%w.b). The ultrasounds bath system (D-78224 Singen/htw, Elma, Germany) was used with a nominal frequency of 50 kHz and power of 1000 W. In this research, based on the pretest results and previous studies (Cao et al., 2010; Entezari et al., 2004) walnut samples were treated with three ultrasound time duration (5, 10 and 15 min) and three ultrasound bath temperature (20, 35, and 50ºC). Moisture content of the walnuts after ultrasound treatment was 8.8 (%w.b). After the walnut samples were treated by ultrasonic factors, a material testing machine (H50 K-S, Hounsfield, England) was used to determine the rupture force of the walnuts. The walnut was placed between two plates, and loaded at three loading speeds (0.5, 1.5, and 2.5 mm s-1) and pressed until the walnut ruptured. Rupture force was applied along with X and Y axes. The X-axis was in the longitudinal axis through the hilum to the tip (length) and the Y-axis was in the latitudinal axis (width) at right angles to the X-axis. Kernel extraction quality was classified into grades according to size and number of broken pieces of the kernel. Central composite design (CCD) of resound surface method was used to optimize the effect of ultrasonic factors on walnut kernel extraction.
Results and Discussion
The results indicated that the loading speed, ultrasound time duration, loading direction, and moisture content had a highly significant effect (P<0.01) and ultrasound bath temperature (P<0.05) on the rupture force and kernel extracting quality. Regarding the sum of squares of ANOVA results, the ultrasound time duration factor had the most effect on the rupture force and the loading direction factor had the most effect on kernel extraction quality. By increasing bath temperature and ultrasound time duration, walnut rupture force was decreased. The minimum walnut rupture force was obtained in 25 min ultrasound time duration, 50ºC bath temperature, 1.5 mm s^-1 loading speed, and width loading direction for wet walnut. By increasing bath temperature, walnut kernel losses were increased. The best kernel extraction quality was obtained in 2.5 mm s^-1 loading speed, 25 min ultrasound duration, 20ºC bath temperature, and longitudinal loading direction. The proposed optimal point was obtained at 64.4 N rupture force, and two half of the kernel at 1.3 mm s^-1 loading speed,  25 min ultrasound duration, 50ºC bath temperature, and longitudinal loading direction for wet walnut.
Conclusion
The walnut ultrasound treated samples had minimum rupture force and the best quality kernel extraction. It was observed that by increasing the loading speed and ultrasound time duration, the percentage of whole kernels and the quality degree of broken kernels increased.

Abstract Introduction
In recent decades, artificial intelligence systems were employed for developing predictive models to estimate and predict many agriculture processes. Neural networks have the capability of identifying complex nonlinear systems with their own high learning ability. Artificial Neural Networks as a modern approach has successfully been used to solve an extensive variety of problems in the science and engineering, exclusively for some space where the conventional modeling procedure fail. A well-trained Artificial Neural Networks can be used as a predictive model for a special use, which is a data processing system inspired by biological neural system. The short storage life of hawthorn fruit and its high susceptibility to water loss and browning are the main factors limiting its marketability. So, it is important to evaluate parameters that affected the hawthorn quality. An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi-Sugeno fuzzy inference system. To estimate changes in fruit quality as a function of storage conditions, the evolution of certain quality-indicative properties such as color, firmness or weight can be used to provide related information on the quality grade of the product stored. Measurement of these parameters is an expensive and time-consuming process. Therefore, parameter prediction due to affecting factors will be more useful. In this study, the physicochemical properties of hawthorn fruit during various storage was predicted using artificial neural networks method. Hawthorn (Crataegus pinnatifida), belonging to the Rosaceae family, consists of small trees and shrubs. The color of the ripe fruit ranges from yellow, through green to red, and on to dark purple. Hawthorn is one of the most widely consumed horticultural products, either in fresh or processed form. It is also an important component of many processed food products because of its excellent flavor, attractive color and high content of many macro- and micro-nutrients.
Materials and Methods
The purpose of this study was a prediction of color, physical and mechanical properties of hawthorn fruit (Crataegus pinnatifida) during storage condition using artificial neural networks (ANNs) and adaptive network-based fuzzy inference system (ANFIS). Experimental data obtained from fruit storage, were used for training and testing the network. In the present research, artificial neural networks were used for modeling the relationship between physicochemical properties and color attributes with different storage time. Several criteria such as training algorithm, learning function, number of hidden layers, number of neurons in each hidden layer and activation function were given to improve the performance of the artificial neural networks. The total number of hidden layers and the number of neurons in each hidden layer were chosen by trial and error. The network’s inputs include storage time, hawthorn moisture content and storage temperature and the network’s output were the values of the physicochemical and color properties. The training rules were Momentum and Levenberg-Marquardt. The transfer functions were TanhAxon and SigmoidAxon.
Results and Discussion
To predict the weight loss and firmness multilayer perceptron network with the momentum learning algorithm, topologies of 3-15-5-1 and 3-8-5-1 with R²=0.9938 and 0.9953 were optimal arrangement, respectively. The optimal topologies for color change, hue, Chroma were 3-9-7-1 (R²=0.9421), 3-9-3-1 (R²=0.9947) and 3-7-1 (R²=0.9535) respectively, with momentum learning algorithm and TanhAxon activation function. The best network for ripening index prediction was Multilayer perceptron network with the TanhAxon activation function, Levenberg-Marquardt Levenberg-Marquardt learning algorithm, topology of 3-5-1-1 and R²=0.9956.
Conclusion
Three factors including firmness, total soluble solids and titratable acidity were considered for ripening index calculation during fruits storage condition. Momentum and Levenberg-Marquardt learning algorithms with SigmoidAxon and TanhAxon activation functions were used for training the patterns. Results indicated artificial neural networks to be accurate and versatile and they predicted the quality changes in hawthorn fruits. The outcomes of this study provide additional and useful information for hawthorn fruits storage conditions.

Abstract Introduction
Extra Virgin Olive Oil (EVOO) is one of the most common and popular edible oils which is an important part of the Mediterranean diet. It is a rich source of sterol, phenol compounds and vitamins A and E. EVOO has useful effects on human body and significant reduction of cardiovascular diseases due to these benefits, EVOO is expensive so unfortunately adulteration in EVOO by mixing it with other cheap and low cost and low value oils such as canola, sunflower, palm and etc. is very common. Adulteration leads to health and financial losses and sometimes cause serious illness. Olive oil has various quality levels which depend on different factors such as olive cultivar, storage, oil extracting process etc.
Materials and Methods
There are numerous food quality evaluation and adulteration detection approaches which include destructive and non-destructive methods. Control sample (EVOO) was applied from "DANZEH food industry", Lowshan, Gilan Province. For ensuring that control sample is extra virgin, a sample was tested in "Rahpooyan e danesh koolak Lab." Tehran, Iran; according to "Institute of standards and industrial research of Iran" ISIRI number: 4091 and INSO 13126-2. Eight semi-conductor gas sensors "FIS, MQ3, MQ3, MQ4, MQ8, MQ135, MQ136, TGS136, TGS813 AND TGS822" applied in used olfaction machine. In this study there were 6 treatments: 1- Pure EVOO, 2- EVOO with 5% adulteration, 3- EVOO with 10% adulteration, 4- EVOO with 20% adulteration, 5- EVOO with 35% adulteration and 6- EVOO with 50% adulteration. Adulteration created with ordinary frying oil (including sunflower, canola, and maize oils). Each treatment prepared in seven samples and each sample test was repeated seven times. In this study, olfaction machine, a non-destructive, simple and user friendly System applied. As mentioned, the olfaction machine includes eight different sensors, so each test has eight graphs. Four features (1- Sensor output (mV) in start of odor pulse (refer to fig. 3) 2- Sensor output at the end of odor pulse 3- Average of sensor output during odor pulse and 4- Difference of sensor output at the end and start of start of odor pulse); So 32 features extracted and analyzed and finally effective sensors reported.
Results and Discussion
Histogram and box plot of raw data showed that the data are not normal and need some preprocessing operations. Preprocessing facilitates data analyzing and classifying extracted features. After preprocessing, the standard data, divided into two classes: train data (70%) and test data (30%). Data classified with 4 different classifier models which include: K-nearest neighbors, support vector machine, artificial neural network and Ada-boost. Results showed that KNN method, with 89.89% and SVM with 86.52% classified with higher accuracy. Similarly, the confusion matrix showed the reasonable results of classifying operation. Also, three effective sensors in classifying determined TGS2620, MQ5 and MQ4 respectively, and on the other side, sensors such as MQ3 and MQ8 have the minimum effect on classifying so it is possible to remove these sensors from the sensor array without effective impress on results. This may cause decrease in the olfaction machine price and reduce analyzing time.
Conclusion
Due to increasing adulteration in foods, especially in olive oil and its significant effects on people's health and financial losses, a simple, cheap and non-destructive quality evaluation extended. Results showed that the olfaction machine with metal oxide semiconductor (especially including TGS 2620, MQ5 and MQ4 sensors) can use for classification and adulteration detection of extra virgin olive oil. Evaluation of this system's output leads to higher classification accuracy by using KNN and SVM method for olive oil classification and also fraud detection (5% adulteration).

Abstract Introduction
Strawberry plays an important role in human health because of its micronutrients and natural antioxidant content. Increasing storage time and decreasing microbial processes, weight and volume, and eventually facilitating export, has bolded the need for drying this product. The most common drying method is sun drying. This technique requires large areas and lengthens the time to complete the process which is undesirable economically. Furthermore, the final product may be contaminated by dust and insects, and the exposure to solar radiation results in color deterioration. In order to improve the quality, traditional sun drying techniques can be replaced by a more rapid and efficient drying method such as hot-air drying. In recent years air impingement technology has got more attention in the field fruit slices drying due to high heat and mass transfer, decreasing drying time and increasing product quality. The objectives of this study were to investigate the effects of drying conditions on the drying kinetics and quality characteristics including the rehydration ratio of the strawberry slices in an air impingement jet dryer.
Materials and Methods
An air jet impingement dryer with controllable temperature, air velocity, and the relative nozzle-to-product distance (H/D) was used in this study. The experiments were conducted under different temperatures (45, 55, and 65°C), air velocities (6, 9, and 12 m s^-1) and H/D ratios (4, 5, 6, 7, and 8). The initial moisture content, effective moisture diffusivity, activation energy, and rehydration ratio were evaluated.
Results and Discussion
The effects of drying temperature and air velocity on the moisture ratio and the drying rate are shown in Figs 2 and 3. As it can be seen, the moisture ratio of strawberry slices decreased with the increase of drying time. The analysis of variance for drying time indicated that increasing drying temperature and air velocity could reduce the drying time.  In addition, the effect of drying temperature on drying time was more significant than that of the air velocity.  It is clear that the drying rate decreased with moisture content. There was a rapid decrease in drying rate during the initial period and slow decrease at the later stages of the drying process. It is also found that the drying process generally took place in the falling rate period. It is observed that the moisture ratio decreased as H/D ratio fall. The response of drying time was affected significantly (p < 0.05) by H/D ratio. The effective moisture diffusivity increased with increasing drying temperature and air velocity. Based on the results reported in this study, the Wang and Singh model with the lowest Root Mean Square Error (RMSE=0.02) and the highest Coefficient of determination (R²=0.996) provided the best fit to describe the experimental drying data of strawberry slices. The statistical analysis shows that drying temperature and air velocity have significant (p < 0.01) effect on the rehydration ratio (RR) of slices, while the interaction effect was not significant. The means comparison shows that the RR of dried slices decreased as drying temperature and air velocity rose. H/D ratio significantly (1%) affected rehydration ratio. The means comparisons shows that the rehydration ratio increased when H/D value varied from 4 to 8. Also, the results of color change represented that color change of dried samples decreased with increase of temperature and air velocity and increased with increase of the H/D ratio.
Conclusion
a) Increasing drying temperature and air velocity dropped the drying time. In addition, the effect of drying temperature on drying time was more significant than that of the air velocity.
b) A constant rate period was not observed in drying of strawberry slices and the whole process of strawberry slices was carried out in the falling rate period.
c) The moisture ratio decreased as H/D ratio dropped, which in turn resulted in saving drying times.
d) The Wang and Singh model was found to be the best model to describe the drying kinetics of strawberry slices.
e) The effective moisture diffusivity of strawberry slices ranged from 1.62×10-10 to 3.24×10-10 m² s^-1.
f) The values of activation energy of strawberry slices were found to be 12.88, 15.055 and 16.746 kJ mol^-1 for air velocities of 6, 9 and 12 m s^-1, respectively.
g) The rehydration ratio of dried slices dropped as the drying temperature and air velocity rose and increased with increase of the H/D ratio.
h) The color change of dried samples decreased with the increase of temperature and air velocity and increased with the increase of the H/D ratio.

Abstract Introduction
Some unit operations of food process engineering such as drying consumes a high amount of energy. Therefore, analysis of energy and exergy can be a suitable method to manage the energy consumption of the drying. Hence, in the present research, analysis of energy and exergy for the drying process of lemon verbena leaves was performed.
Materials and Methods
A cabinet solar dryer was employed to investigate the energy consumption of thin layer drying of lemon verbena leaves. The dryer had a galvanized solar plate collector which had a surface area of 0.75 m2 and to absorb the maximum solar energy, the collector painted with the black color. The collector was set at an angle of 45 degrees relative to the horizon and an electric blower was installed in the bottom of the collector to blow the ambient air through the solar collector and hence, hot air entered the drying chamber to dry the lemon verbena leaves. In order to record the air temperature and humidity in different locations of the dryer, an Arduino board with 8 smart sensors (AM2301, with temperature accuracy of 0.5°C and humidity accuracy of 3%) were used. To obtain the initial moisture content of the leaves, they inserted in an electrical oven for 16 hours at a temperature of 70°C. In order to measure the moisture content of the leaves during drying, they weighted at different times using a digital balance (A & D, Japan with accuracy of 0.001 g).
Energy consumption rate of the drying was calculated by Equation (1):
Where, Ein: energy consumption rate (kW), : mass flow rate of drying air (kg s^-1), cp: specific heat of drying air (kJ kg^-1 °C^-1), Δt: temperature difference between the ambient air and drying air (°C).
Also, the specific energy consumption of drying (SEC) was calculated by Equation (2):
Where; SEC: Specific energy consumption (MJ kg-1 of removed water) t: drying time (s), and M: mass of removed water from the drying material (kg).
Also, useful power can be calculated from Equation (3):
Where; Eout: useful power (kW), ms: Evaporation rate (kg s^-1), lg: latent heat of vaporization (kJ kg^-1 of water)
In order to calculate energy efficiency, Equation (4) was used:
 
Also inlet and outlet exergy were calculated by equations (5) and (6), respectively:
 Where; T1: Inlet air temperature into the drying chamber (°C), T2: Outlet air temperature from the drying chamber (°C), T0: Ambient air temperature (°C).
Also, Equations (7) and (8) were used to calculate exergy efficiency and loss, respectively:
Results and Discussion
The results of energy analysis showed specific energy consumption (SEC) increased with increasing of drying temperature and decreasing of air velocity. Accordingly, in the air velocity of 2 m s-1 and the temperatures of 30, 40, and 50 ˚C, SEC were 276.3, 694.7, and 708.0 MJ kg^-1 of removed water, respectively. While SEC for an air velocity of 2.5 m s^-1 and air temperatures of 30, 40, and 50 ˚C were 266.9, 469.8, and 638.0 MJ kg^-1 of removed water, respectively, the corresponded values for air velocity of 3 m s^-1 were as 217.0, 391.3, and 501.8 MJ kg^-1 of removed water, respectively. Also, the results revealed that with an increase of temperature and a reduction of velocity, energy efficiency reduced, so that the maximum value of energy efficiency observed in an experiment with temperature of 30˚C and velocity of 3 m s^-1. Also, the highest value of exergy efficiency obtained in temperature of 50˚C and velocity of 3 m s^-1.
Conclusion
A hot air solar dryer was used for drying lemon verbena leaves. Results of specific energy consumption of drying showed a high amount of fossil fuels can be saved by using this dryer. Also, from the aspect of energy and exergy efficiency, using of the dryer in the lower temperature and higher air velocity is recommended.

Abstract Introduction
Food is composed of various compounds, and when the food quality expires, it becomes inappropriate for consumption and the end of life leads to some pathogenic microorganisms in food. So food processing is essential. In recent years, various heat treatments have been considered that have various disadvantages, so researchers are looking for alternative technologies in industrial processing to overcome these problems. Electric treatments play an important role in food heating technology and one of the methods of electric thermal processing is ohmic processing, that ohmic heat is based on the flow of electricity through a product. The purpose of this study was to investigate the effect of voltage and weight loss on the amount of energy and exergy during this process in order to obtain the best amount of energy consumed during the heating process, since the most common way to heal the heating is by heating. In addition to maintaining the product's qualitative characteristics, the product has to carefully monitor its own system parameters.
Materials and Methods
The sour oranges were purchased from a garden located in the city of Gorgan, Golestan province. The prepared oranges were washed and divided into two halves in the middle and immediately after purchase, all samples of juice were taken manually in the same conditions and the samples were prepared to conduct the test during the ohmic process with voltage gradients and the percentages of different weight loss to investigate the amount of energy efficiency, exergy efficiency, exergy loss, and improvement potential during the process. For the heating process, three voltage gradients of 8.33, 10.83 and 13.33 V cm^-1 and three percentage values of weight loss of 10% (from 90 g to 81 g), 20% (from 90 g to 72 g), and 30% (from 90 g to 63 g) were selected. Then, the energy and exergy consumed during the process were calculated and analyzed using a factorial experiment in a completely randomized design with SAS statistical software.
Results and Discussion
Based on the results, it can be concluded that the voltage gradient and weight loss percentages are significant for energy efficiency, exergy efficiency, exergy, and potential improvement at 1% level. Increasing the voltage gradient increases the efficiency of energy and exergy and reduces the potential for recovery and exergy is wasted. The highest energy efficiency was 91.6% in the 13.83 V cm^-1 voltage gradient and the weight loss percentages 10% and the lowest value was 51.51% in the voltage gradient of 8.33 V cm^-1 and the weight loss percentages 30%. The maximum improvement potential was 8.33 V cm^-1 and the weight reduction was 30% and the lowest value was at 13.33 V cm^-1 voltage gradient and 10% weight loss percentages. The highest exergy efficiency of 59.51% was found in the 13.83 V cm^-1 voltage gradient and the weight loss percentage was 30% and the lowest value was 31.88% on a voltage gradient of 8.33 V cm^-1 and a weight percentage of 10%.
Conclusion
- By increasing the voltage gradient, the energy efficiency had increased and there was a significant difference between all the volatility gradients.
- For exergy efficiency, when the voltage gradient increased, the exergy efficiency amount increased, and in all percentages weight loss was a significant difference between the voltage gradient.
- By increasing the voltage gradient, the amount of exergy loss decreased significantly and with increasing percentage weight loss, this amount was significantly increased.
- The improvement potential was reduced by increasing the voltage gradient and there was a significant difference between the voltage gradients for the improvement potential.

Abstract Nowadays, the dielectric properties of food and biological products have become a valuable parameter in foodstuff engineering and coating technology, covering a remarkable spectral domain from 10-6 to 1012. In the present study, 27 completely healthy pears were selected and subjected to quasi-static and dynamic loading. The storage period was ten days. In this study, the qualitative characteristics and their relationship with changes in dielectric coefficient were investigated. At the end of the storage period, the fruits’ dielectric coefficient values and their qualitative characteristics were measured. The measurements were carried out for a capacitor plates’ distance interval of 11 cm, 10 V input voltage and 60 kHz input voltage frequency. According to the results, in the dynamic loading mode of 400 N, the highest dielectric coefficient with a value of 5.2989 was obtained. In dynamic loading mode of 400 N, the qualitative property had the minimum value. The antioxidant, phenol content, Vitamin C content and firmness were 33.925%, 14.523 mg/100g, 5.7 mg/100g and 5.5333 g, respectively. The results of the study indicated that increasing the loading force on the pear reduces all qualitative indicators for all loading modes and an increase in dielectric coefficients of the products was observed.

Abstract Introduction
One the most important discussions of the world community is the importance and the role of edible oils in the nutrition and physical health of individuals, especially in the prevention of cardiovascular disease. One of these oils, used in cooking, is cow ghee. Cow ghee should be free of vegetable oil, animal fat, mineral oils, flavored additives and any other external ingredients. It is hard to find a technique that can easily and reliably measure the quality of the oil. So far, no special machine or system has been designed or built to distinguish the pure cow ghee from the adulterated ones. Electronic nose is a new method that has recently been considered by researchers in agriculture especially in the field of food quality. Because of high ability of e-nose system, in this research, this system was used for the detection of pure cow gee from the adulterants ones.
Materials and Methods
An olfactory machine system based on eight MOS sensors was designed to detect pure cow ghee from the adulterated with various proportions of vegetable oil and animal fat. Designed system includes data acquisition system, sensors, sensors chamber, sample box, power supply, connections, electric valves, air pump and air filter. The sensor array was consisted of the 8 MOS sensors that each of them react to specific volatile compounds. These sensors are widely used in olfactory machines because of their high chemical stability, high durability, low response to moisture and affordable prices. These are the most commonly used sensors in electronic nose system. To prepare samples with different percentages of adulteration, animal body fat and refined vegetable oils were added to pure cow ghee. In order to carry out the experiments, the sample was placed in sample box and in the baseline correction step (200 seconds), clean air was passed through the sensors to transmit the response of sensor array to steady state. At the injection step (180 seconds), the sample headspace was transmitted and passed through sensors chamber.  Output voltage of each sensor depends on the type of sensor and its sensitivity. At the cleaning step (120 seconds) the clean air was passed through sensors to get the sensor array responsive to a stable state. Also, at this step the pump removed the odor remaining inside the sample container and system was prepared for the next test. The signals obtained from the sensors were recorded and then pre-processed.
Results and Disscussion
PCA and QDA analysis were used for detection the differences between pure cow ghee and adulterated ones. The data obtained from the signals processing with fractional method were used as input of PCA. The PCA results showed that the total variance between pure cow ghee and mixture of cow ghee with animal's fat was 97%. Also score plot of cow’s ghee and its mixture with vegetable oil showed the total variance of 96% between different samples. Sensors are the main components of an electronic nose system therefore it is necessary to select the best sensors to detect differences between samples. The loading plot was obtained to show the role of sensors in e-nose system and demonstrates that the selected sensors have a high degree of complementarity. Based on confusion matrix obtained from QDA analysis, pure samples were detected from vegetable oil and animal fat samples with correct classification rate of 95.24 and 97.15, respectively.
Conclusion
An eight-sensory olfactory machine system (MOS) was designed to detect pure cow ghee from the presence of vegetable oil and animal fat oil. In PCA analysis, the variance between samples was 97% and 98%, respectively. According to the results the radar graph of PCA analysis, it can be concluded that the sensors No 2 (TGS822), 3(MQ136), 4(MQ9) and 8(TGS2620) have the highest and sensor 6 (MQ135) has the lowest ability in classification. The MQ135 sensor reacts to the detection of ammonia, benzene, and sulfide. In other words these gases did not play important role in separating of cow ghee from other mixed oils.

Abstract Introduction
The most costly part of poultry breeding is feeding. Due to the noticeable developments in animal husbandry and agricultural sectors, it is necessary to use the mechanized methods to reduce the casualties, increase the productivity as well as reduce the time and cost in each of these sectors. Reducing the particle size is one of the ways to process cereals which improves the mixing and also the nutritional value of the feed and the quality of the pellet feed. Optimizing the performance of hammer mill with the aim of reducing the size of different materials for poultry feed, would be very beneficial for obtaining the minimum cost of food, maximum quality and capacity. The main objective of this research was to optimize the operational variables, including sieve size, grain moisture content, feed rate and the number of hammers, each of them at three levels, on a hammer mill during the process of poultry food production from wheat, corn, barley and soybean grains.
Materials and Methods
The seeds used in experiments were wheat (Azar2 variety), corn (Brazilian variety), soybean (Danpars variety) and barley (Aras variety). A laboratory hammer mill was used to perform experiments. The treatments including sieve diameter (2, 2.3and 4.4 mm), grain moisture content (10, 14 and 18%), seed input rate to milling compartments (one-third, two-thirds and fully openness of tank gate) and the number of hammer (12, 18 and 24) were investigated. In order to measure the working capacity of the hammer mill, the required time for milling was recorded. The amount of final milled crop in each experiment was weighed and divided into the needed time for milling. Sieve analysis was used to determine the distribution and dispersion of the milled material which works according to the standard of ASTM E-11-70 Part 41 (Anonymous, 2004). In this study, the effects of input variables were investigated using the response surface method focusing on the central composite design approach to optimize the fineness degree and working capacity of the mill. The Design Expert 8.0.6 software was applied for statistical analysis, modeling and optimization.
Results and Discussion
The results indicated that sieve size and the number of hammers have been affected by the fineness degree of wheat grains, significantly. In addition, all four factors and interaction effects between sieve size and moisture content and also moisture content and number of hammers influential working capacity at the significant level of 1%. In the case of corn, the influence of moisture content and its interaction with sieve size on grain fineness, and the effect of sieve size, moisture content, feed rate and interactions between sieve size and moisture content and moisture content and feed rate of working capacity were significant at the level of 1%. For barley, moisture content at the level of 1% and interaction between sieve size and moisture content at the probability level of 5% were effective on barley fineness degree. Meanwhile, the moisture content at the level of 1% and sieve size and its interaction with moisture content at the level of 5% influenced working capacity, significantly. Soybeans were not able to respond the required moisture level for the experiments due to their soft and brittle texture, whereas unreliable results were obtained by changing its moisture levels. The best size of sieve holes, grain moisture content, feed rate and the number of hammers were determined to minimize the fineness degree and maximize the working capacity of the hammer mill.
Conclusion
In this research, the response surface method considering a central composite design was used to optimize the operational variables of a hammer mill, including sieve hole size, grain moisture, feed rate and the number of hammer to produce poultry feed with the aim of achieving a minimum fineness degree (more grain crushing) and maximum milling capacity. The results of variance analysis were presented for wheat, corn, barley and soybean. Regression models could represent the relationship between the independent variables and the outputs with high confidence coefficient, and the best values of input variables were determined to optimize grinding operation.

Abstract Introduction
Dracocephalum moldavica L. is an annual plant with blue or white flowers and fragrant leaves which belongs to the family of Lamiaceae with the height of up to 80 cm. This plant is native to Central Asia and is accepted in Central and Eastern Europe. In Iran, it is mainly grown in the province of West Azarbaijan and the Alborz Mountains. The essential oils and extracts derived from the secondary metabolisms which are mainly used in the pharmaceutical industry, dietary, cosmetic, flavoring and also as tea and beverage with sugar or honey. The liquid extract of the herb contains a high percentage of water, which should evaporate to increase shelf-life, easy transport, handling and storage, the ease of standardization and preservation of the product quality. On the other hand, the active compounds of the extracts are affected by temperature, oxygen, light and enzymes. Therefore, because of the uses and benefits of herbal extracts, they need to be dried by a practical and effective method like spray drying. In literature still there are no studies taking into account to the comparisons between RSM and TOPSIS as two important optimization methods. So, as the main objective of the present work, the effects of moisture content, drying performance, total phenol content, total flavonoid content and antioxidant activity have been surveyed. Finally, the optimal point of each process variable was presented by two optimization methods.
Materials and Methods
Aerial parts of Moldavian balm plant were cleaned and drying of plant was carried out under shade and thin layer conditions. The extraction of Moldavian balm was obtained by maceration method using ethanol 50 % (v/v), plant to solvent ratio of 1/10 (w/v). After 48h, the extract was concentrated in a rotary evaporator (Buchi Rotavapor R-205, Switzerland) to obtain a solid concentration of 6%. The used carrier was: Maltodextrin and apple pectin. Different ratios of carrier were prepared, then the ratio was added to distilled water and stirred by a magnetic stirrer. Finally, the solution was mixed with extract. The drying of Moldavian Balm plant extract was performed using a spray-dryer (Büchi B-191, Switzerland) with co-current flow regime. The powders provided by the spray drying were stored in refrigerator until they were needed for the experiment.
Results and Discussion
The results of variance analysis showed that the Box-Behnken design with the second-order model has led to the meaningfulness of the model, insignificant of the Lack of Fit and the appropriate correlation coefficient for each of the responses. A total number of 15 experiments were conducted to investigate the effect of process variables such as inlet air temperature, compressed air flow rate and concentration of carriers on moisture content, drying performance, total phenolic content, total flavonoid content and antioxidant activity of  Moldavian balm powder. Inlet air temperature and compressed air flow rate had the most significant effect on moisture content and drying performance, while Chemical properties of the powder affected by changing the concentration of carriers.
Optimization parameters of the spray drying process was performed using surface response and TOPSIS methods. The optimum predicted conditions in the response surface method and TOPSIS method were obtained at inlet air temperature, compressed air flow rate and concentration of carrier (152.5-150°C), (8.046-7.5 lit min^-1) and 20%, respectively.
Conclusion
By comparing two methods, it can be concluded that although they could provide the same optimum points, the RSM is more efficient. Because RSM offers a mathematical model that can be used at any desired point of variables to predict the output quantities as well as describing the process trend, while TOPSIS method is unable to predict the process trend and only provides the ranking of alternatives.

Abstract Introduction
In recent years, with increasing population growth and improving livelihoods, the consumption of vegetable oils has been increasing and has led to an increase in the level of oilseed cultivation. Sesame (Sesamum indicum L.) is an economically important crop which is widely cultivated all over the world. Sesame has been considered as an oil plant for cultivation in Iran's climatic conditions recently. Sesame contains about 58-44% oil, 18-25% protein and 13.5% carbohydrate. Sesame is grown mainly in the developing tropical and subtropical areas of Asia, Africa. The three countries of China, India and Myanmar are accounted as the largest producers of this product in the world. Screw pressing is the most reliable method for extracting oil from oilseed grains. This method is simpler than others and is more efficient in terms of cost and food security. The general objective of this research was to investigate the effects of rotational speed, temperature, type of screwing and die diameter on the amount of oil extraction from sesame oil and prediction of oil extraction using artificial neural network and compare to regression models.
Materials and Methods
In this research, a sesame oil extractor machine was designed and manufactured. Various experiments were carried out to determine the amount of oil extracted based on variable parameters such as the shape of the press screw, the rotational speed, the temperature and the diameter of the die. The experiment was performed at three levels of press screw type (constant pitch, variable pitch and conical), temperature (30, 60, 90), three levels of rotational speed (20, 50, 80 rpm) and three level of die diameter (6, 8, 10mm). The experimental design was factorial based on completely randomized design with three replications. The mathematical software (Matlab, 2012b) was used to determine the optimal neural network. The type of network was Multi-Layer Perceptron (MLP). In order to design this network, there were 3 neurons in the first layer (input), which was equal to the number of studied variable parameters (type of screw, rotational speed and temperature), the second layer was hidden layer, and the last layer (the output) had a neuron for the extracted oil) was equal to the number of outputs examined in this network. The Levenberg-Marquardt algorithm (LM) was used to train it, which is one of the fastest neural network training methods. The Second-order polynomial regressions were performed based on the step-by-step method and non-meaningful sentences were eliminated from the model. The accuracy of the models was determined by calculating the correlation coefficient and root mean square error (RMSE) indices.
Results and Discussion
The results of the experiments showed that the effect of type of press screw, rotational speed, extraction temperature and die diameter on the amount of oil extraction was significant (p≤0.01). The highest amount of extracted oil was obtained at conical press screw , rotational speed of 50 rpm, temperature of 60 °C and die diamter of 6 mm. An artificial neural network of three-layer perceptron and regression models were used to predict the amount of sesame oil extracted. The results showed that the artificial neural network model (1-8-3) with a correlation coefficient of 97.47% and a RMSE of 0.65 compared to linear regression and quadratic regression models had the higher efficiency in predicting the amount of extracted oil.
Conclusion
In this study, the effect of temperature, rotational speed, press screw type and die diameter on the amount of extracted oil were investigated. The results of this study showed that the change in the type of screw, rotational speed, diameter of die and temperature on the amount of extracted oil was significant at 1% level. Results also showed that the artificial neural network method was more efficient than linear and second order regression methods.

Abstract Introduction
Fruits and vegetables play an important role in food supply and public health. This group of agricultural products due to high humidity are perishable and most of them (5 to 50 percent) waste during post-harvest operation. Decreasing and minimizing such waste as "hidden harvest" could be an effective way to save food and increase profitability. Despite the surplus of the fruit production in the country, our position in terms of exportation is not commensurate with production, so measurements and grading on the basis of qualitative parameters such as firmness, taste, color, and shape can influence the marketing and export of fruit. In this research, application of an acoustic test is considered to achieve an effective and economic technology in the field to determine the stiffness of kiwifruit in post-harvest step. The aim of this study is to investigate the stiffness index of kiwifruit and provide a classification algorithm in the post-harvest step by using the non-destructive method of processing impact acoustic signals.
Materials and Method
In this research, an acoustic-based intelligent system was developed and the possibility of using the acoustic response to classify kiwifruit into soft, semi-soft and stiff categories was studied. 150 samples of Hayward variety of Kiwifruit was used during the 18 days shelf life in controlled conditions of temperature and humidity. Analyses were done in 9 sets per two days. In each analysis, an acoustic test was done by 48 samples in both free fall condition and fall from a conveyor belt. The feature extraction of acoustic signals in both the time domain and frequency domain has done, then the classification of samples was done by using the Artificial Neural Network. After getting the impact signals of stiff, semi-soft and soft samples, stiffness of kiwifruits identification has done by using acoustic features. The stiffness of kiwifruit samples in this study was measured to be 15.9±4.9 (N) by using the Magnes- Taylor test. Finally, samples were classified into stiff, semi-soft and soft by comparison of maximum force and flux of signals amplitude.
Results and Discussion
The results showed that the features of CF and maximum amplitude in the time domain have high accuracy in kiwifruit classification. The frequency resonances as environmental noises or impact position are out of control in the time domain which causes a decrease in accuracy. So, the ANN by features of time domain has not the acceptable capability to identify the semi-soft samples. The identification of semi-soft samples is not easy because of having same properties of stiff and soft samples. Extracted features of frequency domain have the most capability of correct detection. The optimal network has five neurons in the hidden layer and 0.014782 of mean square error. The accuracy of correct detection of the optimal network was 93.3, 91.3 and 78.3 percent for stiff, semi-soft and soft samples, respectively. Because of using more features in the frequency domain, the classification of all categories was acceptable and identification of semi-soft samples was as good as stiff and soft samples. The results of combined features of time and frequency domain showed that the artificial neural network has less efficiency in comparison with the other two attitudes. The accuracy of identification and classification was decreased by adding the extracted features of the time domain. So achieving the most accuracy in classification is accomplishable just by using the features of the frequency domain. By comparing the results of both free fall and online tests, it is claimed that this research can be industrialized.
Conclusion
Comparison of all results shows that there was no significant difference in the capability of ANN for identification and classification of the sample in three categories. After all, we can use this method in online sorting of kiwifruits by controlling the vector and position of impaction.

Abstract Introduction
Grape fruit set its fruits and shortly after planting and due to high nutritious value and excellent food quality has been welcomed by many people in the world, but considering its soft tissue and high softening velocity and sensitivity to fungi attack it is known as an extensively vulnerable fruit. One of the most important ways to maintain fruit quality, decrease vulnerably and assist more appropriate storage, is the use of coating method and proper packing of agricultural products and combining these procedures to decrease damages in storage. Edible coatings provide a replacement and fortification of the natural layers at the product surface to prevent moisture losses, gas aromas, and solute movements out of the food, while selectively allowing for controlled exchange of important gases, such as oxygen, carbon dioxide, and ethylene, which are involved in fruit respiration. Chitosan is the most common polysaccharide-based coatings. Chitosan films have been successfully applied as edible material in films and coatings for the quality preservation of different fruit. In this study, the effects of the application of chitosan edible coatings and storage time on some physical, chemical, mechanical and rheological properties of grape were investigated during storage.
Materials and Methods
Grape fruits were screened for physical damages, fungal infections, and size homogeneity after harvesting from the farm. Then fruits were divided into without coating and fruits with coating. Fruits being coated, prepared in chitosan emulsion and submerged for two minutes and kept at 20°C for one hour for drying the surface coating via airflow. In order to calculate the weight loss, three containers of each grape fruits (treatment and control) collected and after weighing and averaging weight loss were compared to initial weight during storage expressed as a percent. Color intensities were determined using colorimeter samples. In order to determine soluble solids from each sample, refract meter was used and pH amount of each sample was determined. Mechanical traits and fruit stiffness were measured through penetration test using materials test machine Zowick/ Roell having 500 N loadcell in line with the small diameter with concave probe (5 mm diameter), the penetration depth of 2 mm and loading rate of 10 mm s^-1. Mechanical traits including stiffness and elasticity module calculated from the force-deformation curve. Viscoelastic materials have the properties of both viscous and elastic materials and can be modeled by combining elements that represent these characteristics. A viscoelastic model, called the Maxwell model which can predict behavior was evaluated.
Results and Discussion
In this current study, the application of chitosan coating significantly reduced the fresh grape decay. Fruit decay of grape increased with storage time, but the coating reduced the rate of decay with the length of storage. According to the results, the application of these coatings has a positive impact on yield stress and energy of rupture product texture during the storage. Results of variance analysis showed that temperature, coating and storage time has a significant effect (1% level) on some of the engineering properties of the grape. Storage time has a significant effect on elasticity, while the coating does not have a significant effect on this parameter. Finally, results showed that the application of chitosan coating has an effect on relaxation time and stress. So during storage of coated samples these parameters decreased compared to uncoated.
Conclusion
Edible films and coatings may reduce the moisture transfer, the rate of oxidation and respiration which are considered important to prolong the shelf-life of these products. This investigation showed that the chitosan coatings are effective for grape shelf life extension and retarded the senescence process compared with control. The coat has been as a physical barrier for the gas exchange between the fruit and the environment. It was demonstrated that the coating reduced the loss of firmness and delayed the softening of fruit and texture change.

Abstract Introduction
High energy consumption and non-uniformity drying in conventional batch type dryer are the common problems in paddy dying industry. Non-uniformity drying causes to kernel breaking chance in the milling process. Using new dryers with better performance can solve the drying problem and energy saving. In this research, the operation of a re-circulating batch dryer was compared with a fixed bed batch dryer (conventional dryer) for paddy drying.
Materials and Methods
This research was done in a paddy milling factory in Ferydonkenar and deputy of Rice Research Institute of Iran, in Amol, Mazandaran province. Both re-circulating dryer and conventional batch type dryer were made by Khazar Electric Company in Amol- Iran and they had 5 tonnes capacity. In the re-circulating dryer, ambient air was warmed in the furnace and blown to drying zone inside of grain bin. Natural Gas (NG) was used for air warming in dryers. Warm air absorbed paddy moisture and pushed away from the dryer. Drying temperature ranges for re-circulating dryer and conventional dryer was 48-50 °C and 38-52°C, respectively. The paddy variety was one of the Iranian rice varieties as Tarom and initial moisture content of grains was 21% (w.b), it was decreased using drying to 8-9% (w.b) for milling process. Paddy moisture content was measured each 60-120 min by SUNCUE TD-6 portable moisture tester-Taiwan. Energy consumption calculated by fuel and electrical energy summation in each experiment. Natural Gas and electrical power consumption were measured by Gas and electric counters respectively.
Drying time, paddy moisture change trend and energy consumption were investigated for paddy drying in each dryers. Also, milling ratio, breaking percent, whitening degree, and elongation rate after cooking were studied after the milling process for rice dried using national standard methods and deputy of Rice Research Institute facilities in Amol. Experimental samples were 150 g and husker (SATAKE THU35B), a whitener (SATAKE TMU05) and KETT C-100 were used for husking, whitening and whiteness degree, respectively. All Experiments were done with three replication and data analyzed using T- student method in 5% probability. 
Results and Discussion
Results showed that re-circulating dryer caused to reduce 54.12 percent in drying time and energy saving in paddy drying in compare with conventional paddy dryers. The trend of moisture content changes was longer and over-drying occurred in lower layers in conventional batch type dryer compared to re-circulating dryer. Paddy drying was 20 hours more in batch type than the re-circulating dryer. It caused wasting time and energy consumption. Specific energy consumption for water evaporating in the re-circulating batch dryer was 3.9 MJ/kg water and it was 76.25 percent less than fixed bed batch dryer.  After the drying process in both dryers, paddy moisture content was in range 8-9 percent (% w.b). Using re-circulating dryer did not have a significant effect on milling yield but it had a significant effect on broken rice. Broken rice decreased by 5 percent after the milling process when paddy dried by re-circulating. Uniformity of layers drying and normal heat stress in rice kernels in re-circulating dryer reduced broken rice in the milling process. Whiteness degree of rice dried using fixed bed dryer was 2.4 percent more than the re-circulating batch dryer. Also, rice dried had more elongation rate about 6.2 percent after cooking when paddy dried by conventional dryer. 
Conclusion
Results of this paper showed that using of re-circulating dryer would decrease time and modify energy consumption in paddy drying. The costs of installation for the re-circulating batch dryer was about 5.3 times more than fixed bed batch dryer. It seems too expensive at first but considering energy and time-saving in the drying process and suitable effect on decreasing grain breakage in paddy milling, using of the re-circulating batch dryer is recommendable in rice milling factories.

Abstract Introduction
Rice is one of the most important cereal grains in the world. Milling is one of the most important phases of the paddy processing that affects the quality and quantity of the product. Postharvest losses include threshing, drying, transportation and milling contains about 30–40% of total produced rice in developing country. Parboiling increases the mailing efficiency of rice from 51% to 80%, protein, fat and ash content. Champa variety is one of the most important varieties of rice in the southwest of Iran and has low milling quality in spite of its flavor and aroma. This study was conducted to assess increasing the quality of Champa rice milling phase by parboiling method.
Materials and Methods
This study was conducted to‏ assess the increasing quality of Champa rice milling phase by parboiling method in the growing season of 2016 in Lordegan city. Paddies were prepared from a rice farm in Lordegan city. Parboiling treatments consisted of three soaking temperatures (35, 55 and 75°C) and two steaming times (15 and 25 minutes) at a steam temperature of 110 °C. This study was performed in a factorial experiment based on a completely randomized design in three replications. Parboiling process included soaking, steaming, drying and whitening. Bain Marie was used to keep the water temperature constant in two phases of soaking and steaming. Samples were placed in a oven to decrease the humidity in the drying phase. Breakage percentage, loss of solid material, milling efficiency, whiteness degree and the ratio of length to width were measured in raw and baked rice in all samples.
Results and Discussion
Breakage in control treatment (non-parboiling) was 19.38%. The lowest breakage percentage (4.03%) was obtained in parboiling treatment (soaking temperature of 55 °C and a steaming time of 15 minutes). Parboiling improved milling efficiency and reduced loss of solid materials. Highest milling efficiency (67.11%) was obtained in a soaking temperature of 55 °C and steaming time of 25 minutes. The lowest amount of loss of solid materials (1.74%) was obtained in a soaking temperature of 75 °C and steaming time of 25 minutes. The highest ratio of length to width (2.46) and the highest whiteness degree (76.54%) was obtained in no parboiling treatment. There was no significant difference in water absorption parameter between parboiling treatment and non-parboiling treatment.
Conclusion
Champa rice variety has a very good flavor and aroma but did not have good appearance and its breakage percentage is not good. Parboiling reduces the breakage and improves the appearance in raw and baked rice. Parboiling had a lot of positive effects on the milling quality of this rice cultivar. The best treatment (soaking temperature of 55 °C and steaming time of 25 minutes) reduced breakage percentage (by 79%) and loss of solid materials (by 37%) and increased milling efficiency (by 2%) in comparison with control treatment (non-parboiling). Overall, parboiling reduced rice streaking during baking by improving the quality attributes of paddies and finally improved the rice shape.

Abstract Introduction
During filling a silo, granular material containing a range of particle sizes, the fine material accumulates under the filling point. The inclined surface of stationary bed particle which is formed in silos during filling process acts similar to a sieve through which the smaller particle fall. This effect is called sifting. As a result of the mentioned effect, much finer particles form a vertical cylindrical zone of high concentration at the silo center. For optimal design in industrial process such as aeration of stored products in silos, filling silos, and wherever granular materials are handled, it is necessary to survey the distribution of the fine materials depending on product and process properties. The objectives of present study were: (a) To study fine change as affected by substantial parameters, (b) To model fine changes at different conditions in silos.
Materials and Methods
In the present study, an experimental setup consist of a main container, elevator, trapezoidal container and experimental silo was designed and built. Fine content was defined by BCFM (broken corn and foreign material). By applying a new approach, sampling was performed in a radial and vertical direction. The position of each sampling point was determined with a scaled distance from center (R) and from bottom (Z). Local BCFM (BCL) was defined as the value of BCFM in each sampling point. Influential parameters namely, initial BCFM (BCI), volume flow rate (Q) and fill pipe diameter (DF) were considered as treatments. Non-linear regression technique was applied on the experimental data to predict the distribution pattern of fines into the pilot-scale silo. The most appropriate model in a try and error procedure was selected based on highest value of R2 and least value of χ2, RMSE and MRDM.
Results and Discussion
 According to the results of ANOVA, it was found that the effects of all parameters were significant at 5% probability. BCL decreased nonlinearly with a concave down decreasing trend along radial direction due to sifting effect. As a result, most amount of fines remained in the sections closer to the center of the silo. Fine distribution became more uniform with decreasing Z and increasing BCI and DF. Also, the distribution of fine became more uniform with increasing Q. BCL was a nonlinear function of R and a linear function of Z, BCI, Q and DF. Although including more and complex terms increased the model complexity but in the present study considering BCL as an exponential function of R and as an implicit function of Z and R (ZR) improved the quality of the model significantly. The values of 0.94, 1.14, 1.06, 11.39 for R², χ2, RMSE and MRDM, respectively, gave the best model. The results showed, considerable accumulation of fines occurred at the center of the silo which increased with increase of level of Z. Also, low concentration of fine occurred at the periphery of the silo especially at higher levels of Z. It means that maximum non-uniformity of fine distribution occurred at higher levels of Z.
  Conclusion
The present study investigated distribution of fines during filling affected by main parameters namely, initial BCFM, volume flow rate and fill pipe diameter in a pilot scale silo. A new procedure was developed for measuring the fine material along radial and vertical directions. Distribution of fine was modeled using a developed equation considering the effects of main parameters. The results showed that distribution of fine becomes more uniform with decreasing height and increasing initial BCFM, volume flow rate and fill pipe diameter. 

Abstract Introduction
Long drying time and high energy consumption are the big problems in paddy drying using conventional batch type dryer. Besides, non-uniformity occurs in paddy rice dried and low milling quality. Paddy is over dried in lower layers and broken kernel chance increased in milling process. Using of a new pattern for warm air causes to better air passing through the paddy bulk and uniformity of drying. Computational fluid dynamics (CFD) is a good method for modeling of air passing in dryers in order to find better air condition in paddy drying process. The aim of this research was investigation on common and porch patterns applied for air entrance to paddy bulk in a dryer in order to optimize air channel conditions in a conventional paddy dryer.
Materials and Methods
In this study, optimization of air flow was investigated in a batch type paddy dryer using computational fluid dynamics (CFD). Two patterns as conventional and porch (reverse V type) patterns were applied for air entrance to paddy bulk in the dryer as conventional and porch (reverse V type) patterns. Experimental examination were done using a laboratory batch type dryer with chargeable air flow pattern in 50 °C for drying paddy (Tarom-Hashmei Var.). Numerical simulation of air velocity and pressure drop in porous media of paddy in the dryer was achieved by employing computational fluid dynamics method and Fluent software. Air velocity pattern and temperature changes in bulk of paddy were investigated in different time of solution including 20, 100, 1000, 1800, 3600 and 7200 seconds for both patterns.
Results and Discussion
Considering air flow and temperature as constant, the results showed the porch type pattern has better performance than the conventional pattern for air passing in the dryer. The velocity vortex was higher in all parts of the channel in the porch scheme. Air velocity uniformed decreased from beginning to end area in the conventional pattern, but in the porch type pattern, air velocity was more in the end of the duct than beginning area. Pressure drop was about 10 percent in the conventional pattern than porch pattern. At the end of the air channel, this variation inversed due to contact of the air with the end wall and pressure drop in this part of the chamber of porch scheme was higher than the conventional one. Improvement of air flow in paddy occurred in low and middle layers in the porch type pattern and there was no difference between two air passing patterns in top layers. Validation of modeling showed that temperature disturbance of the porch model was more uniform than the conventional model and difference between temperatures of model and experiments was about 2 to 3 °C.
Conclusion
The research concluded that using of the porch type pattern had better performance than the conventional pattern for air passing in the dryer but it is needs to more supplementary research to find the best height and angle in the paddy dryer. Porch type pattern causes to more speed and uniformity of air among of paddy than the conventional pattern. This improvement observed in low and middle layers of the paddy bulk. Validation of temperature data showed that the difference between experimental and modeled data was 4 to 6 percent and this difference was higher in the conventional pattern than the porch pattern. According to the results of this research, Porch pattern can be recommended to use in the conventional batch type dryer.  

Abstract Introduction
Garlic (Allium sativum L.) is an important Allium crop in the world. Due to its therapeutic properties, it was cultivated in many countries. Furthermore, garlic is usually used as a flavoring agent; it may be used in the shape of powder or granule as a valuable condiment for foods. In addition to its use in food products, it was also widely used as an anticancer agent. Shallot (Allium hiertifolium Boiss. L) is a perennial and bulbous plant. It is from Alliaceae family and is an important medicinal plant. The shallot is native of Iran, and grows in the high pastures. Shallot is consumed in dry areas in most parts of the country. Also shallots have been well known in Iranian folk medicine and its bulbs have been widely used for treating rheumatic and inflammatory disorders. In addition, this plant is used in the preparation of significant amounts of potassium, phosphorus, calcium, magnesium, sodium, pickles and as an additive to yogurt and pickles. ANN as a modern approach has successfully been used to solve an extensive variety of problems in the science and engineering, exclusively for some space where the conventional modeling procedure fail. A well-trained ANN can be used as a predictive model for a special use, which is a data processing system inspired by biological neural system. When mathematical equations are difficult to extrapolate, and fuzzy logic is better when decisions must be made with the estimated values below the incomplete information. The fuzzy logic theory effectively addresses the uncertainty problems that solve the ambiguity.
Materials and Methods
 The aim of this study was to predict moisture ratio of garlic and shallot during the drying process with fluidized bed dryer using mathematical model, artificial neural networks and fuzzy logic methods. Tests were carried out on three levels of inlet air temperature (40, 55 and 70 °C) and three inlet air velocities (0.5, 1.5 and 2.5 m s^-1). To estimate the drying kinetic of garlic and shallot, five mathematical models were used to fit the experimental data of thin layer drying. Three factors (air temperature, air velocity and drying time) to forecast moisture ratio in fluidized bed dryer as independent variables for artificial neural networks and fuzzy logic was considered. Cascade forward back propagation (CFBP) and feed forward back propagation (FFBP) with Levenberg-Marquardt (LM), Bayesian learning (BR) algorithms for ANN and the Mamdani Fuzzy Inference System using triangular membership function were used for training patterns.
Results and Discussion
Consequently, the Page and Midilli et al. model was selected as the best mathematical model to describe the drying kinetics of the garlic and shallot slices, respectively. The results of artificial neural networks model for predicting MR showed that the R² of 0.9994 and 0.9996; and and RMSE of 0.0036 and 0.0014 were obtained for garlic and shallot, respectively. Also, The fuzzy inference system presented the R² of 0.9997 and 0.9998; and and RMSE of 0.0027 and 0.0011 for garlic and shallot, respectively. Comparing the results obtained from mathematical models, artificial neural networks and fuzzy logic, showed that the RMSE in the fuzzy logic was lower than artificial neural network and mathematical models.
Conclusion
Three factors (air temperature, air velocity and drying time) were considered for forecasting moisture ratio in fluidized bed dryer as independent variables using mathematical model, artificial neural networks and fuzzy logic. Cascade forward back propagation (CFBP) and feed forward back propagation (FFBP) with Levenberg-Marquardt (LM), Bayesian learning (BR) algorithms and the Mamdani Fuzzy Inference System using triangular membership function were used for training the patterns. Comparing the results obtained from mathematical models, artificial neural networks and fuzzy logic, showed that the root mean square error in fuzzy logic was lower than others.

Abstract Introduction
Convective air drying is one of the oldest and most popular drying methods. Designing and controlling the convective air drying needs the mathematical description of the moisture transfer during the drying process, known as drying kinetics. Fick’s second law of diffusion can be used for modelling the moisture distribution inside the moist object during drying process.
Mathematical modeling of drying process is a very important tool, as it contributes to understand better moisture distributions inside the product which helps designing, improving and controlling drying operation in the food industry.
Implementation of the partial differential equations subject to the correspondent initial and boundary conditions is one of the main methods of mathematical modeling to describe the physical phenomena such as moisture transfer during drying. In the recent decades, considerable number of research works have been devoted to numerical solution of mass transfer phenomena during convective drying of food products by using the common numerical solution such as FDMs, FEMs and FVMs.
The spectral collocation (pseudospectral) methods is a powerful tool for the numerical solutions of smooth PDEs like mass transfer equations. Pseudospectral methods are able to achieve the high precision with using a small number of discretization points compared to FDMs and FEMs and with low computational time and computer memory.
The objective of present research is to simulate the mass transfer phenomena in one dimension during convective drying of apple slices. The validation of the presented numerical model was done by comparing experimental drying data taken from Kaya et al. (2007) and Zarein et al. (2013). For more confirming the numerical approach, a numerical example with the exact solution is provided and the related errors were evaluated.
 
Materials and Methods
Estimation of mass transfer coefficients
The convective mass transfer coefficient in the surface of the apple slice was obtained according to the relationship presented by Paitil (1988) and Janjai et al. (2008).
    (1)  
 
Estimation of effective moisture diffusivity coefficient
Fick’s second law of diffusion was applied to obtain the effective moisture diffusivity coefficient of the apple slices. The analytical solution of this equation can be written as follows (Crank, 1975):
         (2)
In this study, we consider the Pseudospectral methods for solving 1D mass transfer equation. In order to develop the model, the following common assumptions are considered: negligible heat changes during drying process, moisture is transferred inside the slices by diffusion, one-dimensional mass transfer in apple slices, non-shrinkage and non-deformation of the slice.
Results and Discussion
In the field of numerical analysis, the main advantage of pseudospectral methods compared to others such as FDMs and FEMs are exponential convergence and sufficient accuracy (Sun et al., 2012). The values of parameters and coefficients of mathematical model are summarized in Table 1. The comparisons between the predicted average moisture content and the experimental data are shown in Fig. 1 & 2. It can be seen, the numerical results are in good agreement with the experimental data. The values of the correlation coefficient and the root mean square error from comparison of numerical result with experimental data taken from Zarein et al. (2013) and Kaya et al. (2007) were 0.9996, 0.0729 and 0.997, 0.1561 respectively. Moreover, the running time for solving 1D mass transfer equations was about 3 seconds. This result is the evident that the presented model is successful for predicting the moisture content history during drying process.
Moreover, by using the considered numerical method the approximate solutions of defined numerical example for different discretizing points was evaluated and the associated error history are shown in Figure 3. It can be seen that the values of errors are very low and about 10-3 and 10-5, that confirms the high accuracy, robustness and efficiency of the suggested numerical approach.
 
Conclusion
Spectral collocation (pseudospectral) method is presented to solve mass transfer equation in one dimensional in during convective drying process approximately. The model was validated by the reported experimental data from convective drying of apple slices. Also, a numerical example, which had an exact solution in a closed form, was provided to illustrate the high accuracy of the proposed method. The results of statistical computations (r and RMSE) and numerical example showed the efficiency, applicability and robustness of the presented approach.