Journal of Agricultural Machinery

Research Article Design and Construction

Design and Development of a Warning System for Seed Blockage in a One Row Grain Drill

O. Esmand; S. R. Mousavi Seyedi; D. Kalantari

Volume 11, Issue 2 , 2021, Pages 131-143

https://doi.org/10.22067/jam.v11i2.83159

Abstract

Introduction The use of new technology in planters is one of the most important factors in the advancement of agricultural science. In the present study, an electronic warning system has been designed and implemented to prevent large seeds from falling from the fall pipe into the ground groove. In this ... Read More Introduction The use of new technology in planters is one of the most important factors in the advancement of agricultural science. In the present study, an electronic warning system has been designed and implemented to prevent large seeds from falling from the fall pipe into the ground groove. In this study, three types of corn, bean and soybean seeds have been used, using two laser and microwave sensors. Viewing and comparison of the two sensors and their performance in two conditions of medium and high sensitivity in both laboratory and field conditions were conducted. In this case, the differences between the two sensors in different sensitivities have been evaluated and compared. The performance of the sensors in seed count has also been studied and compared. According to the results obtained in both cases, the sensors performance was acceptable, and especially in the maximum sensitivity of the sensors, they were able to handle well the clogs created in different situations (clogging down or above the fall pipe or emptying the seed tank). Detect and alert in a timely manner. Also, the count of seeds in all three seed types was recorded with high accuracy compared to the actual number. Materials and Methods Three types of coarse seeds (corn, beans and soybeans) as well as two types of sensors (laser and microwave) with two levels of medium sensitivity and high sensitivity were used for the experiments. Laser sensors are one of the most precise instrumentation and industrial automation tools that use laser light to detect objects or even precise distances. The function of the microwave sensor is that the high frequency waves are transmitted when the power supply is connected. These waves are reflected back to the module receiver if they hit objects. The open waves in the module are multiplied by the frequency of transmission by the mixer and a low-output (IF) signal is generated. The output frequency is equal to the difference between the frequency of the transmitted and reflected waves caused by the Doppler effect. Based on this frequency, the presence of a moving object and its speed are detected. Experiments were carried out at both laboratory and field levels and in both moderate and high sensitivity modes using variable resistance mounted on the controller. The equivalent distance for each seed test is 100 meters, so twice for each seed in the laboratory and field level for each of the laser and microwave sensors in both high and medium sensitivity modes. In this system, in case of falling pipe clogging due to seed accumulation or mud under the falling pipe or other factors, an alert system (warning beep), along with the corresponding LED light, indicates a problem in the seed fall system and the operator alerts paying attention to the LED light (green or red) will detect the problem. Results and Discussion The results indicated that by installing a variable resistance inside the circuit, different sensors can be created in the sensors. Increasing the sensitivity of the sensor as much as possible can cause higher the efficiency of the sensor. In the two cases of medium and high resistance, sensors work with medium and high sensitivity. It works since both modes have been tested and the results have been satisfactory. The accuracy of counting and seed detection accuracy between two laser sensors and microwave sensors in two medium and high sensitivity modes were calculated and evaluated. The experiments in the laboratory showed that the difference in the number of seed count by laser sensor compared to the actual number in maize seed at medium and high sensitivity were 87.4% and 94.3%, respectively, in bean seeds 89.1% and 94.2%, respectively. And in soybean seed were 89.4% and 92.3%, respectively. Conclusion The developed embedded system can successfully check and announce the instantaneous state of three types of grain tested (corn, beans and soybeans) in the seed delivery tube of a hand single-row planter with visual cues (on or off LED lights) and audible signals (on or off the alarm), whenever there is a grain flow or no grain flow. Likewise, the developed system can show the blockage at the end of the seed delivery tube with visual indications of the green and red lights on or off and the alarm sound described in detail. These warnings are indications of a fall pipe failure or lack of grain flow in the grain measuring mechanism toward the opening groove and then into the ground. This type of detection alerts the operator in a timely manner by monitoring the status of the grains in the measuring system and ensuring that the grains are located in the ground.

Research Article Design and Construction

Designing and Constructing an Active Boom Balancing System using a New Technique Variable Fulcrum Method and Comparing It with a Conventional Sprayer

P. Pashaee; H. R. Ghasemzadeh; H. Behfar

Volume 11, Issue 2 , 2021, Pages 145-159

https://doi.org/10.22067/jam.v11i2.79786

Abstract

Introduction According to reports on trends in the agricultural industry, demand for more precise and affordable machinery is rising and precision farming methods used by farmers are expanding. Damping vibration of the boom sprayer is one of the challenges for researchers when crossing the surface roughness. ... Read More Introduction According to reports on trends in the agricultural industry, demand for more precise and affordable machinery is rising and precision farming methods used by farmers are expanding. Damping vibration of the boom sprayer is one of the challenges for researchers when crossing the surface roughness. The lack of uniformity of the nozzle spray pattern and the reduction of the precision and quality is the result of an uncontrolled vibration of the boom sprayer. So far, many efforts have been made to decrease the vibration of the long sprayer boom. Using active and passive methods, researchers have achieved great success in reducing the spray boom vibration. Many of these methods are based on the use of external force as a controlling force. Expensive equipment, the use of tractor hydraulic power, and high energy costs are the main disadvantages of these methods. In the present work, a new system called "variable support" was designed and built. The boom rests on a round bar at its midpoint; as the boom tends to oscillate, a minute amount of rotation of the bar activated by a servomotor in an appropriate direction, alters the position of the resting point of the boom on the supporting bar, bringing the boom back to its initial balanced position as a result.Materials and Methods To carry out experiments, the universal tractor U650 and a mounted tractor sprayer model tms500 with 8 m boom and a 500-liter tank, was used in this research by making changes to the design of the simple tractor sprayer a new active sprayer designed and built with intelligent online balancing system that in addition to balancing the boom angle, it reduced the fluctuations that occur during work. Electronic control was used to control the position of the boom. The microcontroller programming codes were developed and uploaded in the microprocessor to execute instantaneous commands to the mounted activator due to the need for boom positional data for analyzing experiments, a data logger was also designed in conjunction with the controller circuit and the algorithm was loaded after coding with C++. To compare the new sprayer with the conventional, a field test was conducted. Tests were carried out according to manufacturer's instructions at three-speed levels of 3 (low), 5 (medium), and 8 km h-1 (high), with three bumps heights of 10, 15, and 20 cm with three replications. For the acquisition of vertical acceleration as well as axial rotation data in the conventional sprayer, a data logger with an accelerometer and gyroscope was used. The data logging rate and the accuracy of the accelerometer and gyroscope measurement were set to 50 Hz, 0.1 m s-2 and 0.1°, respectively.Results and Discussion To compare the behavior of the active and the conventional spray booms in terms of vibrations, the univariate analysis was used. The results showed that there was a significant difference between the performances of two sprayers at 5% probability level with the sig. number of 0.000.To compare the behavior of the active and the conventional spray booms in terms of axial rotation, also the Univariate analysis was used. The results showed that there was significant difference between the performances of two sprayers at 5% probability level with the sig. number of 0.000. Also, comparing the marginal mean values of the data obtained from the data logger showed that the active boom compared with the conventional boom had less axial rotation and less vertical acceleration.Conclusion Results of experiments showed that the new sprayer with variable support system, relative to the conventional sprayer in terms of controlling boom acceleration and the angular balance of the boom with a significant difference had relative superiority and can be considered as an appropriate alternative to increase the accuracy of spraying, although more research on large scale booms are necessary before coming to final conclusion.

Research Article

Simulation, Development and Evaluation of an Autonomous Robotic Boat Used in Aquacultures

H. Abdolmaleki; A. Jafari; H. Mousazadeh; A. Hajiahmad

Volume 11, Issue 2 , 2021, Pages 161-171

https://doi.org/10.22067/jam.v11i2.78325

Abstract

IntroductionAs the world population grows up, the quantity and quality of human food must be improved. The production yield of marine aquaculture and farming of aquatic organisms, as a valuable source of food, will be increased. Regular and online monitoring of the physical, chemical, and biological ... Read More IntroductionAs the world population grows up, the quantity and quality of human food must be improved. The production yield of marine aquaculture and farming of aquatic organisms, as a valuable source of food, will be increased. Regular and online monitoring of the physical, chemical, and biological qualities of water and environmental parameters in such these controlled environments can be achieved by using advanced world technologies, such as autonomous boats. In this study, simulation of an autonomous boat has been done to help better understanding and control of this type of vessel in various environments such as dams, ports, rivers, aquatic ecosystems, and aquaculture. Hence, the main goal of this paper is to simulate and evaluate the guidance and navigation system of an autonomous boat based on the Fourth order of Runge-Kutta for determining the changes of water quality indices in a fish farming ponds.Materials and Methods In order to achieve the main goal of this study, an autonomous boat was designed and built. This boat as a general-purpose robotic trimaran boat has dimensions of 110 cm x 37 cm x40 cm and is made of Plexiglas 2 mm thick. Maximum forward speed of the boat is 125 cm s-1 (at 6850 rpm of brushless motors) and the turning radius is less than 61 cm. The environmental data can be transferred using Internet of Things (IOT), smartphones, SMS, and mini PC. The position and heading of the boat are determined using GPS and IMU data. The hydrodynamic and aerodynamic forces, moments, and coefficients of the boat model are determined and then applied in the mathematical simulation as the input of classic Runge-Kutta (RK4). The performance of the robotic boat navigational and control systems evaluated in a rectangular track with a length of 20 m and a width of 15 m in a fish farming pond in Karaj and 4 waypoints. The local coordinates of four corner of the mentioned rectangular in the pond was (0, 0), (0, 20), (15, 20), and (15, 0). The purpose of control system was to conduct the actuators in such way that boat be able to go to the next point. When the boat reaches the target distance of one m of the desired point, the next point will be introduced as a new target. The set point of boat speed was 0.4 m s-1 and zero state vector was [0, 0, 0, 0, 0, 0]. Results and DiscussionThe maximum error of position and heading of the autonomous boat is 135 cm and 11 degrees, respectively. Also, in the speed PID controller test (40 cm s-1), the average and standard deviation of the speed calculated as 40 cm s-1 and 2 cm s-1, respectively. Maximum difference between the heading obtained from the Kalman filter and received from the GPS is 11 degrees. In some situations that high precision of heading angle is not required, the GPS data can provide such accuracy of the heading. Among the variables of longitudinal, latitude, time to reach the target area, yaw rate, heading, and forward speed the minimum and maximum of percentage error are related to forward speed and yaw rate, respectively. These values show good performance of the simulated model and PID controllers.Conclusion In this study, motion simulation and evaluation of a robotic boat was carried out using a model boat and MATLAB software. The mathematical model simulated the real boat behavior correctly and the boat can be used safely in fish farming ponds to monitor environmental conditions and water quality.

Research Article Design and Construction

Effect of Parameters on the Separation of Almond Shell and Kernel, and Design and Development a Pneumatic Separator

V. Neisari fam; R. Tabatabaei koloor; A. Motevali

Volume 11, Issue 2 , 2021, Pages 173-185

https://doi.org/10.22067/jam.v11i2.81511

Abstract

IntroductionAlmonds (Prunus amygdalus) belongs to the family of Rosaceae and the subspecies of Pronoideae. Its kernel contains a lot of energy, amino acids, sugars and mineral elements. Iran is ranked fifth in terms of producing almonds after United States, Australia, Spain, and Morocco, but at the same ... Read More IntroductionAlmonds (Prunus amygdalus) belongs to the family of Rosaceae and the subspecies of Pronoideae. Its kernel contains a lot of energy, amino acids, sugars and mineral elements. Iran is ranked fifth in terms of producing almonds after United States, Australia, Spain, and Morocco, but at the same time, Iran's position is not very suitable in the world export market. The processing of this product involves three stages of shell breaking, kernel separation, and packaging. One of the important methods of separation of the kernel from the wooden crust is the use of pneumatic separation and this method can be used to grade, clean, and separate the seeds of different materials.Materials and MethodsAlmond samples of the Shokofeh variety (A.H.3) were obtained from Maragheh gardens in East Azarbaijan province. The moisture content of the shell, the kernel, and mixture of them was determined using the oven drying method. Also, some physical and mechanical properties were measured. In order to design the almond separator system, it is important to determine aerodynamic properties. The most important aerodynamic properties such as terminal velocity and drag force were determined. The first step in designing and manufacturing a device is to select the cross-sectional shape and dimension. The cross-section of the machine is selected based on parameters such as simplicity and construction costs. With the assumption of a machine with a separation capacity of 2 kg (mixed product) per minute, the length and the width of the machine were obtained to be 18 cm and 15 cm. Using the terminal velocity and dimensional data, the blower distance to the outlet, the tunnel length, the power and flow rate of the blower were calculated and then the design and construction were done. To evaluate the separation and evaluation of the apparatus, parameters such as blower speed, shell size, and moisture content of the mixture were investigated for each parameter at three levels. Airflow rates of the wind tunnel were 3, 5, and 7 m s-1, moisture content (7%, 13%, and 19%), shell size in three groups: small, medium, and large.Results and DiscussionThe average geometric properties including length, width, thickness, geometric mean diameter, and spherical coefficient for almonds were 20.64, 13.25, 7.4, 12.64 mm, and 0.612, respectively, as well as properties for large shells (25.17, 16.5, 11.15, 16.66 mm, and 0.66), for average size (17.36, 13.5, 6.4, 11.44 mm, and 0.65) and fine size (13, 9.9, 3.5, 7.66 mm, and 0.59), respectively. The mechanical properties of the samples (shell and almond kernel) were measured at three levels of moisture content of 7%, 13%, and 19%. The results showed that by increasing the moisture content, the fracture force for both shell and kernel increases. Almond shell had the highest angle of rotation at all levels of moisture. This was due to its heterogeneous shape, broken edges and rough surface. On the other hand, almonds had the lowest degree of rotation, due to the greater weight of the kernel and the more homogeneous and spherical shape than the shell. The results obtained from measuring the terminal velocity of the samples selected from the kernel and shell in terms of their weight indicated that the velocity limit for the almonds was 10.2-12.2 m s-1 and for the shell, the range was 1.8-6 m s-1. The variance analysis of the effect of particle size, velocity, and moisture parameters on the level of separation of shell in almond mixture showed that all major effects and interactions of factors were significant at 1% probability level. Particle size and moisture content did not affect the separation rate at 7 m s-1. With decreasing velocity, the separation rate in the particle size was reduced, which was due to the higher speed of the separation rate. At low velocity, the best separation was related to the fine particle size, which was due to the harmonization of the fine particle velocity and the separation rate.ConclusionPneumatic separation of almond kernel and shell was affected by air velocity, particle size and moisture content. As the flow rate increases, the amount of shell separation from the kernel increases. Particle size and moisture content did not affect the separation rate at 7 m s-1. The results at medium moisture content indicated that in addition to the acceptable separation level (relative to other moisture levels) at this level (13%), the harvesting time of this product can be managed and the use of additional energy in the processing of this product is prevented.

Research Article

Evaluation of the Effect of Rake Angle on the Performance of a Modified Narrow Blade

B. Souri Damirchi Sofla; S. H. Karparvarfard; A. Ranjbar Karim Abadi; H. Azimi-Nejadian; A. Moazni Kalat

Volume 11, Issue 2 , 2021, Pages 187-197

https://doi.org/10.22067/jam.v11i2.84823

Abstract

IntroductionTillage is one of the most important field operations to improve soil structure and physical conditions and provide the proper plant site. Conservation tillage is one of the methods of tillage that reduces tillage costs. The blade is one of the most important consumed components of tillage ... Read More IntroductionTillage is one of the most important field operations to improve soil structure and physical conditions and provide the proper plant site. Conservation tillage is one of the methods of tillage that reduces tillage costs. The blade is one of the most important consumed components of tillage tools in the conservation tillage, which is very important for how it is adjusted and its effect on the quality of tillage and energy required of tillage tools. According to the research conducted on the importance of optimizing tillage implements, the aim of this study was oriented to determine the optimum rake angle of a narrow-modified winged and non-winged blade in the field soil.Materials and MethodsThe tests were conducted in the 22nd part of farms in Agriculture School (Bajgah zone) of Shiraz University. Three levels of blade rake angles (20, 25, and 30 degrees), two levels of tillage depth (15 and 20 cm), and two levels of forward speed (2 and 3 km h-1) were the treatments of this study. Draft, fuel consumption, slippage, soil disturbance area, soil upheaving area, and specific draft were the measured parameters and they were measured for each combination of the treatments. The RNAM test code was then used to measure the draft force. In order to measure fuel consumption, two flow meters were used in the round way as a closed-loop. The encoder and the fifth wheel were also employed to measure the slippage. The profilometer and laser meter were applied to measure the soil upheaving and disturbance areas. The split-split plot on randomized complete block design was used to do the field experiments in three replication and the data analysis was performed by SAS software (9.4 edition). Multivariate linear regression was used to determine the optimum values of the mentioned parameters. For this purpose, the lowest value of draft, fuel consumption, specific draft, tractor driver wheel slip, and the highest soil disturbance and upheaving areas was considered.Results and DiscusionThe results showed that the magnitude of draft increased with rake angle, therefore, the minimum draft was obtained in the rake angle of 20°. As the blade rake angle increased, the amount of soil disturbance area was increased and the maximum soil disturbance was obtained in the rake angle of 30°. The mean slip values of the tractor driver wheels when using non-winged blade were not significant for three levels of blade rake angles and it was significant for two velocity levels. With increasing in rake angle from 20 to 25°, the mean values of specific draft were increased, but with changeing the rake angle from 25 to 30°, there was not significant difference between specific draft values. The difference between the magnitude of tractor driver wheels slip for three levels of rake angle was not significant. Increasing the rake angle had a significant effect on tractor fuel consomption, such that it increased by increasing the rake angle values.ConclusionThe optimum rake angle for the non-winged blade mode was 20° with R2 of 0.73 and for the winged blade mode was 30° with R2 of 0.90. The optimum depth for the non-winged blade was 19.98 cm with R2 of 0.99 and for the winged blade was 20 cm with R2 of 0.97. Also, the optimum forward speed values for the non-winged blade was 2.21 km h-1 with R2 of 0.43 and for the winged blade was 2.03 km h-1 with R2 of 0.84.

Research Article

The Effect of Compression Ratio and Alternative Fuels on the Performance of Turbocharged Diesel Engine by GT-POWER Software

S. Ahmadipour; M. H. Aghkhani; J. Zareei

Volume 11, Issue 2 , 2021, Pages 199-212

https://doi.org/10.22067/jam.v11i2.71613

Abstract

Introduction Today, maximizing the efficiency of fuels and increasing the output power of diesel engines is considered inevitable due to the increasing need for energy resources, the reduction of fossil fuel resources, the need to maintain the environment, reduce air pollution, and limit the electricity ... Read More Introduction Today, maximizing the efficiency of fuels and increasing the output power of diesel engines is considered inevitable due to the increasing need for energy resources, the reduction of fossil fuel resources, the need to maintain the environment, reduce air pollution, and limit the electricity supply and fuel supply. In the large cities of Iran, the problem of vehicle pollution is one of the main problems. The lack of proper fuel, soot filters, and absence of requirement for a technical inspection of diesel vehicles have led to an increase in mortality and the growth of lung cancer due to pollution. All of studies indicate that fossil fuels, despite the low cost of production, will increase the cost of both living and environment. A solution for this crisis is to reduce the sources of pollutant-producing sources from the source of these pollutants. In the internal combustion engines, the compression ratio and alternative fuels are two important factors affecting engine performance and exhaust emission. Materials and Methods In this research, a one-dimensional computational fluid dynamics solution with GT-Power software was used to simulate a six-cylinder diesel engine to study the performance and exhaust emissions with different compression ratios and alternative fuels. The compression ratio was chosen to be 15:1 to 19:1 with an interval at unity. Alternative fuels such as (as base diesel), methanol, ethanol, diesel and ethanol, biodiesel and decane were selected. To modeling engine, first, all parts of the engine were introduced as a real six-cylinder engine, and then the required data were entered according to the actual engine conditions at the atmospheric pressure of one atmosphere. Before this investigation was carried out, a validation model for evaluation was done by experimental and simulation data. The validation results showed that software model error is acceptable and the model has a good capability of fitting and predicting. Results and Discussion The engine performance was evaluated in terms of engine power, engine torque, and specific fuel consumption at different engine compression ratio and fuel. The results showed that with increasing the compression ratio, brake power and brake torque increased. Among the fuels used in this engine, the maximum brake power and brake torque in the compression ratio of 19 with the decane fuel were 3.86% higher than that the base fuel and the lowest value was awarded in the compression ratio of 15, with methanol fuel and it was equal with 56.04%. The results indicated that by increasing compression ratio, the brake specific fuel consumption was reduced due to more power than the fuel consumed in the engine. A fuel with lower heating value should be injected more mass to the engine. This will increase the brake specific fuel consumption. In this research, the decane fuel with a compression ratio of 19 with a reduction of 3.72% had the lowest brake specific fuel consumption among other fuels. The CO emission from the engine largely depended on the fuel's properties, the availability of oxygen, the fuel mix with air, temperature, and turbulence inside the combustion chamber. The results highlighted that by increasing compression ratio, CO emission increased and CO emission in biodiesel fuel, with a compression ratio of 15, was decreased by 82.37% compared to the base. CO2 emissions are not too harmful to humans, but they increase the potential for ozone depletion and global warming. With increasing compression ratio, CO2 and HC emissions increased for all fuels, CO2 emissions have risen up the base. The fuel heating mechanism, combustion temperature, oxygen content, and gas fuel availability are the most important factors in the formation of NOx. With increasing the compression ratio, the amount of NOX increases, which is due to the high temperature in the cylinder at a higher compression ratio. The viscosity and density of fuels have an effect on NOX emission, and because of the larger droplets of the fuel, it released NOX. The highest NOx emissions from biodiesel fuel are due to the high oxygen content of this fuel and the lowest NOx emissions from decane fuel, due to the low density of the fuel compared to other fuels. Conclusion The results of this study showed that the decane fuel with a compression ratio of 19 in total had the best functional and pollutant characteristics among the six fuel used in this study. Therefore, this fuel can be the best alternative for diesel fuel.

Research Article

Studying some Pollutant Emissions of an Injection Gasoline Engine Using Mixed Fuel of Ethanol, Gasoline and Carbon Nanoparticles

M. Malek mohammadi; M. Rahnama; S. Abdanan Mehdizadeh; N. Kazemi

Volume 11, Issue 2 , 2021, Pages 213-230

https://doi.org/10.22067/jam.v11i2.76903

Abstract

Introduction Due to the rapid growth in the urban population, the numbers of cars also have increased which resulted in an increase of pollution level in the urban areas of the developing countries. The pollutants emerging from combustion engines may include: carbon monoxide (CO), unburned hydrocarbons ... Read More Introduction Due to the rapid growth in the urban population, the numbers of cars also have increased which resulted in an increase of pollution level in the urban areas of the developing countries. The pollutants emerging from combustion engines may include: carbon monoxide (CO), unburned hydrocarbons (UBHC), oxide of nitrogen (NOx), oxides of sulfur (SOx), particulate matter (PM), soot, hydrogen, oxygen, traces of aldehydes, alcohols, ketons, phenols, acid, lead aerosol, etc., along with normal combustion products i.e. carbon dioxide (CO2) and water vapors. In order to overcome the problems associated with the bio-fuel, the chemical substances like fuel additives derived from organic, inorganic metals were used. Fuel additives generally improve the combustion efficiency and reduce the pollution. Metallic based compounds, such as manganese, iron, copper, barium, calcium and platinum, etc., which have been used as a combustion catalyst for hydrocarbon fuels. Recent advances in nanoscience and nanotechnology enables production, control and characterization of nanoscale energetic materials. Nano materials are more effective than bulk materials because of its higher surface area. Another important advantage of nanoparticle is its size, because there is no chance for fuel injector and filter clogging as in the case of micron sized particles. Gan and Qiao, (2011) investigated the burning characteristics of fuel droplets containing nano and micron sized aluminum (Al) particles by varying its size, surfactant concentration and type of base fluid. Tyagi et al. (2008) conducted a study to improve the ignition properties of diesel fuel and investigated the influence of size and quantity of Al and Al2O3 nanoparticles in a diesel fuel. It was inferred that it shortens the ignition delay and increased the ignition probability of fuel. Finally, it was concluded that, the increase in heat and mass transfer properties of the fuel has the potential of reducing the evaporation time of droplets. In the present investigation, the effect of mixture of ethanol with gasoline and carbon nanotubes on emission characteristics was evaluated using Jatropha biodiesel in a compression in a spark ignition engine.Materials and MethodsIn this study, a mixture of ethanol with gasoline (at five levels, 0, 10, 20, 30 and 40%) as a renewable fuel and carbon nanoparticles (at three levels of 0, 20 and 80 ppm) as catalyst were used in spark ignition engine (in 1000, 2000 and 3000 rpm). Engine pollutants such as sound, carbon monoxide, unburnt hydrocarbons, carbon dioxide and oxygen output were measured. Furthermore, a device was designed and manufactured to measure and display the amount of carbon monoxide in the exhaust outlet; moreover, if the amount of carbon increased air compressor was activated to reduce carbon monoxide in the exhaust outlet.Results and Discussion The results showed that with increasing ethanol consumption, the amount of carbon monoxide and unburned hydrocarbons were reduced. Furthermore, the amount of produced oxygen and carbon dioxide increased. Also adding carbon nanoparticles to fuel caused the engine sound level decreased. According to the observation, carbon monoxide decreased while using an electronic device compare to the engine without a carbon monoxide controlling system. This depicts that implementation of carbon monoxide can be control and reduce which is very useful while engine is working under the close environments.ConclusionThe use of alternative fuel, gasoline as well as the reduction of exhaust emissions in the spark ignition engine is of great importance. Therefore, in the present study five levels of ethanol (0, 10, 20, 30 and 40%) and three levels of carbon nanoparticles (0, 20 and 80 ppm) were mixed with gasoline and used in spark ignition engine at three rotation speed (in 1000, 2000 and 3000 rpm). According to the results, there is a reduction in carbon monoxide and unburned hydrocarbons and increasing carbon dioxide emission by using ethanol, because of its fuel bound O2. Furthermore, 3.8% dB 54% reduction in sound and CO, respectively at 3000 rpm with E10 were observed.

Research Article

Numerical Study of Wheat Conveying in Separator Cyclone using Computational Fluid Dynamics

S. Naimei Dizajyekan; Gh. Shahgholi; A. Rezvanivand fanaei; V. Rostampour

Volume 11, Issue 2 , 2021, Pages 231-246

https://doi.org/10.22067/jam.v11i2.79613

Abstract

IntroductionCyclones are widely used to separate solid particles from the fluid phase. Due to the ease of construction, low running costs, and hard-working conditions at high temperatures, people's interest in using cyclones is increasing day by day. Engineers are generally interested in two parameters ... Read More IntroductionCyclones are widely used to separate solid particles from the fluid phase. Due to the ease of construction, low running costs, and hard-working conditions at high temperatures, people's interest in using cyclones is increasing day by day. Engineers are generally interested in two parameters to perform a complete evaluation of the design and operation of a cyclone. These parameters are the particle collecting efficiency and the pressure drop inside the cyclone. The precise prediction of the pressure drop in cyclone is very important which it is directly related to operating costs.Computational Fluid Dynamics (CFD) is a diversified tool for predicting flow behavior in a wide range of design and operational conditions. Numerical solution of Navier-Stokes equations is the basis of all CFD techniques, which is the result of fast computer upgrades and a better understanding of the numerical resolution of turbulence.Materials and MethodsRegarding preliminary experimental tests and understanding the fluid flow, the flow rate of 0.08 kg s-1 was selected as the flow rate. Six levels of inlet velocities 10, 12, 14, 16, 18, and 20 m s-1 were selected for understanding the effect of inlet velocity on the cyclone performance. The measurements were carried out using a hot-air anemometer (TSI-8484model with a resolution of 0.07 m s-1 and an operating range of 0.125 to 50 m s-1), and a pressure differential meter instrument (CPE310s-KIMO model) with an accuracy of 0.1 Pa.The region is discretized as a finite volume in a set, called the region grid or mesh after discretization. For incompressible fluids, pressure-based and density-based solvers are used, respectively. Regarding the velocity of the material entering the cyclone and low Mach number, a pressure-based solver could be used in this study.The shear stress transport model (SST) is a modified version of the k-ω 2-equation model. This model combines the two turbulence k-ω and k-ε models. The Lagrangian discrete phase model in Ansys Fluent follows to the Euler-Lagrangian model.Defining the best type of boundary condition is important for solving the problem and extracting solving fields. The boundary conditions used in this study include the inlet velocity in the entrance of cyclone and output pressure in both the upper and lower output sections.Results and DiscussionIn the results section, the results are initially validated by experimental results. Then, the parameters relating to separation efficiency and pressure drop are discussed. Finally, the tangential and axial velocities are considered as important parameters in the cyclone performance.One of the important issues in the cyclones is the static pressure because it completely affects the phenomenon of separation in the cyclone. The velocities of 16 m s-1 and 18 m s-1 have a good potential for use as the base velocity of the inlet fluid to the cyclone. The velocity of 20 m s-1 is not suitable for separation due to high-pressure drop related to high static pressure.The separation efficiency in the cyclone was 92 to 99% at all levels, the highest separation efficiency of 99% occurred at the velocity of 16 m s-1 and the lowest separation efficiency of 9% happened at the velocity of 20 m s-1.An increasing trend in axial and radial velocities occurred and the highest tangential velocity occurring in the input section. Considering the working conditions, the inlet velocities of 10 m s-1 to 16 m s-1 are appropriate for the turbulence intensity viewpoint.Conclusion(1): The speeds 16 m s-1 and 18 m s-1 showed a good potential for use as a base velocity of the fluid to the cyclone.(2): The highest separation efficiency for the velocity of 16 m s-1 (99%) and lower isolation efficiency was obtained at velocity of 20 m s-1 (92%).(3): The velocities of 10 m s-1 to 16 m s-1 are suitable input rates from the point of view of turbulence intensity.(4): It is concluded that from the point of view of wear to the velocity of 10 to 16 m s-1, practical use is possible, and the velocity of 18 m s-1 and 20 m s-1 require the reinforcement of the relevant sections.

Research Article Modeling

Ventilation and Cooling Modeling and Lyout of Fans, Pads and Vents of an Octagonal Greenhouse

J. Javadi Moghaddam; S. Ozlati; Gh. Zarei; D. Momeni; F. Azadshahraki

Volume 11, Issue 2 , 2021, Pages 247-262

https://doi.org/10.22067/jam.v11i2.82130

Abstract

IntroductionGreenhouse technology is a ﬂexible solution for sustainable year-round cultivation of many horticulture products, particularly in regions with adverse climate conditions or limited water and resources. Greenhouses are the structures that provide the desired conditions for plant growth throughout ... Read More IntroductionGreenhouse technology is a ﬂexible solution for sustainable year-round cultivation of many horticulture products, particularly in regions with adverse climate conditions or limited water and resources. Greenhouses are the structures that provide the desired conditions for plant growth throughout the all seasons. Plant growing and crop production in the greenhouses require proper ventilation conditions to provide optimal temperature, relative humidity and CO2 and to minimize the toxic gases. Ventilation method of greenhouse is depending on the design of greenhouse ventilation and cooling is usually done by evaporative pad and fan systems or fan and vent systems. Recently different designs, different structures and different layouts of fans, pads and vents are used in greenhouses. Layout of fans, pads and vents affects the performance of ventilation systems. The aim of this study was to layout the fans, pads and vents to provide best air flow in an octagonal greenhouse. Materials and MethodsIn this study, three layouts of evaporative pad and fan systems and vents were modeled by computational fluid dynamics (CFD) method. For computational fluid dynamic of inside greenhouse airflow, the air flow was considered to be compressible. In order to estimate density, velocity and temperature, the Navier- Stokes equation included momentum, state, energy, continuity was used. For modeling the fluid flow, all necessary and dependent parameters of climate were considered based on the concentration and air pressure at the level of the open sea. Fluid flow equations were solved by finite volume technique. Three mentioned layouts of this study were 1- fans on the roof of the pyramids and vents on the wall of the pyramids, 2- pads and fans on the greenhouse side walls and 3- pads on the greenhouse side walls and fans on the roof of the pyramids (parallel pads). The performances of each arrangement can be improved by the speed of the fans, the size of the vents. The main equation in fluid flow simulation using CFD can be done by the following set of equations in which the continuity equation in the form of indicial notation can be presented as: Moreover, the momentum equation can be written by the following form: The equation 4 shows the state equation in a fluid flow interaction. All technical calculations and CFD simulations were done by Solidworks 2018 software.Results and DiscussionThe results showed that octagonal greenhouse by a specific form of the vents on the walls and fans on the roof could provide a circular air flow around the plants in the greenhouse. However, due to different powers of the fans, different velocity and different shape of air circulation could be achieved. When pads and fans are located on the greenhouse side walls, uniform air flow from the pads move uniformly throughout the greenhouse and then exit from opposite fans which causes desired air flow in the greenhouse. When the fans are located on the roof of the pyramids and pads are located on the side walls parallel, pad surface increases in the greenhouse and thus relative humidity increases and temperature decreases.ConclusionBecause of the specific shape of the vents in octagonal greenhouse, different air velocity and different shape of air circulation will be achieved when different power of the fan is used. This causes that the octagonal greenhouse can be used in different climate conditions. When the fans are located on the roof of the pyramids and pads are located on the side walls, temperature decreases and relative humidity increases and this layout is desirable for hot and dry climate. An octagonal greenhouse can be used in different climate by using a suitable layout of fan, pad and vents.

Research Article Modeling

Modeling of Potato Slice Drying Process in a Microwave Dryer using Artificial Neural Network and Machine Vision

S. Rezaei; N. Behroozi-Khazaei; H. Darvishi

Volume 11, Issue 2 , 2021, Pages 263-275

https://doi.org/10.22067/jam.v11i2.78709

Abstract

IntroductionMicrowave drying compared to conventional hot air drying has many benefits to apply in food drying processes such as volumetric heating, high thermal efficiency, shorter drying time and improved product quality. In conventional microwave drying method, a fixed microwave power was used during ... Read More IntroductionMicrowave drying compared to conventional hot air drying has many benefits to apply in food drying processes such as volumetric heating, high thermal efficiency, shorter drying time and improved product quality. In conventional microwave drying method, a fixed microwave power was used during the drying process. However, the water of the product evaporated and mass of product decreased over the time that resulted in microwave power density (MPD) increasing during the drying process. Increasing the power density, especially at the end of the process, sharply increased the product temperature. High temperature of products led to the deterioration of the product quality. Most research used variable microwave power program for preventing the risk of overheating and charring of product. The evaporation of the water causes the shrinkage of product. Therefore, many studies have used machine vision for measuring the shrinkage and this technology has been used in modeling and predicting the MC.Materials and MethodsThe fresh potato samples (Solanum tuberosum cv. Santana) with 83% (w.b.) of initial MC were sliced into the chips of 5mm thickness. The developed drying systems consisted of microwave oven, lighting unit and imaging unit, temperature sensor, microwave power adjusting unit and a data acquisition unit (DAQ). A LabVIEW (V17.6, 2017) program was developed to integrate all measurements and adjusting the microwave power during the drying process. In this study, two sets of experiment with different aims have done. The first set of experiments was used for calculating the shrinkage by developed image processing algorithm and MC by offline mass measurement and then data sets were used to investigate the artificial neural networks (ANNs). The second set was used for evaluating the reliability of investigating models. The experiments, in the first set, were done with 8, 4 and 2.67 W g-1. In the variable mode, the power varied in two/three steps with respect to the MC of samples during the drying process. Second set of experiments was done in two variable and constant power modes with 5 and 3 W g-1. An image processing algorithm was developed to measure the shrinkage of potato slice during the drying process. In this study the feed forward ANN with back propagation algorithm was used. Two structures of ANN were used for modeling of MC. In the first model time and power density and the second model shrinkage and power density were used as input. Also moisture ratio was used as an output parameter in two models.Results and DiscussionThe obtained results indicated that for the first model the ANN with 2-3-1 structure had better results than others structures. This structure had 0.0713, 0.0337 and 0.0640 of RMSE and 0.9764, 0.9973 and 0.9800 of R for train, validation and test, respectively. For the second model, the 2-2-2-1 structure of ANN with 0.0780, 0.0816 and 0.0908 of RMSE and 0.9598, 0.9799 and 0.9746 of R for train, validation and test, respectively had better results than other structures. The evaluation of these models with a second data set showed that the second model with shrinkage and power density as input with 0.067 of RMSE and 0.994 of R had better results than the first model with 0.173 of RMSE and 0.961 of R. These consequences expressed that the second model had higher reliability for prediction of MC based on shrinkage and power density during drying process.ConclusionIn this study, a microwave dryer was developed with a real-time image recording system and a microwave power level program during the drying process. Two ANN models were used for modeling of drying kinetics of the potato slices. Also image processing algorithm was investigated by measuring the shrinkage of potato slice during the drying process. The outcomes revealed that shrinkage as input in the ANN had great effect on MC prediction during the drying process.

Research Article

Feasibility of Online Diagnosis of Botrytis elliptica Disease in the Lilium Plant using the Machine Vision System and K-means

H. Biabi; S. Abdanan Mehdizadeh; M. Salehi Salmi

Volume 11, Issue 2 , 2021, Pages 277-291

https://doi.org/10.22067/jam.v11i2.77237

Abstract

IntroductionThe automatic detection of plant diseases in early stages in large farms, in addition to increasing the quality of the final product, could prevent the occurrence of irreparable damage. To this end, accurate and timely diagnosis of farm conditions is of great importance. In order to facilitate ... Read More IntroductionThe automatic detection of plant diseases in early stages in large farms, in addition to increasing the quality of the final product, could prevent the occurrence of irreparable damage. To this end, accurate and timely diagnosis of farm conditions is of great importance. In order to facilitate production potential and prevent a significant decline in yield, disease diagnosis is necessary periodically throughout the whole life of the. On the other hand, early detection of the disease in its early stages of growth can also prevent the spread of diseases. One of the most common methods for diagnosing plant diseases is the use of visual methods, but this method is difficult to evaluate the performance of a number of parameters such as the effects of the environment, nutrients, and organisms and so on. Furthermore, the accuracy of repetitions is very much related to individual fatigue of inspector. Research on activities that have the ability to identify diseases at an early stage and prevent the spread of contagious diseases are of great importance. Therefore, the use of new applications and new detection technologies to protect can significantly reduce the risk of product loss. Therefore, the purpose of this research is to design and construct an intelligent control system that automatically detects the health of the lilium plant and to improve the plant's condition.Materials and MethodsSample collectionIn this study, 80 pots of four kilograms (including healthy and disease plants) were considered for plant growth in vegetative stage. The spring onions were grown in pots with 20 cm diameter and 30 cm height. Experiments were carried out in a greenhouse with a temperature of 27.15°C day/night and a relative humidity of 70-75%.Image processing In this research, the camera was placed at a constant distance of 50 cm from the flower to evaluate the stem and the leaves attached to it. The images were captured under the constant light conditions in the greenhouse during a specific hour of the day (10 to 12) every other day. The image was taken in RGB color space with a resolution of 1024 × 840 pixels, and after image transfer to the computer, image processing was performed using Matlab 2016a. After examining the plant image, 9 color channels (R, G, B, L, a, b, H, S, and V) were examined from three color spaces (RGB, Lab and HSV) and stem length to diagnosis of Botrytis elliptica disease.Feature selection and classification In this research, after improving the image and extracting the feature, the linguistic hedges method was used to select the features and the K-means clustering was applied in the N-division of the k-clustering specified by the user. In this method, each attribute was assigned to a cluster closer to the mean vector. This method continues until there was no significant change in the mean vectors between successive repetitions of the algorithm.Results and DiscussionAccording to the results of feature selection L leaf, L stem, a leaf, b leaf, H leaf, b stem, H stem, V leaf and stem length, were the best features. Moreover, the accuracy of diagnosis for the diseased and healthy plants were 96.42 and 100 percent, respectively, and the overall classification accuracy was 97.63 percent. Therefore, in general, it can be said that the proposed image processing method is desirable and acceptable in order to diagnose the disease. According to this, zhuang et al. (2017) used sparse representation (SR) classification and K-means clustering to identify leaf-based cucumber disease. In the proposed method, it has been shown that system could detect cucumber diseases with accuracy rate of 85.7%. Therefore, the proposed image processing technique seems to be able to diagnose the disease quickly and easily.ConclusionToday, in the modern agricultural systems, numerous computational methods have been designed to help farmers to control the proper growth of their products. However, there are still major problems with the rapid, accurate and classification of diseases in the early days of the disease. Therefore, the purpose of this study was to design, construct and evaluate a smart system based on image processing in order to identify and classify the leaf disease of the leaves of the lilium plant and remove it by spraying the contaminated parts. For this purpose, the linguistic hedges method was used to select the characteristics and k-means method to classify the infected plant from healthy. The results of the classification for the diseased and healthy plants were 96.42 and 100 percent, respectively, and the overall classification accuracy was 97.63 percent, which indicates the acceptable accuracy of the machine vision system in detecting the disease.

Research Article Modeling

Greenhouses Energy Supply Modeling Using Renewable Energy in Grid-Connected mode

S. Mirzamohammadi; A. Jabarzadeh; M. Salehi Shahrabi

Volume 11, Issue 2 , 2021, Pages 293-303

https://doi.org/10.22067/jam.v11i2.79780

Abstract

IntroductionThe increasing global population on the one hand and limited water and soil resources on the other hand, contribute to the need for the supply of agricultural products by adopting modern methods. One of the modern methods of farming is the cultivation of products in commercial greenhouses. ... Read More IntroductionThe increasing global population on the one hand and limited water and soil resources on the other hand, contribute to the need for the supply of agricultural products by adopting modern methods. One of the modern methods of farming is the cultivation of products in commercial greenhouses. Despite favorable performance of greenhouses in the agricultural sector, high demand for direct and indirect energy is among the main considerations of developing them because the energy supply of greenhouses has the highest influence on the performance of greenhouses, quality of products, and market price of products. In this study, the energy supply of greenhouses in the case of using renewable resources is done in a grid connection state. Trading energy with main grid is enabled. Decision-makers’ objective is determining the optimal number of renewable resources and energy storage units for the purpose of income maximization.Materials and MethodsBasically, the supply of energy for greenhouses or in other terms supply of electric, cooling, and heating loads required by greenhouses is intended to cover lighting, internal temperature, emission of CO2, and relative humidity. Since many greenhouses have proper access to the main grid for the supply of their demanded load, the problem seeks maximum use of renewable energy rather than buying power from the grid for supplying the loads which greenhouses need to its secure revenues. To this, mathematical modeling has used to determine the optimal number of energy sources and storage units that revenues of using renewable energy resources be optimized based on existing limitations. These limitations include balancing generation and consumption of thermal and electrical power in each hour, logical relationship between charging and discharging of batteries, limit of power generation of renewable sources in each hour of the day and the level of capital available for investment.Results and DiscussionBased on the collected data, 9 different issues have been defined in terms of the proportion of costs of solar energy and wind energy and the proportion of purchasing and selling price of power. The obtained results suggest that in the case of equality of investment and maintenance costs of solar and wind energies, the use of wind energy rather than solar energy will be justified. The most significant reasons for this is considering proper conditions of wind speed which causes its inclusion in optimal solution of the problem since using solar energy during nightly hours is impossible. In addition, in the case of the equality of above costs, when purchasing and selling price of power cost is the same, the generated energy is completely used in the greenhouse. In the case of increasing the selling price, energy supply to the main grid will be economically justified. Since investment and maintenance costs of wind power are two times and 1.5 times higher than those of solar energy, using wind energy is cost-effective.ConclusionThe results suggest that in the case of an equal price of selling power to the grid and buying power from it, all of the energy will be consumed in the greenhouse. In the case of an increase in selling price, the supply of energy to the main grid will be economically justified. In addition, the results imply the significant effect of geographic conditions of the region, since sometimes concurrent use of renewable energies is unjustified. Since the lack of supply of energy to greenhouses significantly influences the cultivation of products, considering the cost of lack of energy supply in modeling is one of the contributions of the present study. Another significant aspect of the study is the generalization of modeling from the greenhouse to greenhouse complexes. To do so, using the notion of micro-hub for greenhouses and their management will be useful.

Research Article Modeling

Potential Evaluation and Modeling of Biogas Production from Apple Pomace

M. Sami; A. Akram; M. Sharifi

Volume 11, Issue 2 , 2021, Pages 305-316

https://doi.org/10.22067/jam.v11i2.80322

Abstract

IntroductionThe need to develop alternative energy sources especially renewable energy has become increasingly apparent with the incident of fuel shortages and escalating energy prices in recent years. With the advent of renewable energy, various studies have been conducted to investigate the potential ... Read More IntroductionThe need to develop alternative energy sources especially renewable energy has become increasingly apparent with the incident of fuel shortages and escalating energy prices in recent years. With the advent of renewable energy, various studies have been conducted to investigate the potential of biogas production from agricultural waste. Considering the importance of retention time and methane production potential for designing industrial digesters, many studies on potential analysis and modeling of the digestion process of different products have been carried out by various researchers. These studies are valuable for the design and implementation of anaerobic digesters. Apple is one of the most popular fruits in many parts of the world and is widely cultivated in many temperate regions of the world. Considering the large volume of apple waste in Iran, this study was designed based on potential evaluation and modeling of biogas production from apple pulp.Materials and MethodsIn order to measure the potential of biogas production from apple pomace, a number of lab-scale digesters with a capacity of 600 ml and a working capacity of 400-500 ml were made. pH and C/N ratio were modified by adding NaOH and urea solution, respectively. Three different temperature treatments including psychrophilic (ambient temperature), mesophilic (37ºC), and thermophilic (47ºC) were applied to the substrate. Used pomace samples were collected from the output of an apple juice factory in southern Isfahan province, Iran. Anaerobic Biodegradability (ABD) was obtained by dividing the experimental methane production potential (BMP) obtained from the experimental results on the theoretical methane production potential. Three most common kinetic models of Gompertz, Logistic, and Richards were used to predict and stimulate the cumulative methane production of treatments.Results and DiscussionUnder ambient temperature, the digestive process took a longer time, and the time of maximum dilly biogas production was considerably more than the other two treatments. Statistically, production time and peak time of this treatment was higher than the other two treatments at 1% significance level. Maximum daily biogas production in the ambient treatment was observed on day 37th with a volume of 6.99 g-VS-1 ml, while maximum daily biogas production in the treatments of 37 °C and 47 °C were observed on days 22th (20.16 ml g-VS-1) and 20th (25.57 ml g-VS-1), respectively. In all three treatments, daily biogas production increased sharply in the first incubation days and after that reduced and then production increased again. In mesophilic and thermophilic treatments, the production of biogas modestly stopped after 35 days, but under the ambient temperature, the process of production continued after 55 days. The methane concentration of biogas in the psychrophilic treatment was significantly lower than the other two treatments at 1% level. Two treatments of 37°C and 45°C have a significant difference in methane yield at 1% level. Nevertheless, the production of biogas in two treatments was not statistically different. In all three treatments, the lowest pH was recorded after 7 days of production and the highest pH was recorded on days 34-40. All three kinetic equations were able to simulate the methane production process with high precision, although the results of the Logistic model provided higher accuracy. In the treatment 47 °C, the efficiency of the studied equations was higher than other treatments and models were able to predict the production process with higher accuracy. Results of the experiment show the high biochemical methane production potential of apple pomace (473.17 ml g-VS-1), which under laboratory condition of this study up to 63.9% of this potential (302.70 ml g-VS-1) was obtained. ConclusionThis study results are valuable for the design and implementation of industrial digesters. The results indicate the apple pomace has a high potential for the production of methane and its biodegradability is high. Apart from pH that is acidic, other apple pulp factors are appropriate for the activity of methanogenic bacteria. In terms of nutrients, apple pomace is also a good environment for the growth of anaerobic bacteria.

Research Article Image Processing

Anthracnose Detection on Walnut Tree Leaves using Outdoor Image Processing Methods

A. Yousefvand; J. Amiri Parian

Volume 11, Issue 2 , 2021, Pages 317-329

https://doi.org/10.22067/jam.v11i2.82558

Abstract

IntroductionControl of walnut diseases and pests requires the mapping of the extent of contamination within possible shortest time. Therefore, it is necessary to develop systems to detect and determine the prevalence and location of contamination for researchers and gardeners. Image processing has been ... Read More IntroductionControl of walnut diseases and pests requires the mapping of the extent of contamination within possible shortest time. Therefore, it is necessary to develop systems to detect and determine the prevalence and location of contamination for researchers and gardeners. Image processing has been proposed as an approach to determine the extent and type of damage to different products in farms and gardens. The aim of this study was to design an algorithm based on the processing of walnut leaf images under natural light conditions in order to provide a rapid and non-destructive detection of diseases for the protection of trees using imaging methods. In this research, the possibility of detecting Anthracnose disease was investigated by processing walnut leaf images. The disease was detected using in situ images taken from the leaves to provide the basis for designing application software on smart mechatronic systems. Materials and MethodsImages of leaves on walnut trees were taken under outdoor light conditions. Color and morphological properties extracted from the images were used to detect the pest on the leaves. Gnomonia leptostyla disease diagnostic algorithm was based on process of color and morphological characteristics, leaves background and disease-stained spots. The range of changes in R, G, and B indices was obtained in histograms and then two-dimensional spaces were analyzed statistically on GR, GB, and BR planes. All points from these regions were used as statistical samples, for which bivariate regressions of GR, GB, and BR were obtained as y = b0 + b1x. Segments containing anthracnose spots from the leaves were segregated by extracting the coordinates of the points in each side on the RGB color space cube. Finally, anthracnose content was detected based on the number of spots detected by the algorithms. The percentage of contamination was used to determine the amount of contamination in each imaged area.Results and DiscussionExamination of the colored spaces indicated that the domain of the anthracnose color components on the GR side has nothing in common with the color components of the leaves. The analysis of color space data revealed that the leaves and anthracnose were more distinguishable on the GB and RB sides, respectively. According to the histogram of the HSV color space, anthracnose spots were isolated from the leaves by determining the H range. In the evaluation of the proposed method for diagnosis of anthracnose, the infection severity calculated by the algorithm with the true infection intensity. T-test results for comparing the mean of the two infection intensity samples showed no significant differences between the two groups at 1% probability level. ConclusionThe evaluation of the proposed method showed a 98% segregation accuracy for G. leptostyla detection method. Based on the results, the proposed method for detecting anthracnose spots is suitable for determining the contamination severity in the imaged areas.

Research Article

Optimization Effect of Ultrasound on Rupture Force and Kernel Extracting Quality of Walnut using Response Surface Method (RSM)

E. Biabani Agdam; M. H. Khoshtaghaza; Gh. Najafi

Volume 11, Issue 2 , 2021, Pages 331-342

https://doi.org/10.22067/jam.v11i2.80096

Abstract

IntroductionOne 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 ... Read More IntroductionOne 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 MethodsWalnut 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 DiscussionThe 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.ConclusionThe 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.

Research Article

Applying Adaptive Neuro-Fuzzy Inference System and Artificial Neural Network to the Prediction of Quality changes of Hawthorn Fruit (Crataegus pinnatifida) during Various Storage Conditions

M. Zandi; A. Ganjloo; M. Bimakr

Volume 11, Issue 2 , 2021, Pages 343-357

https://doi.org/10.22067/jam.v11i2.86654

Abstract

IntroductionIn 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 ... Read More IntroductionIn 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 MethodsThe 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 DiscussionTo 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.

Research Article

Optimizing the Muffler of a Portable Lawn Mower Engine to reduce Noise Pollution Levels

Sh. Sedighi; D. Kalantari; J. Rédl

Volume 11, Issue 2 , 2021, Pages 359-369

https://doi.org/10.22067/jam.v11i2.84829

Abstract

IntroductionThe most important adverse effects of noise on humans have reduced work efficiency and physiological damaging effects such as increased heart rate, high blood pressure, permanent and temporary hearing loss, impaired vision, disrupting the body's balance system, causing nervous disorders and ... Read More IntroductionThe most important adverse effects of noise on humans have reduced work efficiency and physiological damaging effects such as increased heart rate, high blood pressure, permanent and temporary hearing loss, impaired vision, disrupting the body's balance system, causing nervous disorders and even nervous disorders. Much of the occupational disturbance is due to acoustic vibrations in agricultural mechanization, which is affecting a large number of farmers. In this regard, most of the noise and vibration come from two-stroke or four-stroke engines that are used in lawn mowers, sprayers, pits and more. These high-vibration equipment causes a great deal of damage to their operators. Portable lawn mowers are popular for working in urban and rural areas due to their low cost, low maintenance cost, high maneuverability and affordability. Therefore, the possibility of optimizing the muffler of a small combustion engine for a lawn mower was investigated and studied in the present stud.Materials and MethodsTo optimize the existing muffler, geometry of the factory muffler was first redesigned in solidworks 2014 software. Then the optimized muffler, along with the factory muffler exported into ANSYS CFX software and simulated in terms of velocity and pressure distributions. To evaluate the built muffler and compare its performance with the factory standard muffler, the mufflers were then mounted on a DOMA’s lawnmower model WPGD501 with a 42 cm3 engine volume and tested outdoors in a radius of 5 m. All sound recording tests were performed in steady state at a distance of 1m with a 45° angle and position along the exhaust outlet to reconstruct the user's ear position. A digital thermometer TEM-8820 and a PSA-V01 digital barometer were used to measure the sound pressure and an environment temperature.Results and DiscussionThe results showed that at 3000 rpm, the sound pressure level of the modified muffler decreased by 6.4% compared to the modified muffler. The same decrease in sound pressure level was achieved at 5000 rpm, equal to 4.5%. The results of this study showed that with increasing engine speed, pressure changes in the muffler had an upward trend. These changes in the modified muffler increased by 0.02 kPa at 3000 rpm and by 0.07 kPa at 5000 rpm. According to the outputs of the FFT diagrams, the intensity and amplitude of the output frequencies from the modified muffler significantly decreased almost at most frequencies. Therefore, effective pressure difference (ΔPrms) was used for the further investigations. The results of this study showed that the pressure changes in the muffler had an upward trend with increasing the engine speed. These changes in the modified muffler increased by 0.02 kPa at 3000 rpm and by 0.07 kPa at 5000 rpm.ConclusionAccording to the results of the present study, by optimizing the internal muffler geometry of the lawn-mowers by installing internal blades and neutralizing the sound intensity inside the muffler, it is possible to reduce the sound pressure level by 4% to about 7% over the original muffler. It is a very simple and inexpensive method for the manufacturers of such engines.

Research Article

Estimation of the Best Classification Algorithm and Fraud Detection of Olive Oil by Olfaction Machine

M. R. Zarezadeh; M. Aboonajmi; M. Ghasemi-Varnamkhasti; F. Azarikia

Volume 11, Issue 2 , 2021, Pages 371-383

https://doi.org/10.22067/jam.v11i2.84105

Abstract

IntroductionExtra 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 ... Read More IntroductionExtra 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 MethodsThere 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 DiscussionHistogram 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.ConclusionDue 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).

Research Article

Measuring Mechanical Properties and Simulating the Creep Behavior of Wild Cane Stem using Burger-Voigt Model

M. Porabolghasem; A. Ghazanfari Moghaddam; F. Mozafari ghoraba

Volume 11, Issue 2 , 2021, Pages 385-397

https://doi.org/10.22067/jam.v11i2.80688

Abstract

IntroductionKnowledge of mechanical and viscoelastic properties of agricultural material will be helpful in the transportation and processing of these materials. Giant reed grass, also known as wild cane, is a tall, perennial, bamboo-like, grass that grows in wet areas. The giant reed grass can ... Read More IntroductionKnowledge of mechanical and viscoelastic properties of agricultural material will be helpful in the transportation and processing of these materials. Giant reed grass, also known as wild cane, is a tall, perennial, bamboo-like, grass that grows in wet areas. The giant reed grass can flourish in a wide variety of soils, including coarse sands, gravelly soil, heavy clay, and river sediment. This grass attains heights of 7 m and once established the stems can reach a thickness close to 3 cm. The stems of giant reed grass are used for different purposes. Traditionally the stems are used in the villages for fencing, roofing, and producing handcrafts. The modern uses of the giant reed stems include plywood, composites panels and paper production. The giant reed stems are not uniform and are made from many nodes. The number of nodes and the distance between nodes can affect the mechanical properties of the stems. In order to attain a suitable use of the stems in various industries, the physical and mechanical properties of the stems must be determined. Knowledge of mechanical and viscoelastic properties of agricultural material will be helpful in transportation and processing of these materials. The purpose of this research was to determine some relevant mechanical properties of the stems of giant reed grass with different nodes and moisture contents.Materials and MethodsIn this research, different mechanical and viscoelastic tests were performed on the stems of cane at various levels of moisture and number of nodes. The Burger-Voigt model with different number of elements was also used to model the creep behaviors of the stems. The cane stems were cut and divided to three groups of two, four, and six-node stems. The moisture contents of the stems were adjusted to three levels of 30, 40 and 50% (w.b.). After preparing the stems the mechanical tests were performed using an Instron testing machine with a three-point support. The creep tests were done by hanging a 10 kg weight at the middle of each stem. The experiments were done using factorial tests based on completely randomized design. The Young module, toughness, and the yield points of the stems were measured by the three-point method. These parameters were obtained from the stress-strain curves of the three-point compression bending tests. The results showed that the Young module was affected by both moisture and the number of nodes, but there were no interaction effects. The creeps of the stems under 10 kg loading were modeled using 3 to 5 elements Burger-Voigt models. In these models a combination of springs and dashpots are used to represent the stems. The curve fitting was performed using the MATLAB software and the goodness of fitness was verified using the fitted curves and calculating the coefficient of determinations.Results and DiscussionThe results by investigating the graphs and the ANOVA tests showed that the Young module was significantly affected by both moisture and the number of nodes. The obtained Young module for cane stem ranged from 572-1268 MPa. Both yield point and toughness were affected by both moisture and the number of nodes and their values were 65-250 N and 0.016-0.132 J.m-3, respectively. The creep test results indicated that the maximum deformation and maximum time for of the interaction of the two factors was insignificant. The maximum deformations ranged from 2.1-42.5 mm, and the maximum time for reaching the final deformation was 12.5-75 minutes for various moistures and the number of nodes combinations and showed that the 5-element Burger was best for explaining the viscoelastic behavior of cane stems (R2>0.97).ConclusionIn this research, some mechanical properties of the giant reed grass stems were measured and the creep behavior of the stem was modeled using 3-5 elements Burger-Voigt models. The results indicated a decrease in the Young module of the stems with increase with moisture content and increase in the Young module with increase in the number of nodes. On the other hand, the elongation of the stems increased with both number of the nodes and the level of moisture. The 5-element Burger-Voigt model was best fitted to the creep data.

Research Article Modeling

Modeling Grain Losses in Mechanized Harvesting of Oily Sunflower

P. Ghiasi; M. Safari

Volume 11, Issue 2 , 2021, Pages 399-408

https://doi.org/10.22067/jam.v11i2.84191

Abstract

Introduction Sunflower planting is mostly carried out for two particular purposes; oil production and as nut. Harvesting is one of the biggest problems in both types of sunflower. The difficulty of harvesting and less scientific research have led us to study the mechanized harvesting of this kind of ... Read More Introduction Sunflower planting is mostly carried out for two particular purposes; oil production and as nut. Harvesting is one of the biggest problems in both types of sunflower. The difficulty of harvesting and less scientific research have led us to study the mechanized harvesting of this kind of crops. In this research, head losses and grain losses for the inner section of combine were investigated during mechanized harvesting of oily sunflower and a regression model was used based on the experimental tests for head losses and grain losses in the inner section of the combine.Materials and Methods After preparing an especial head for harvesting sunflower, the head was set up on the combine for measuring the harvest losses. The cutting, threshing and clearing process for sunflower seeds were done during the tests. The design of the head is the same as the sunflower bushes are firstly bent by the bar and then sequentially the cutting, and transferring processes are done. The tests were implemented in an oily sunflower farm by a combine harvester (1055 john deer) in 3 replications. The farm performance was 2170 kg ha-1 and was located in Kermanshah province in Iran. A pre-test was done to define the best combine forward speed and finally 2.5 km h-1 was adjusted for combine forward speed. The bar height (BH) in two levels (20 and 70 cm) and head height (HH) in two levels (60 and 120 cm) were independent parameters to evaluate the head. The dependent parameters were the combine losses and head losses. For the analysis of variance of the variable parameters, a 2×2 factorial plot with 3 replications was used. A regression model was defined based on experimental tests.Results and DiscussionHaving done the experimental tests, data were analyzed and the effect of independent parameters on the head and combine grain losses were investigated. The effect of the bar height on the head grain losses was significant at 1% level and the effect of the head height and interaction between bar height and head height on the head grain losses was also significant at 5% level. Results showed that with increasing in bar height, the head grain losses increased. With a change in the bar height, the location of the cutting point is changed and this led to a change in the head grain losses. The effect of the bar height on the combine grain losses was significant at 5% level but the effect of the head height and interaction between bar height and head height was not significant on the combine grain losses. Increasing in the bar height led to increase in material other grain (MOG) which enters to the combine, and also resulted in increasing in combine grain losses. The coefficient of determination of head grain losses in the regression model was 0.97. The model was able to explain the relationship between the bar and head height with head grain losses due to the relationship between independent and dependent parameters. The amount of R-squared for the combine grain losses in the regression model was 0.53. Because of the effect of other parameters in the inner section of the combine, the output of the model predicted that increasing in the bar height and head height, resulted in increasing in head grain losses, and also increasing in the bar height and decreasing in head height let to increasing in combine grain losses. The output of model showed that regulating the bar height and cutting height could reduce the harvest losses by less than 3%. This R-squared is obviously less than R-squared of head grain losses model. The output of the regression model predicted that the increase in the bar height and head height was associated with increase in the head grain losses, and increasing in the bar height and decreasing in head height, resulted in increasing in combine grain losses. The output of the regression model showed that the harvest losses can be reduced less than 5% by regulating the bar height and cutting height.ConclusionOne of the most important parameters for mechanized harvesting is the head mechanism which cuts the crops and transfers them to the threshing unit. The cutting height in the sunflower head was defined by the bar height and head height. According to the linear relationship between the head and combine losses with the bar height and head height, and the interaction between them, the regression model was able to predict the result successfully. This model of grain losses in the head and combine model can be used in the intelligent combine to minimize the harvest losses. The optimization of the bar height and head height for minimizing the harvest losses can be the subject of next researches.

Research Article

Effects of Air Impingement Jet Drying on Drying Kinetics and Some Quality Attributes of Strawberry Slices

M. Rad; H. Goli; F. Mirahmadi

Volume 11, Issue 2 , 2021, Pages 409-422

https://doi.org/10.22067/jam.v11i2.83943

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 ... Read More 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.

Research Article

Energy and Exergy Analysis of Drying Process of Lemon Verbena Leaves in a Solar Dryer

M. Moradi; J. Ghasemi; H. Azimi-Nejadian

Volume 11, Issue 2 , 2021, Pages 423-433

https://doi.org/10.22067/jam.v11i2.85801

Abstract

IntroductionSome 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 ... Read More IntroductionSome 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 MethodsA 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 DiscussionThe 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.ConclusionA 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.

Research Article

Investigation of some Energy and Exergy Factors during Ohmic Heating Processing of Sour Orange

M. Vahedi Torshizi; M. Azadbakht; M. Kashaninejad

Volume 11, Issue 2 , 2021, Pages 435-445

https://doi.org/10.22067/jam.v11i2.80760

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 ... Read More 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.

Research Article

Evaluation of Several Spectral Indices for Estimation of Canola Yield using Sentinel-2 Sensor Images

N. Loveimi; A. Akram; N. Bagheri; A. Hajiahmad

Volume 11, Issue 2 , 2021, Pages 447-464

https://doi.org/10.22067/jam.v11i2.80232

Abstract

Introduction Remote sensing and using satellite images have been widely considered due to the high speed of measurement and great area of coverage. Canola is a source of edible oil and its cultivation in Iran and the world is developing. Comparing with other crops, canola, because of its yellow flowers, ... Read More Introduction Remote sensing and using satellite images have been widely considered due to the high speed of measurement and great area of coverage. Canola is a source of edible oil and its cultivation in Iran and the world is developing. Comparing with other crops, canola, because of its yellow flowers, has a different canopy color, and only a few researches have been carried out in order to assess the spectral indices for prediction of its yield. Therefore, the main objective of this research is to evaluate some spectral vegetation indices to estimate the yield of canola in different growth stages. Materials and Methods The study was performed in 2016-2017 in Karaj, Iran. Three canola farms were chosen for the evaluation of the relationship between yield and some vegetation indices derived from the Sentinel-2 sensor. The sensor data were processed in five stages: before flowering, early flowering, peak of flowering, green and dry maturity, and the vegetation indices were extracted for each of them. This research was pixel-based and the pixels network of each studied farm was determined by RTKGPS. During harvesting time, for measurement of grain yield, five samples, four from the corners and one from the center of the pixel, were taken and their average was considered as the representative amount of the pixel. Totally, 112 pixels from three studied farms were used to calibrate the predictive models. By using Simple Linear Regression (SLR) models, ten new and conventional vegetation indices were assessed. Also, Multivariate Linear Regression (MLR) models and Artificial Neural Net (ANN) models with four bands, three visible bands and NIR band, as inputs, were used to predict the canola yield. In order to validate the SLR and MLR models, the "K-Fold" method of cross-validation was used, and for the validation of ANN models, 15% of data were used; 70% for the train, 15% for validation, and 15% for the test. Results and Discussion The results showed that, on the basis of SLR models, among the growth stages, the highest coefficient of determination (R2) in each of the vegetation indices belonged to one of the two stages: the peak of flowering and green maturity. According to SLR models, among the vegetation indices in different stages, the NDYI in the peak of the flowering stage had the highest correlation with yield (R2 = 73%). Also, the RVI with 29%, BNDVI with 52%, NDVI with 56%, and GNDVI with 35% had the highest R2 in the before flowering, early flowering, peak of flowering, green and dry maturity stages, respectively. MLR models resulted to the best yield predictive model at the peak of flowering stage (R2 = 76% for the calibration and R2 = 73% and RMSE = 0.641 for the validation). For ANN models, the strongest model achieved at peak of flowering stage (R2 = 92% for the calibration (train) and R2 = 77% and RMSE = 0.612 for the validation (test)). It seems that the results are affected by yellow flowers of canola, and absorption of blue light by their petals. Therefore, in the peak of the flowering stage, the reflection of the blue light is more likely to belong to green leaves and stems. Therefore, any index such as NDYI, which the blue reflection is subtracted in its equation, represents better the number of flowers, and since the density of flowers is directly related to the yield, the yield will be predicted with more precision. Conclusion The results of the analysis of the indices by SLR models showed that the correlation of each of the vegetation indices with the canola yield, in different stages of growth, has a considerable difference. Based on this model, the highest R2 in each of these indices happened in the peak of flowering or green maturity stage, and among these indices in different stages, the NDYI in the peak of the flowering stage had the highest R2. Finally, in both of the MLR and ANN models, with four bands, three visible bands and near-infrared band, as inputs, the best yield predictive model resulted in the peak of the flowering stage.

Research Article

Semi-mechanized Harvesting of the Safflower Petals in Comparison with Conventional Method

M. Safari; H. Sharifnasab

Volume 11, Issue 2 , 2021, Pages 465-475

https://doi.org/10.22067/jam.v11i2.80725

Abstract

IntroductionSafflower (Carthamus tinctorius L.) is an oil plant with a growth cycle of 120 days. The seeds of this crop are primarily used for oil production, while its flower petals are used for extracting natural pigments and medicinal purposes. The cultivation area for this crop in Iran was about ... Read More IntroductionSafflower (Carthamus tinctorius L.) is an oil plant with a growth cycle of 120 days. The seeds of this crop are primarily used for oil production, while its flower petals are used for extracting natural pigments and medicinal purposes. The cultivation area for this crop in Iran was about 2300 ha during 2014-2015. Due to the recent droughts, cultivation of this crop has a good income for farmers because of the short growth period, resistance to drought (water stress) and less maintenance requirements. In the meantime, the flower petals of this crop are used for food coloring and medical affairs. The flower petals are harvested with the traditional method in most parts of Iran, which has a lot of hardship for harvesting and increases production costs. On the other hand, this crop is contaminated in terms of sanitary factors due to the contact of the worker hands with flower petals. Therefore, applying a proper mechanization method for petals harvesting is an effective step in the development of this crop cultivation.Materials and MethodsIn this study, three petal harvesting methods including the manual (conventional) method, Knapsack (Indian modified) method and Fossil-fueled wheelbarrow machine method were compared in terms of effective field capacity, downfall loss percentage, purity percentage, energy consumption, and harvesting costs. The Indian knapsack machine was modified. The experimental design format was a Randomized Complete Block Design (RCBD) with three replications‏. In the knapsack method (modified), petals were separated from the receptacle by a cutting blade and sucked into the machine reservoir. In the manual method, petals were separated from the reception by the worker hands and put inside the special bags which hanged on the worker neck. In the fossil-fueled wheelbarrow machine, an 8 kW motor-powered engine was used to set up the 1200 w vacuum system and cutting unit. The vacuum system was installed on the special chassis in wheel barrow machine. Each experimental plot had about 149 safflowers in one square meter area, which was harvested in different methods.Results and DiscussionThe results showed that the harvesting loss (W.W.) of the Knapsack method, Fossil-fueled wheelbarrow machine method, and manual method were 0.63%, 1.11%, and 3.25%, respectively. The percentages of purity were 97.71%, 98.66%, and 95.29%, respectively. There was a significant difference between machine and manual methods in 5% level. The effective field capacity of the methods was 2.45, 2.76, and 1.39 g min-1 (in dry condition), which was not significantly different between the machinery treatments in 5% level. The energy consumption for the fossil-fueled wheelbarrow machine was significant compared to the other two methods (1356 kW h-1 in 30 days). In terms of the economic point, benefit-cost ratios were 1.75, 1.55, and 1.16 for the Knapsack method, Fossil-fueled wheelbarrow machine method, and manual method, respectively. If the solar panel was used in the Knapsack method, the benefit-cost ratio would decrease to 1.54.ConclusionThe field capacity of machines methods was more than manual method for safflower petal harvesting. The Knapsack machine had less loss percentage than other treatments. The wheelbarrow machine had a higher degree of purity, but no significant difference was observed between this treatment and the Knapsack method. The energy consumption of the wheelbarrow machine was higher than other treatments. The economic evaluation showed that the Knapsack machine had a higher benefit-cost ratio than other treatments. If the solar panel was used by this machine, the use of a solar panel system would be economical too. Finally, with regards to the technical and economic parameters, using the Knapsack machine was recommended for safflower petal harvesting.

Research Article

Ergonomic Evaluation Posture of Sugarcane Workers using REBA Method

N. Monjezi

Volume 11, Issue 2 , 2021, Pages 477-489

https://doi.org/10.22067/jam.v11i2.78574

Abstract

Introduction One of the most important risk factors for developing musculoskeletal disorders is the inappropriate work of postures and since maintaining the health of the workforce promotes community development. Therefore, the workforce should be in an appropriate working environment without any harmful ... Read More Introduction One of the most important risk factors for developing musculoskeletal disorders is the inappropriate work of postures and since maintaining the health of the workforce promotes community development. Therefore, the workforce should be in an appropriate working environment without any harmful factors to ensure its physical and mental well-being. Among the various problem found in agriculture mentioned above, a problem commonly reported in agricultural workers in particular farmers in a rural area is work-musculoskeletal symptoms (MSS) in a different part of the body. In the process of producing sugarcane, a significant part of the stage of cuttings, planting, and harvesting is done manually. A low level of knowledge about the correct condition of the body during work is one of the problems of farmers. Therefore, body status assessment methods are considered as the basis and the basis for assessing the risk of musculoskeletal disorders associated with work. We decided to do a posture assessment in these persons while working to determine the posture hazard level. The purpose of this study was to identify inappropriate working conditions in sugarcane fields at the cutting, planting and harvesting manual stages. Materials and Methods This study was a descriptive-analytical approach performed on 300 workers by using the REBA method. The Rapid Entire Body Assessment (REBA) method was used to determine the risk of MSDs. The REBA posture-targeting method is probably the most well-known method for rapid assessment of risks. The REBA method is ideal for rapid assessment of standing work. In order to collect the required data, each part of the body was scored and work frequency, load/force, coupling were considered to achieve a REBA score. The REBA provides a quantitative value to the evaluation that indicates the level of severity of each task. The calculation was made by using the REBA Employee Assessment Worksheet that has been divided into two groups; Group A (Trunk, Neck, and Legs) postures and Group B (Upper Arms, Lower Arms, and Wrists) postures for left and right. A summary of the procedure for the REBA score and the degree of risk is found in the REBA decision table. The risk score of this approach should be in the range of one of fifteen, where the higher scores signify greater levels of apparent risk. An analysis of scores represents the work’s risks and indicates possible actions to avoid or minimize the risks. The method of work was to photograph workers in sugar cane fields of Khuzestan province during the activity and analysis of photographs using modeling the body of workers with REBA 6 software and analyzing different situations using REBA method. Results and Discussion By cutting stage, a total of 6.6% of evaluating postures by REBA technique obtained scores of 8-10 (very high risk level) and 93.4% had scores of 11-15 (very high risk level) that correspond to the action level 3 and 4, respectively. In planting stage, a total of 12.10% of evaluating postures by REBA technique obtained scores of 8-10 (very high risk level) and 87.90% had scores of 11-15 (very high risk level) that correspond to the action level 3 and 4, respectively. In the harvesting stage, a total of 15.30% of evaluating postures by REBA technique obtained scores of 8-10 (very high-risk level) and 84.70% had scores of 11-15 (very high risk level) that correspond to the action level 3 and 4, respectively. The results showed that according to the REBA method, in preparation cuttings, planting and harvesting sugarcane manually, respectively, 93.48, 90.87 and 84.77% of the workers' posture are in the most critical group that should be avoided. Risk level should be reduced, especially in sugarcane fields. More training and instructions are needed to have a good working position in sugarcane procedures. Improvement of working posture need to be done by improving all aspects that related to physical workload such as by reducing the workload on the back, neck, shoulder/arm, and also hand/wrist. Conclusion A high percentage of musculoskeletal disorders in workplaces occur due to awkward posture and non-ergonomic design of the workstations for lifting and carrying of materials. To avoid these injuries, jobs should be designed in a way that ergonomics risk factors are controlled properly. The results of this study can be used to develop WMSDs preventive strategies in the workplace and improve workers’ health. Educational intervention can be an appropriate way to improve the physical condition and ultimately reduce musculoskeletal disorders. Some proposed corrective actions include: standardizing the design and construction of the work tool used by the user's anthropometric study (especially sharp sickle), establishing suitable work-resting cycles and conducting periodic examinations for the early detection of musculoskeletal disorders. Of course, given the high percentage of damage to sugarcane production during manual operation, it's definitely a move to mechanized operations in sugarcane crops.

Research Article

Analysis of Energy Indicators and Environmental Impacts of Dryland Cantaloupe Production with Life Cycle Assessment Approach (Case Study: Ilam)

A. Kaab; M. Sharifi; H. Moradi

Volume 11, Issue 2 , 2021, Pages 491-504

https://doi.org/10.22067/jam.v11i2.82119

Abstract

IntroductionCantaloupe is a one-year-old herb of gourds and edible fruit with very good properties. Cantaloupe is one of the best sources of vitamin A and is rich in beta carotene, which is converted into vitamin A in the body. In addition, it contains other useful nutrients such as potassium, steel, ... Read More IntroductionCantaloupe is a one-year-old herb of gourds and edible fruit with very good properties. Cantaloupe is one of the best sources of vitamin A and is rich in beta carotene, which is converted into vitamin A in the body. In addition, it contains other useful nutrients such as potassium, steel, fiber, magnesium, iodine and vitamins B5, B3, B6 and B1. Life cycle assessment in recent years has become an appropriate tool for assessing environmental impacts in agricultural and food industries. The purpose of this study was to evaluate the life cycle assessment of this horticultural crop in terms of energy consumption and the environmental impacts in the city of Iwan West, Ilam province.Materials and MethodsThe data were collected from dryland cantaloupe producers in the city of Iwan West, Ilam province using questionnaires and interviews were collected from farmers. In this study, four important energy indices were energy use efficiency (EUE), energy productivity (EP), specific energy (SE), and net energy gain (NEG). Environmental impacts on dryland cantaloupe production were evaluated using a life cycle assessment approach and the obtained indexes were calculated using the CML 2 baseline 2000 model. Ecoinvent databases were used to access needed information and data analysis was done with Simapro software. In a life cycle assessment project, all production processes of a product from the stage of extraction of materials to disposal of the remaining waste from the product are reviewed and the results of the reduction of environmental degradation are applied. Each life cycle assessment project has four essential steps including, goal and scope definition, life cycle inventory, environmental impact assessment, and interpretation.Results and DiscussionInput and output energy analysis in dryland cantaloupe productionThe total input and output energies for dryland cantaloupe were calculated to be 39021.59 and 39190.43 MJ ha-1, respectively. Diesel fuel, agricultural machinery and nitrogen fertilizers were the most widely used energy inputs with 51%, 24%, and 14%, respectively. Energy use efficiency for dryland cantaloupe production was calculated at 1.004.Analysis of environmental impacts in dryland cantaloupe productionIn this study, the global warming potential per produced product in dryland cantaloupe production was estimated to be equal to 202.45 kgCO2 eq. from among inputs, diesel fuel had the most impact on the effects of abiotic depletion and ozone layer depletion, and in all parts of the effects of agricultural machinery and nitrogen fertilizers, the largest share of pollutants was allocated. The results of normalization showed that the effect of marine aquatic ecotoxicity and freshwater aquatic has the highest environmental burden on dryland cantaloupe production.ConclusionThe results of energy analysis showed that the total energy inputs were equal to 39021.59 MJ ha-1. Among inputs of diesel fuel, agricultural machinery, and nitrogen fertilizer were the most consumed energy inputs. The energy use efficiency index and the net energy in this study were 1.004 and 168.84 MJ ha-1, respectively. The results of environmental impacts had shown that diesel fuel, nitrogen fertilizer, and agricultural machinery had been most affected. It is recommended that proper management of agricultural machinery, equipping fields with new and suitable machines and avoiding the use of tractors and worn-out tools should be put in order to minimize the energy consumption and environmental pollutants generated by the production. Less use of chemical fertilizers (especially nitrogen) and its replacement with organic fertilizers can also be affected.

Research Article

Evaluation Energy Flow and Analysis of Energy Economy for Irrigated Wheat Production in Different Geographical Regions of Iran

A. Vahedi; S. Zarifneshat

Volume 11, Issue 2 , 2021, Pages 505-523

https://doi.org/10.22067/jam.v11i2.81747

Abstract

Introduction Agriculture is an energy conversion process. In this process, solar energy, fossil fuel, and electricity are converted mainly into food and fiber. In the agricultural section, the trend of energy consumption increases rapidly every year. Constraints on agricultural land, population ... Read More Introduction Agriculture is an energy conversion process. In this process, solar energy, fossil fuel, and electricity are converted mainly into food and fiber. In the agricultural section, the trend of energy consumption increases rapidly every year. Constraints on agricultural land, population growth, changes in infrastructure, and a trend towards high living standards have contributed to increase energy use in the agricultural sector. Fuel, electricity, machinery, seeds, chemical fertilizers, and chemical pesticides have a significant share in supplying energy sources. Effective use of energy in agriculture reduces environmental problems and prevents the destruction of natural resources and develops sustainable agriculture as an economic production system. Wheat is the most strategic crop in Iran that more than 50.39% of arable land belongs to wheat. Materials and Methods The current study has been done with the objects of evaluation of inputs and crop yield, input and output energy, and energy indices for irrigated wheat for seven provinces such as Alborz, Isfahan, Ardebil, Khorasan-e Razavi, Khuzestan, Golestan, and Hamadan. For this purpose, the required information gathered via study of publications, face to face interview with experts and leading farmers, and questionnaire completion by the irrigated wheat farmers in different cities of each understudy province. Then, with the help of equivalent energy equations, input and output energy and energy indices were calculated. In this research, simple random sampling method was used.Results and DiscussionAccording to the results, total input energies of Alborz, Isfahan, Ardebil, Khorasan-e Razavi, Khuzestan, Golestan, and Hamadan provinces were calculated with 45458.84, 92714.8, 38755.34, 104701, 50971.2, 26198, and 49362. 64 MJ ha-1 respectively, while the output energy for those provinces were 162169.28, 131958.8, 77381.39, 122297, 141901.2, 134106, and 125511.69 MJ ha-1, respectively. The maximum share of energy input for Alborz, Ardebil, Khuzestan, Golestan, and Hamadan provinces were regarding to chemical fertilizers with amounts of 43.06, 43.16, 58.33, 38.05, and 47.57 percent, respectively, while irrigation energy requirement had maximum share in Isfahan and Khorasan-e Razavi with 62.36 and 57.17 percent, respectively. The minimum share of energy input for Alborz, Isfahan, Ardebil, Khorasan-e Razavi, and Golestan provinces was calculated for labor energy requirement with 0.39, 0.29, 0.79, 0.18, and 0.26 percent, respectively, while in Khuzestan and Hamadan, chemicals consumed the lowest energy with 0.55 and 0.89 percent, respectively. Share of direct energies for all understudy provinces were 44.61, 72.13, 41.22, 67.48, 30.75, 39.44, and 39.91 percent, share of indirect energies were 55.39, 27.87, 58.78, 32.52, 69.25, 60.56, and 60.09 percent, share of renewable energies were 27.99, 65.91, 32.35, 60.57, 19.26, 34.92, and 35.16 percent, and share of nonrenewable energies were 72.01, 34.09, 67.65, 39.43, 80.74, 65.08, and 64.84 percent, respectively. Energy ratio for Alborz, Isfahan, Ardebil, Khorasan-e Razavi, Khuzestan, Golestan, and Hamadan provinces were 3.57, 1.42, 3.48, 1.17, 2.78, 5.12, and 2.54, respectively, and energy productivities were 0.26, 0.11, 0.26, 0.08, 0.21, 0.38, and 0.18 kg MJ-1, respectively. Average input energy, output energy, energy ratio, energy productivity, and net energy gain for all provinces were 58308.83 MJ ha-1, 136092.15 MJ ha-1, 2.87, 0.212 kg MJ-1 and 77783. 31 MJ ha-1, respectively. Total input energy cost for irrigated wheat production was 57.966 ×106 Rial ha-1. The Energy intensiveness, Energy intensiveness value, Energy intensity cost, and Energy ratio cost were found as 1.299 MJ (103 Rial)-1, 0.641 MJ (103 Rial)-1, 10853.05 Rial kg-1, and 1.21, respectively.Conclusion In order to reduce the share of indirect energy and non-renewable energy, organic fertilizers should be replaced by chemical fertilizers and plant residues in the field. Minimum tillage should also be used in land preparation operations to reduce fuel consumption, maintain organic matter and soil moisture and reduce soil erosion. To compensate for some of the elements taken from the soil by the plant and the increase of organic matter and fertility of the soil, it is recommended to return part of the plant residues to the soil. The use of combined machines that can perform several simultaneous operations and minimizing and protecting soil tillage to reduce fossil fuel consumption through minimum use of machinery should be investigated as a national necessity.

Research Article

Ranking the Effective Factors in the Technology Acceptance Model for the Actual Use of Agricultural Automation (Case study: Ardebil)

M. Salimi; R. Pourdarbani; B. Asgarnezhad Nouri

Volume 11, Issue 2 , 2021, Pages 525-534

https://doi.org/10.22067/jam.v11i2.81398

Abstract

IntroductionIn Iran, due to population growth and rising costs in the coming years and supply of food needs, there should be solutions for more production, with less waste, so the presence of robots can be justified for more production, reducing waste and reducing current costs. The present study investigates ... Read More IntroductionIn Iran, due to population growth and rising costs in the coming years and supply of food needs, there should be solutions for more production, with less waste, so the presence of robots can be justified for more production, reducing waste and reducing current costs. The present study investigates the factors affecting the adoption of automation in agriculture in Ardabil within the framework of the constructive factors of "Technology Acceptance Model" and examining the applicability of this model in the research community.Materials and MethodsIn the present study, the conceptual model factors include perceived usefulness, perceived ease of use, attitude toward use, and the intention to use, that affect the dependent variable of automation. Six of the first hypotheses of this study are based on the study of the significant relationships between each pair of variables in the framework of the "Technology Acceptance Model", and the applicability of the "Technology Acceptance Model" in the research community is defined in the seventh hypothesis. The method of this research is surveyed and data collection tool is a questionnaire designed based on technology acceptance model (TAM). In this research, the population of 27670 people were investigated that include university staffs-farmers and managers of ministry of agriculture in Ardabil. Using Cochran formula, 380 of them were selected in the form of stratified random sampling as sample size. Validity was confirmed by experts in agricultural management and mechanization, using Cronbach's alpha (0.958). Also, descriptive and inferential statistics were used and data analysis was performed using SPSS20 software.Results and DiscussionThe findings of this study showed that the technology acceptance model with a final determination coefficient of 635.0 was used in the studied population, which means that the applicability of the model (TAM) was very suitable for agricultural study in Ardabil. The priorities for the effects of the variables of the technology acceptance model for the actual use of automation were perceived ease of use (1.284), perceived usefulness (1.280), intention to use (0.954) and attitude (0.478) respectively.Using the results of modeling, it was also found that the correlation coefficient between individual factors and the perceived usefulness of the application of automation has a strong relationship. The correlation coefficient between the two variables is negative and indicates that with increasing individual factors, the level of perceived usefulness of the use of automation also decreases, and vice versa. However, experience, self-confidence and financial situations, level of education, land area, number of family workforce, have not greatly increased productivity and reduced production costs and helped agricultural activities (understanding the usefulness of technology).The relationship can be considered as the most important factor in holding weak and undesirable classes in creating knowledge, experience and poor self-confidence of the respondents towards accurate agricultural technology. In these classes, the content should be presented in a more specialized and practical way to make them understand the usefulness of precision agricultural technology.According to the results of this study, the organization of workshops and periodic training courses, as well as the introduction of this technology in journals and publications and social media is recommended.ConclusionConsidering the confirmation of the hypotheses of this research and the priorities obtained for the effects of the structures of the technology acceptance model, it can be concluded that as it is known, the two main constituents of this model, perceived ease of use and perceived usefulness have had a significant impact on the amount of technology used, or, in other words, technology acceptance. The perceived usefulness is the most effective factor in the actual use of automation. In following, perceived ease of use, intention to use, and the attitude was ranked respectively.

Research Article

Challenges and Opportunities in Development of Agricultural Mechanization in Ahvaz County using SWOT Method

N. Moradi; A. Asakereh; M. J. Sheikhdavoodi

Volume 11, Issue 2 , 2021, Pages 535-548

https://doi.org/10.22067/jam.v11i2.83348

Abstract

IntroductionAgricultural mechanization is defined as the use of energy and production resources, machinery and equipment in agriculture. Modern agriculture is heavily dependent on mechanization, and machinery, equipment, energy resources, and related management processes are heavily used in the food ... Read More IntroductionAgricultural mechanization is defined as the use of energy and production resources, machinery and equipment in agriculture. Modern agriculture is heavily dependent on mechanization, and machinery, equipment, energy resources, and related management processes are heavily used in the food and non-food production. Agricultural mechanization is the major energy-consuming factor in the agricultural system and has benefits such as reducing operating costs and agricultural toil. SWOT analysis has been used in numerous studies on agricultural development and mechanization. SWOT analysis, as an effective mathematical approach, is used for strategic planning and identifying system strengths, weaknesses, opportunities, and threats. In this study, SWOT method was used to evaluate the internal and external factors of agricultural mechanization development in Ahvaz County to present appropriate strategies.Materials and MethodsThe main purpose of this study is to use SWOT analysis to determine the best strategic planning for agricultural mechanization development in Ahwaz. Therefore, the strengths, weaknesses, opportunities and threats of agricultural mechanization development in Ahwaz were studied within the framework of the SWAT program. Ahvaz is considered the agricultural hub of Khuzestan province. Ahvaz, the capital of Khuzestan province, accounts for about 35 percent of the total area under cultivation in the province. Karun, Dez and Karkheh rivers, as the main source of agricultural water, pass through Ahvaz lands. SWOT analysis is a sophisticated but effective way of strategically analyzing a system that considers both the internal and external environment. Opportunities and threats are the external factors of a system, and strengths and weaknesses, the internal factors of the system. Opportunities are attractive external factors that illustrate the reasons for system development and improvement. These are essential elements in the system's external environment that the system can exploit to its advantage. In addition, threats are major external factors that can adversely affect the system. The extent to which the company's internal environment corresponds to the external environment is expressed in terms of strategic fit. SWOT analysis offers four aggressive, conservative, competitive and defensive strategies. Various methods have been used to collect data, including face-to-face interview, questionnaires and a database provided by the Ministry of Jihade-Agriculture of Iran. Data were obtained using the questionnaire from 189 farmers and experts. After classifying and monitoring the data, internal and external factors evaluation matrices were prepared. After analyzing these matrices, the importance and weight of the parameters (i.e. strengths, weaknesses, threats and opportunities for agricultural mechanization development) were determined. Finally, the SWOT analysis matrix was prepared to determine the agricultural mechanization development strategy in Ahvaz.Results and DiscussionAnalyzing the matrix of external factors evaluation showed that the low tendency to invest in agricultural production, less attention by officials to the agricultural sector and water scarcity for irrigation were the most important threats. On the other hand, parameters such as the possibility of providing agricultural facilities and loans to farmers, the large number of agricultural mechanization graduates, the high incentive for farmers to use agricultural machinery, and the possibility of producing agricultural equipment are the most effective opportunities for agricultural mechanization development in Ahvaz County. Also, the results show that vast and flat agricultural lands are the most important strengths of the area, while the high cost of machinery is the most important weakness. SWOT analysis showed that the region is not internally desirable despite relatively good opportunities in external factors, as weaknesses are relatively dominant. The final scores of the internal and external factors evaluation matrices were 2.437 and 2.593, respectively, indicating that competitive strategy should be considered. Therefore, taking advantage of important opportunities for mechanization development in Ahvaz, important weaknesses should be reduced or eliminated.ConclusionThe purpose of this study was to prepare an appropriate strategic planning for the development of agricultural mechanization in Ahvaz. SWOT matrix was calculated, based on internal and external factors evaluation matrices. The matrix was then used to identify the strengths, weaknesses, opportunities, and threats of agricultural mechanization development in this region. Also, the weight of the most important factors (i.e. strengths, weaknesses, opportunities, and threats of agricultural mechanization development) was calculated. Ultimately, based on the matrix results, to develop agricultural mechanization in this region, the competitive strategy was proposed.

Volume 14 (2024)

Volume 13 (2023)

Volume 12 (2022)

Volume 11 (2021)

Volume 10 (2020)

Volume 9 (2019)

Volume 8 (2018)

Volume 7 (2017)

Volume 6 (2016)

Volume 5 (2015)

Volume 4 (2014)

Volume 3 (2013)

Volume 2 (2012)

Volume 1 (2011)

Volume & Issue: Volume 11, Issue 2 - Serial Number 22, 2021 (Fall and Winter)

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