Modeling
S. Sharifi; N. Hafezi; M. H. Aghkhani
Abstract
Introduction
Efficient use of energy in paddy production can lower greenhouse gas emissions, safeguard agricultural ecosystems, and promote the growth of sustainable agriculture. Meanwhile, intelligent agriculture has come to the aid of farmers and policy-makers by harnessing cutting-edge technologies, ...
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Introduction
Efficient use of energy in paddy production can lower greenhouse gas emissions, safeguard agricultural ecosystems, and promote the growth of sustainable agriculture. Meanwhile, intelligent agriculture has come to the aid of farmers and policy-makers by harnessing cutting-edge technologies, which will lead to sustainable welfare and the comfort of human society in the present and the future. Therefore, this study aimed to analyze energy consumption and production, as well as model and optimize the yield of two paddy cultivars using Artificial Bee Colony (ABC) and Genetic Algorithms (GA).
Materials and Methods
Extensive research data was collected by thoroughly examining documentary and library resources, as well as conducting face-to-face questionnaires with 120 paddy farmers and farm owners in Rezvanshahr city, located in the province of Guilan, Iran, during the 2019-2020 production year. The farms consisted of 80 high-grading and 40 high-yielding paddies. The independent variables were machinery, diesel and gasoline fuels, electricity, seed, compost and straw, biocides, fertilizers, and labor. The dependent variable was paddy yield per hectare [of the farm area]. In the first step, energy consumption and production were calculated by multiplying the variables by their corresponding coefficients. In the second step, all the variables that maximize paddy yield were entered into MATLAB software. An artificial bee colony (ABC) algorithm with a novel and straightforward elitism structure was utilized to enhance the fitness function of the genetic algorithm (GA). The Sphere, Repmat, and Unifrnd functions were employed to determine the objective function, define the position of the bee colony, and quantify the position of the bee colony, respectively. In each generation, 900 new solutions were created, and the algorithm iterated 200 times. For the genetic algorithm, the population was defined as a double vector with a size of 100.
Results and Discussion
The findings revealed that the Hashemi (high-grading) paddy cultivar had an average energy consumption and production of 55.973 and 30.742 GJ·ha-1, respectively. The Jamshidi (high-yielding) paddy cultivar had an average energy consumption of 54.796 GJ·ha-1 and double the energy production of the Hashemi at 62.522 GJ·ha-1. In both cultivars, agricultural machinery consumed the highest amount of energy, while straw consumed the lowest amount. The average energy consumption of tractors in the Hashemi and Jamshidi cultivars was 25.111 and 25.865 GJ·ha-1, respectively, accounting for 44.862% and 47.202% of the total average consumed energy. This undoubtedly demonstrates the significant effect of this input and reflects the operators' skill and experiential knowledge. The evaluation indexes, including R², RMSE, MAPE, and EF, as well as statistical comparisons such as mean, STD, and distribution, consistently demonstrated that the ABC algorithm provided the essential conditions for the fitness function. The results of the bee-genetic algorithm optimization revealed that the majority of the consumed resources could be effectively managed on the farm to closely match optimal conditions. Through this optimization, energy consumption in the Hashemi and Jamshidi cultivars was reduced by 53.96% and 39.41%, respectively.
Conclusion
Given its impressive performance and potential for minimizing energy consumption, the ABC-GA algorithm offers an opportunity for policymakers in energy resource management and rice industry managers to develop innovative strategies for significantly reducing energy usage in rice production. This approach could lead to more sustainable and efficient practices in the agricultural sector.
Post-harvest technologies
S. Sharifi; M. H. Aghkhani; A. Rohani
Abstract
IntroductionOn the field and in the paddy milling factory dryer losses have always been challenging issues in the rice industry. Different forms of losses in brown rice may occur depending on the field and factory conditions. To reduce the losses, proper management during pre-harvest, harvesting, and ...
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IntroductionOn the field and in the paddy milling factory dryer losses have always been challenging issues in the rice industry. Different forms of losses in brown rice may occur depending on the field and factory conditions. To reduce the losses, proper management during pre-harvest, harvesting, and post-harvest operations is essential. In this study, different on-field drying and tempering methods were investigated to detect different forms of brown rice losses.Materials and MethodsThe present study was conducted on the most common Hashemi paddy variety during the 2019-2020 season in Talesh, Rezvanshahr, and Masal cities in the Guilan province, Iran with 0.2 hectares and 5 paddy milling factory dryers. On the fields, the method and date of tillage, irrigation, and transplanting used in all experimental units were the same. Moreover, the same amount of fertilizer and similar spraying methods were used across all experiments. For the pre-drying process on the fields, the following three pre-drying methods were applied on the harvest day: A1) The paddies were spread on the cut stems for insolating, A2) The paddies were stacked and stored after being placed on the cut stems for 5h, and A3) The paddies were covered with plastic wrap and stored after 5h of insolating. The first method (A1) is the most common in the area and was chosen as the control treatment. For the second step of the process, the time interval between the on-field pre-drying and threshing was considered: B1) 14 to 19h post-harvest; B2) 20 to 24h post-harvest, and B3) 25 to 29h post-harvest. Afterward, methods A1 to A3 were combined with methods B1 to B3 and feed into an axial flow-thresher at 10 kg min-1, 550 rpm PTO, and two levels of moisture content at 19 and 26 percent (% w.b). The third process was two-stage or three-stage tempering for 10 or 15 hours resulting in four levels (C1 to C4) and was done in the conventional batch type dryer under temperatures of 40 and 50 ˚C and airspeeds of 0.5 and 0.8 m s-1 in paddy milling factories. At the end of each process, a 100g sample was oven-dried for 48h and a microscope achromatic objective 40x was used to detect incomplete horizontal or vertical cracks, tortoise pattern cracks, and immature and chalky grains. The equilibrium moisture content was determined to be 7.3 percent. Losses properties were analyzed using a completely randomized factorial design with a randomized block followed by Tukey's HSD test at the 5% probability and comparisons among the three replications were made.Results and DiscussionResults demonstrated that the stack and plastic drying methods significantly increased the percentage of losses. In the plastic drying method, the percentage of chalky grains and tortoise pattern cracks was higher than other forms of loss. In the first process, irrespective of the pre-drying method, the losses were reduced at a lower level of moisture content. At the end of the first stage, losses in the spreading method were significantly lower at 19% moisture content. Threshing the plastic-wrapped paddies after 14 to 19 hours at 19% moisture content resulted in the maximum threshing loss of 8.446% and over half of the grains were chalky or had tortoise pattern cracks. The threshing loss was halved (4.443%) for paddies threshed 25 to 29h after spreading at a moisture content of 26%. The mean of losses in the second step of the process were 7.229, 5.585, and 5.156% for the time interval between the on-field pre-drying and threshing of 14 to 19h, 20 to 24h, and 25 to 29h, respectively. In the last step of the process in paddy milling factory dryers, there was no significant difference in the minimum percent of losses between 10 and 15 hours of three-stage tempering at 40 °C and with 0.5 m s-1 airspeed. Furthermore, maximum total losses with the most incomplete horizontal and vertical cracks occurred in the two-stage 10h tempering at 50 °C and with 0.5 and 0.8 m s-1 airspeed.ConclusionFood security has always been a critical matter in developing countries. Furthermore, identifying the source of losses in the fields and the factories is one way to reduce losses and achieve food security. Stacking or wrapping the paddies in plastic after pre-drying on the fields for 5h is not recommended in terms of its effect on increasing the percentage of brown rice losses. Additionally, due to the importance of factory dryer scheduling in the management of the losses, it is recommended to use a three-stage 10h tempering at 40 °C and with 0.5 m s-1 airspeed.
S. I. Shariati; M. H. Aghkhani; M. R. Golzarian; A. A. Akbari
Abstract
IntroductionRobots have been used for material handling for many years, and their applications have greatly expanded with the integration of intelligent technologies. While numerous researchers have proposed various robots for this field, it is crucial to design customized configurations that are suitable ...
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IntroductionRobots have been used for material handling for many years, and their applications have greatly expanded with the integration of intelligent technologies. While numerous researchers have proposed various robots for this field, it is crucial to design customized configurations that are suitable for agricultural farms. However, research in our country has been limited to a few mobile agricultural robots. The main focus of this paper is to design and model workspaces and analyze the kinematics of manipulators in agricultural settings.Materials and MethodsThis article investigates the workspace and kinematics of a robot manipulator to design and manufacture a four-DOF manipulator for farming. This manipulator will be capable of performing a variety of tasks, but the goal of this project is to enable it to load and unload materials and products on the farm as an auxiliary force for the farmer.When designing and analyzing a manipulator, the first step is to determine the specific task that the robotic arm will perform. For example, consider a scenario where the task involves loading or unloading forage packages from a trailer at a designated location. This task specification forms the basis for further design and analysis, ensuring that the manipulator is appropriately designed to meet the requirements of the task.An intelligent robotic arm that is attached to a tractor can perform this operation in the shortest possible time without the intervention of human workers. Otherwise, a large number of laborers would be required to move boxes weighing 10 kg over distances of 3 to 4 meters and heights of 1 to 2 meters, which would require a great deal of torque.At this stage, the design of the arm kinematics model, direct kinematic equations, velocity kinematics, and Jacobian matrix solving were performed. The calculations were carried out using two methods: manual calculation and kinematic modeling in MATLAB software for three arm configurations in two simulation tests. The results of both methods were compared.The workspace analysis of the selected manipulator configurations, as well as the use of arm kinematic performance evaluation indices, were illustrated in graphs.Results and DiscussionThe issue of moving forage packages on the farm is described below. If a farmer were to move 48 packages of fodder weighing about 10 kg manually (using human workers) in the workspace modeled in Figure 10, each package would take an average of 30 seconds to be moved reciprocally along an unobstructed path. Hence, it would take approximately 24 minutes to move all the packages. However, the linear speed of the final operator of the robot arm during the first test was found to be 1 meter per second, which is 3.7 times faster than the manual work scenario, and the total movement of the packages can be completed in about 6.5 minutes.Upon analyzing the velocity diagrams of the final performer in both tests, it becomes evident that there is not much variation in speed and acceleration due to the change in configurations. The evaluation of robot workspace indicators was conducted using two methods: workspace index and structural length index. These indicators were calculated for all three configurations, and the results indicated that Configuration Type 1 was the most suitable option. Furthermore, the manipulability index of the robot arm was assessed based on the obtained diagrams for all three configurations in the two tests. It was observed that Configuration Type 1 outperformed the other two types in terms of score, indicating its superior performance. This aligns with the suggestion made by Yoshigawa for the first three joints of the Puma robot.Overall, the results suggest that Configuration Type 1 is one of the most favorable options, ensuring better performance for the final performer.ConclusionOne of the main considerations when using robots in agriculture is the appropriate kinematic design of joints and links for work operations. Using the example of robots assisting with moving products on the ground, it can be seen that using robots significantly reduces the time required compared to manual labor. Furthermore, in terms of energy consumption and cost within a certain period, the use of robots has economic justification.Based on the studies conducted, Configuration Type 1 passed the kinematic path in both tests with a higher manipulability index and a more suitable workspace index based on both calculated criteria. Therefore, this configuration is recommended for the design of robots for the operation of moving products on the ground.
A. Moghimi; A. Sazgarnia; M. H. Aghkhani
Abstract
IntroductionPistachio production has been adversely affected by Psylla, which is a devastating insect. The primary goal of this study was to select sensitive spectral bands to distinguish pistachio leaves infected by Psylla from healthy leaves. Diagnosis of psylla disease before the onset of visual cues ...
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IntroductionPistachio production has been adversely affected by Psylla, which is a devastating insect. The primary goal of this study was to select sensitive spectral bands to distinguish pistachio leaves infected by Psylla from healthy leaves. Diagnosis of psylla disease before the onset of visual cues is crucial for making decisions about topical garden management. Since it is not possible to diagnose psylla disease even after the onset of symptoms with the help of color images by drones, hyperspectral and multispectral sensors are needed. The main purpose of this study was to extract spectral bands suitable for distinguishing healthy leaves from psylla leaves. For this purpose, in this paper, a new method for selecting sensitive spectral properties from hyperspectral data with the high spectral resolution is presented. The intelligent selection of sensitive bands is a convenient way to build multispectral sensors for a specific application (in this article, the diagnosis of psylla leaves). Knowledge of disease-sensitive wavelengths can also help researchers analyze multispectral and hyperspectral aerial images captured by satellites or drones.Materials and MethodsA total number of 160 healthy and diseased leaves were scanned in 64 spectral bands between 400-1100 nm with 10 nm spectral resolution. A random forest algorithm was used to identify the importance of features in classifying the dataset into diseased and healthy leaves. After computing the importance of the features, a clustering algorithm was developed to cluster the most important features into six clusters such that the center of clusters was 50 nm apart. To transfer the hyperspectral dataset into a multispectral dataset, the reflectance was averaged in spectral bands within ±15 nm of each cluster center and achieved six broad multispectral bands. Afterwards a support vector machine algorithm was utilized to classify the diseased and healthy leaves using both hyperspectral and multispectral datasets.Results and DiscussionThe center of clusters were 468 nm, 598 nm, 710 nm, 791 nm, 858 nm, and 1023 nm, which were calculated by taking the average of all the members assigned to the individual clusters. These are the most informative spectral bands to distinguish the pistachio leaves infected by Psylla from the healthy leaves. The F1-score was 90.91 when the hyperspectral dataset (all bands) was used, while the F1-score was 88.69 for the multispectral dataset. The subtle difference between the F1-scores indicates that the proposed pipeline in this study was able to select appropriately the sensitive bands while retaining all relevant information.ConclusionThe importance of spectral bands in the visible and near-infrared region (between 400 and 1100 nm) was obtained to identify pistachio tree leaves infected with psylla disease. Based on the importance of spectral properties and using a clustering algorithm, six wavelengths were obtained as the best wavelengths for classifying healthy and diseased pistachio leaves. Then, by averaging the wavelengths at a distance of 15 nm from these six centers, the hyperspectral data (64 bands) became multispectral (6 bands). Since the correlation between the wavelengths in the near-infrared region was very high (more than 95%), out of the three selected wavelengths in the near-infrared region (710, 791, and 1023), only the 710-nm wavelength, which was closer to the visible region, was selected. The results of classification of infected and diseased leaves using hyperspectral and multispectral data showed that the degree of classification accuracy decreases by about 2% and if only 4 bands are used, the degree of accuracy decreases by about 3%.The results of this study revealed that the proposed framework could be used for selecting the most informative spectral bands and accordingly develop custom-designed multispectral sensors for disease detection in pistachio. In addition, we could reduce the dimensionality of the hyperspectral datasets and avoid the issues related to the curse of dimensionalitylity.
S. Ahmadipour; M. H. Aghkhani; J. Zareei
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 ...
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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.
M. H. Aghkhani; M. Baghani
Abstract
The eggshell of birds, as a natural shield and package, protects the tissues inside it from microbial and mechanical damages. Proper intake of calcium, as an important and effective factor in increasing the strength and quality of the eggshell, could reduce complications. In this paper, the effect of ...
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The eggshell of birds, as a natural shield and package, protects the tissues inside it from microbial and mechanical damages. Proper intake of calcium, as an important and effective factor in increasing the strength and quality of the eggshell, could reduce complications. In this paper, the effect of dietary calcium at five different levels on engineering features of Japanese quail eggs in a in their first laying period was investigated. The values for an average of mass, volume, specific mass, shell thickness, major diameter, central diameter and rupture force along the longitudinal and transverse axes were measured. Rupture energy or toughness, slope of the rupture curve (hardness), deformation along the longitudinal and transverse axis to the point of rupture as well as longitudinal and transverse deformation of 450 tested quail eggs (3 period of time, 5 treatment of calcium, 5 replication, 6 observation) were measured. The characters of the specific mass, shell thickness, rupture force, and slope of the rupture curve of quail eggs indicate the strength of quail egg. In this study, variations in all parameters indicating shell strength at different levels of dietary calcium were consistent with each other. Five different treatments with 1.5%, 2%, 2.5%, 3%, and 3.5% calcium content were supplied for the study. By increasing the calcium content of the quail diet from 1.5 to 3 wt%, the volume and weight of quail eggs dropped and shell thickness was reinforced. According to the results, the shell strength of quail eggs along the transverse axis was slightly less than the longitudinal axis, but the flexibility and energy required for quail egg rupture were much greater across the longitudinal axis.
Modeling
J. Baradaran Motie; M. H. Aghkhani; A. Rohani; A. Lakziyan
Abstract
Introduction Presently, the loss of ground water levels and the increase in dissolved salts have given importance to the determination of salinity and the management of their variations in irrigated farms. Soil electrical conductivity is an indirect method to measure soil salts. The direct electrode ...
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Introduction Presently, the loss of ground water levels and the increase in dissolved salts have given importance to the determination of salinity and the management of their variations in irrigated farms. Soil electrical conductivity is an indirect method to measure soil salts. The direct electrode contact method (Wenner method) is one of the widely used methods to rapidly measure soil ECa in farms. However, soil scientists prefer soil actual electrical conductivity (saturated extract electrical conductivity) (ECe) as an indicator of soil salinity, though its measurement is only possible in the laboratory. The aim of this study was to find a relationship between the prediction of soil actual electrical conductivity (ECe) in terms of temperature, moisture, bulk density and apparent electrical conductivity of soil (ECa). Thereby, the estimation of ECe would allow the partial calculation of ECa that is dependent upon soil salinity and dissolved salts. Materials and Methods This study used RBF neural network in Box-Behnken statistical design to explore the impacts of effective parameters on direct contact method in the measurement of soil ECa and provided a model to estimate ECe from ECa, temperature, moisture content and bulk density. In this study soil apparent electrical conductivity (ECa) was measured by direct contact (Wenner) method. The present study considered four most effective factors: ECa (saturated paste extract EC), moisture, bulk density, and temperature (Baradaran Motie et al., 2010). Given the characteristics of farming soils in Khorasan Razavi Province (Iran), the maximum and minimum of each independent variable were assumed as 0.5-6 mS.cm-1 for ECe, 5-25% for moisture content, 1-1.8 g.cm-3 for bulk density, and 2-37°C for soil temperature. Considering the experimental design, three moisture levels (5, 15 and 25%), three salinity levels (0.5, 3.25 and 6 mS.cm-1), three temperature levels (2, 19 and 37°C) and three compaction levels with bulk densities of 1, 1.4 and 1.8 g.cm-3 were assumed in 27 trials with predetermined arrangement on the basis of Box-Behnken technique. 13 common algorithms were explored in MATLAB software package for the training of the artificial neural network in order to find the optimum algorithm (Table 4). The input layer of the network designed by integrating a Randomized Complete Block Design (RCBD) with k-fold cross-validation. Using k-fold cross-validation, 20 different datasets were generated for training and validation of RBF neural network. Results and Discussion A combination of an RCBD and k-fold cross-validation was used. The results of both training and validation phases should be considered in the selection of training algorithm. In addition, R2 of T1 training algorithm had a much lower standard deviation than other training algorithms. The lower standard deviation is, the more capable the algorithm would be in learning from different datasets. Considering all aspects, trainbr (T2) training algorithm was found to have the best performance among all 13 training algorithms of the neural network. Table 7 tabulates the results of means comparison for R2 of RBF model for both training and validation phases resulted from the application of some combinations of S and L2 factors as interaction. As can be observed, R2 = 0.99 for all of them with no significant difference. However, the magnitude of order differed between training and validation phases. Given the importance of the training phase, L2=9 and S=0.1 were regarded as the optimum values. The sensitivity analysis of the network revealed that soil ECa, moisture, bulk density, and temperature had the highest to lowest impact on the estimation of soil ECe, respectively. This model can improve the precision of soil ECa measurement systems in the estimation and preparation of soil salinity maps. Furthermore, this model can save in time of data analysing and soil EC mapping because it does not need data recollection for the calibration of systems. A validation prose was done with a 60 field collected data set. The results of validation show R2=0.986 between predicted and measured ECa. Conclusion The present research focused on improving the precision of soil ECe measurement on the basis of easily accessible parameters (ECa, temperature, moisture, and bulk density). In conventional methods of soil EC mapping, the systems only measure soil ECa and then calibrate it to ECe by collecting some samples and using statistical methods. In this study, Soil ECe was estimated with R2 = 0.99 by a multivariate artificial neural network model with the inputs, including ECa, temperature, moisture, and bulk density of soil without any need to collect further soil samples and calibration process. The Bayesian training algorithm was introduced as the best training algorithm for this neural network. Thereby, soil EC variation maps can be prepared with higher precision to estimate the spatial spread of salinity in farms. Also, the results imply that soil ECa, moisture, bulk density and temperature have the highest to lowest effectiveness on the estimation of soil ECe, respectively.
M. Baghani; M. H. Aghkhani
Abstract
IntroductionIran as one of the largest producers of poultry in Asia and plays major role in feeding the world's population, particularly in the poultry industry. Research about this industry will help to improve the quality and the quantity of products. Increasing of the concentration of toxic gases ...
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IntroductionIran as one of the largest producers of poultry in Asia and plays major role in feeding the world's population, particularly in the poultry industry. Research about this industry will help to improve the quality and the quantity of products. Increasing of the concentration of toxic gases such as NH3 (ammonia), CO2 (carbon dioxide), SH2 and CH4 in poultry houses comes from bird activity inside the barn is one of the basic problems of the farming. Increasing the amount of these gases more than standard level would cause heavy mortality and reductions in the production. Ammonia is one of the most toxic gases in poultry houses, which must be controlled. Different studies have been carried out on measurement of ammonia emissions from poultry houses to reduce energy consumption and reduce emissions of ammonia. But no specific study has been found on ammonia emissions in Iran and there is no reliable documents of ammonia emissions from poultry in this country.Materials and MethodsIn this study a poultry house with 18 thousand chickens was used to measure the emission rate of ammonia, the effect of temperature, moisture and age of chickens on emissions of ammonia in Sabzevar city. The barn was equipped with semi-automatic mechanical ventilation. At the first step of this research all sensors was installed for data collection, i.e., air velocity, temperature, humidity and ammonia concentration. Recorded data information were stored in a central computer. Five digital sensors, model AM2303, have been used to measure the temperature and humidity of the ambient air quality. The concentration of ammonia in the air inputs and outputs of the farm was measured using an ammonia sensor model TGS2444 every 10 seconds throughout the study and recorded in the central system. The average speed of the exhaust air was measured using the hot wire anemometer probe for every fan. The outputs of all sensors was converted to digital data and transferred to the central computer using RS485 cable in each module. Converting of the sensors output to digital data reduces changing the data and probable errors. Ammonia emission rates was found by calculating the concentration of ammonia and measuring the rate of input air and fans exhaust air by ammonia gas equilibrium equation. Relation of the ammonia emission rate was achieved using affective factors such as age of the birds and inside air humidity and temperature by regression method.Results and DiscussionThe average rate of ammonia emission during broiler growing were measured 89 mg per day for each bird. Ammonia emission rates increased until the age of 37 days and then decreased after the age of 37 days. Age of birds has the highest impact coefficient and temperature and relative humidity of the barn have the least impact coefficients on the ammonia emission rate. The ammonia emission rate has also increased by increasing the age of the bird, temperature and relative humidity of the air. Comparing of the ammonia emission rate derived from regression equation with real conditions showed that the regression equation method has a high precision for estimating the ammonia emission rate.ConclusionIt is showed that the results of this research can predict the ammonia emission rate in the poultry houses and predict the required ventilation rates to minimize the amount of ammonia concentration. The results of this study can be used for automatic control system to minimize energy consumption in the poultry houses. According to the results, the reduction of temperature and humidity in poultry house can be used to reduce the ammonia level.
S. F. Mousavi; M. H. Abbaspour-Fard; M. H. Aghkhani; E. Ebrahimi; A. Soheili Mehdizadeh
Abstract
Introduction
The diagnosis of agricultural machinery faults must be performed at an opportune time, in order to fulfill the agricultural operations in a timely manner and to optimize the accuracy and the integrity of a system, proper monitoring and fault diagnosis of the rotating parts is required. ...
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Introduction
The diagnosis of agricultural machinery faults must be performed at an opportune time, in order to fulfill the agricultural operations in a timely manner and to optimize the accuracy and the integrity of a system, proper monitoring and fault diagnosis of the rotating parts is required. With development of fault diagnosis methods of rotating equipment, especially bearing failure, the security, performance and availability of machines has been increasing. In general, fault detection is conducted through a specific procedure which starts with data acquisition and continues with features extraction, and subsequently failure of the machine would be detected. Several practical methods have been introduced for fault detection in rotating parts of machineries. The review of the literature shows that both Artificial Neural Networks (ANN) and Support Vector Machines (SVM) have been used for this purpose. However, the results show that SVM is more effective than Artificial Neural Networks in fault detection of such machineries. In some smart detection systems, incorporating an optimized method such as Genetic Algorithm in the Neural Network model, could improve the fault detection procedure. Consequently, the fault detection performance of neural networks may also be improved by combining with the Genetic Algorithm and hence will be comparable with the performance of the Support Vector Machine. In this study, the so called Genetic Algorithm (GA) method was used to optimize the structure of the Artificial Neural Networks (ANN) for fault detection of the clutch retainer mechanism of Massey Ferguson 285 tractor.
Materials and Methods
The test rig consists of some electro mechanical parts including the clutch retainer mechanism of Massey Ferguson 285 tractor, a supporting shaft, a single-phase electric motor, a loading mechanism to model the load of the tractor clutch and the corresponding power train gears. The data acquisition section consists of a data analyzer (PCA-40), a personal computer, a piezoelectric accelerometer (VMI-102, DT-2234B), a tachometer and two rubber vibration absorbing elements are located between the rig’s components and the plate holder. An evaluation function was employed in order to achieve the optimal structure of neural network models by selecting the number of layers, number of cells in the layers, transfer function, training function, learning functions, performance function, and number of epochs, in such a way that the MSE of the calculated output error was minimal. The data were collected by means of the accelerometer sensor attached on the clutch mechanism, with three different working conditions (normal condition, with worn bearing, and with worn shaft), and three rotational speeds including: 1000 rpm, 1500 rpm and 2000 rpm. The Wavelet Packet Transform (WPT) was applied on the data-set for features vector extraction and the principle component analyses (PCA) was applied for dimension reduction of the features vector. The signal processing and the features extraction are the most important characteristics of the monitoring methodology, by which the working condition of the machine can be determined. These characteristics may be acquired by transforming the signals from the time domain to the frequency domain and MATLAB software is used for this purpose. This software receives the vibration data (time series of output voltage) which are in Excel files format. To remove the noise a suitable filtering procedure was used and finally the statistical parameters of time - frequency were calculated.
Results and Discussion
To verify the accuracy of the Genetic Algorithm model, the required data were collected from the training and testing steps of the Neural Network. For this purpose, the statistical parameters such as mean squared error (MSE), mean absolute error (MAE) and correlation coefficient (r) were used. The optimal parameters of the neural network obtained for the family of Db4. A trial and error procedure was used to minimize the mean square error of the network output and the desired amount of training step. During the training step, four neural networks including Db4, Db30, Db35 and Db40 achieved a gradient descent weight in the learning bias and four neural networks including Db9, Db15, Db20 and Db25 achieved a gradient descent with momentum weight in the learning bias. The two of the achieved neural networks including Db4, Db20 have circular logarithm function and the remaining networks have annular hyperbolic tangent transfer function. The most appropriate networks configuration was acquired when the network exhibited the minimal error with the training and testing data sets. The results show that the highest accuracy of the GA-ANN Artificial neural networks for all rotational speeds (1000, 1500 and 2000 rpm), and working conditions (intact gear and shaft, damaged bearing and worn shaft) observed for the network family of Db4. The highest error observed for the family of Db20 with MSE of 0.011.
Conclusions
Artificial neural networks can somewhat think and make decisions similar to an expert person. In this project in order to predict the occurrence of a failure of the clutch mechanism of MF 285 tractor, the experimental data were obtained using some sensors, and the data were transferred to a computer by means of a data analytical. By training of the neural networks, the errors were identified separately. The output data from the combined Neural Network and Genetic Algorithm shows that the performance of the prediction model is enhanced. Based on the experiments and calculations, the best data set belongs to the family of Db4 network with the least MSE equal to 4.09E-07 and r equal to 0.99999, indicating that the model could precisely detect the faulty bearings or shafts.
M. H. Aghkhani; J. Baradaran Motie
Abstract
Introduction: Separation and grading of agricultural products from the production to supply, has notable importance. The separation can be done based on physical, electrical, magnetic, optical properties and etc. It is necessary for any development of new systems to study enough on the properties and ...
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Introduction: Separation and grading of agricultural products from the production to supply, has notable importance. The separation can be done based on physical, electrical, magnetic, optical properties and etc. It is necessary for any development of new systems to study enough on the properties and behavior of agricultural products.
Some characteristics for separation are size (length, width and thickness), hardness, shape, density, surface roughness, color, speed limit, aerodynamic properties, electrical conductivity, elasticity and coefficient of static friction point.
So far, the friction properties of agricultural products used in the separating process, but the effect of electrostatic charging on static and dynamic coefficients of friction for separation had little attention. The aim of this study was to find out the interactions between electrostatic and friction properties to find a way to separate products that separation is not possible with conventional methods or not sufficiently accurate. In this paper, the separation of close and smiley pistachios by electrostatic charging was investigated.
Materials and Methods: Kallehghoochi pistachio cultivar has the top rank in production in Iran. Therefore, it was used as a sample.
The experimental design that used in this study, had moisture content at three levels (24.2, 14.5 and 8.1 percent), electric field intensity at three levels (zero, 4000 and 7000 V), speed of movement on the surface at three levels (1300, 2500 and 3300 mm per minute), friction surface (galvanized sheet iron, aluminum and flat rubber) and pistachio type at two levels (filled splits and closed) that was measured and analyzed in completely randomized factorial design.
A friction measuring device (built in Ferdowsi University of Mashhad) used to measure the friction force. It has a removable table that can move in two directions with adjustable speed. The test sample put into the vessel with internal dimensions of 300 × 150 × 25 mm and with wall thickness of 5 mm placed on trolleys. In the bottom of the container a separate aluminum plate was installed as the negative pole of the electric field. The friction plates as a positive pole placed on top of the sample. There were no contact between friction plates and walls of vessel (samples were about 2 to 3 mm higher from the edges of wall).
Frictional force changes due to movement of table, measured and recorded by an accurate load cell. From force-displacement curves, the coefficient of dynamic friction and static coefficient of friction calculated. In general, according to the experimental design, 486 tests were performed.
Results and Discussion: According to the results of statistical analysis, there is significant interaction affect between pistachios type and electrical field, as well as, the interaction between electrical field and speed, on dynamic coefficient of friction. It means two pistachio types can be separated by electrical charging.
Different physical properties of surface of filled non-splits pistachio nuts (such as corners and edges) and filled splits ones, caused differences in the distribution of electric charge and as a result, its interaction with the electric field were significant.
Changes in dynamic coefficient of friction according to the electric field intensity at different levels of moisture content and speed on the friction surfaces of iron, aluminum and rubber, was drawn in Fig.4, 5 and 6, respectively. These figures reflected the reduction of dynamic coefficient of friction by increasing the movement speed of table.
According to Fig.7, increasing the intensity of the electric field increases the dynamic coefficient of friction. Because this leads to build the opposition charge on samples and galvanized iron sheets, and with increase of electrical field, these charges will rise.
Fig.9 shows different trends of variation of dynamic coefficient of friction against moisture on rubber surface. This chart shows the higher coefficient of friction of filled non-splits samples than filled splits in all cases and shows an increasing trend with increasing humidity.
Conclusions: Table 2 presents the dynamic coefficients of friction in different states on different levels of moisture content. According to this table, the maximum difference was achieved in moisture content of 8% (which is close to the product storage moisture) in rubber surface with field strength of 7000 V and 1300 mm per minute speed. On 14 percent moisture content, the maximum difference was achieved on aluminum surface by 2500 millimeter per minute speed and 7000 V field strength. By the results, on 24 percent moisture content (the moisture close to peeling process) the maximum difference between filled non-splits and filled splits pistachios friction was achieved on aluminum surface, 7000 V electric field strength and 2500 millimeter per minute table speed.
Thus, to have a separation system, the aluminum surface, 7000 V electric field strength and adjustable speed between 1300 to 2500 mm per minute is recommended.
M. Naghipour Zade Mahani; M. H. Aghkhani
Abstract
Introduction: Carrot is one of the most common vegetables used for human nutrition because of its high vitamin and fiber contents. Drying improves the product shelf life without addition of any chemical preservative and reduces both the size of package and the transport cost. Drying also aidsto reduce ...
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Introduction: Carrot is one of the most common vegetables used for human nutrition because of its high vitamin and fiber contents. Drying improves the product shelf life without addition of any chemical preservative and reduces both the size of package and the transport cost. Drying also aidsto reduce postharvest losses of fruits and vegetables especially, which can be as high as 70%. Dried carrots are used in dehydrated soups and in the form of powder in pastries and sauces. The main aim of drying agricultural products is decrease the moisture content to a level which allows safe storage over an extended period. Many fruits and vegetables can be sliced before drying.because of different tissue of a fruit or vegetable, cutting them in different direction and shape created different tissue slices. Due to drying is the exiting process of the moisture from internal tissue so different tissue slices caused different drying kinetics. Therefore, the study on effect of cutting parameters on drying is necessary.
Materials and Methods: Carrots (Daucus carota L.) were purchased from the local market (Kerman, Iran) and stored in a refrigerator at 5°C. The initial moisture contents of the Carrot samples were determined by the oven drying method. The sample was dried in an oven at 105±2°C about 24 hours. The carrots cut by 3 models blade at 3 directions. The samples were dried in an oven at 70°C. Moisture content of the carrot slices were determined by weighting of samples during drying. Volume changes because of sample shrinkage were measured by a water displacement method. Rehydration experiment was performed by immersing a weighted amount of dried samples into hot water 50 °C for 30 min.
In this study the effect of some cutting parameters was considered on carrot drying and the quality of final drying product. The tests were performed as a completely random design. The effects of carrot thickness at two levels (3 and 6 mm), blade in 3 models (flat blade, wavy blade and Ridged blade) and the cutting direction at 3 levels (linear, lateral and diagonal) were evaluated on drying kinetics, drying rate, shrinkage and rehydration. Statistic analysis done by SPSS software.
Results and Discussion: The results of analysis of variance showed that the effects of cutting parameters were significant on studied parameters (p<0.01) (Table 1). Thin layers dried faster than thick layers because of firmness of surface which it causes slow moisture transfer. The least drying time was 200 minutes at the samples that cut by a wavy blade at the lateral direction with a significant difference (p<0.05) given Fig.3. In these samples surface evaporation is more, because of more surface. The compare means showed drying rate at thick layer is fewer because of the longer distance moisture removal (Fig.6). Also the most drying rate was 0.74 gmin-1 at cutting by flat blade on linear direction with a significant difference (p<0.05).The least shrinkage was obtained on this treatment was 36.7% given Fig.8. The most of tissue of linear slices is woody part that is dense compare with other parts therefore shrinkage decrease at during drying. The most rehydration was 3.96 and 3.88 for cutting by flat blade in diagonal and linear direction with significant difference to other treatments. Rehydration depends on cell damage greatly. Since the slices of carrot that cut by flat blade were damaged fewer than other treatments therefore rehydration was more.
Conclusions: The drying behavior of carrot slices was studied at different methods in slicing carrot. The results showed a significant effect of the cutting variables on drying kinetics, drying rate, shrinkage and rehydration. The carrot moisture content decreases continuously over the drying and the fastest drying occurred at thin layers sliced by wavy blade. The slices that were cut by flat blade at linear direction caused the best quality. The results show cutting parameters are significant effect on quality of dried fruits and vegetable. There for the study of drying behavior is necessary for fruits with different tissue because of more quality of production and high efficiency at drying. Also the study of cutting parameter suggest on other fruits and vegetables with different tissue. The results help to manufactures for improvement of production of drying equipment.
Design and Construction
A. Damirchi; M. H. Aghkhani; M. Khojastehpour; J. Baradaran Motie
Abstract
Introduction: In conventional farming, the soil and crop are considered uniform in different locations of the farm and the fertilizers are applied according to the average of soil needs with an additional percentage for safety (Loghavi, 2003). Non-essential chemical fertilizers in the field have harmful ...
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Introduction: In conventional farming, the soil and crop are considered uniform in different locations of the farm and the fertilizers are applied according to the average of soil needs with an additional percentage for safety (Loghavi, 2003). Non-essential chemical fertilizers in the field have harmful effects and social, economic and environmental concerns will increase. Many fertilizers go into the surface waters and ground waters and cause poisoning and environmental pollution without being absorbed by the plants. In variable rate technology, the soil fertilizer needs a map of all parts of the farm which is prepared with the GIS system. This map is uploaded on the computer before variable rate fertilizer machine starts. The computer continually controls the fertilizing rate for each part of the farm using a fertilizing map and global positioning system. The purpose of this study is to construct and evaluate a map-based variable rate fertilizer system that can be installed on a common fertilizer in Iran to be used as a variable rate system.Materials and methods: In common variable rate fertilizers, the rotational speed change of the distributor shaft is used to apply fertilizers. In this way, a DC motor is assembled on the main shaft of all distributors, which reduces the fertilizing accuracy. The reason for this is that there is no separation for units along the width of the fertilizer. Therefore, we used one DC motor for each distributor and another motor to rotate the agitator in the tank.System Set up: To design and select a suitable engine, the required torque for the rotation distributor shaft was measured by a torque meter and the amount of 2.1 Nm was acquired for that. With regard to the maximum rate of nitrogen fertilizer for land and tractor speed at the time of fertilizing, the order of 350 kg per hectare and 8 km per hour, the maximum distributor shaft speed and power required to rotate distributor shaft were calculated to be 55 rpm and 6.9 watts, respectively. The selected motor was rated 27.5 watts, 24 volts and 7.5 amperes (Since there were no 6.9 watts motors in the market, a more powerful motor was selected). According to the gear ratio and motor speed, the speed of the distributor shaft was adjustable in the range of 0 to 65 rpm. To determine the speed and position with respect to the direction, a central encoder (E50S8-600-6-L-5 model manufactured by Autonix Korea) was used on the ground wheel. The encoder had 600 pulses per revolution of the axis.Performance evaluation of the system: Performance evaluation of the system consists of two parts; static and moving tests. In static tests, the purpose was the determination of the fertilizer loss (in grams), due to changes in distributor speed as well as the accuracy of the electromechanical control system according to the command values sent to the device. Results of this part were used for the calibration of the device.In motion tests: In motion tests, the assessment of fertilizer loss was due to values set in a given situation and the accuracy of planted fertilizer in place (delay and acceleration) is reviewed. The delay is found by the determination of the distance that the fertilizer was placed after the desired location on the ground and the acceleration is found by the determination of the distance that the fertilizer is placed before the desired location on the ground.Results and discussion: The distributor flow rate on F0 valve position was measured for different rotation speeds. The correlation (linear regression) between the planted fertilizer and rotation speed of distributor shaft (rpm) were 0.99 for y=71.636x+75.182. So, it can be deduced that these two parameters have a good linear correlation. The results achieved from diagrams and regression model were used in the programming of the system control unit. Thus, by reading the distributors motor speed, the amount of fertilizer can be calculated and the amount of used fertilizer according to the need of the farm in each part is controlled. The effect of plot length on the amount of fertilizing on 25% need level was not significant, but it was significant on 50% need level. This is due to stopping and starting fertilizer flow during the test, changes in motors speed and error of these on fertilizer output at a certain amount of fertilizing so that at the 25% need level, the error resulting from these factors had less share on the amount of plant fertilizer and the effect of plot length was not significant according to the system default. On the other hand, the effect of forward speed was significant on the 50% need level and insignificant on the 25% need level.Conclusions: In order to calculate the accuracy of the system, the error from the application amount of fertilizer was measured at different fertilizing rates. The correlation between the adjusted fertilizing rate and the measured fertilizing rate was 0.98 with regression model of y=1.0475x which shows the good accuracy of the system.
A. Rohani; S. I. Saedi; H. Gerailue; M. H. Aghkhani
Abstract
Introduction: Fast and accurate determination of geometrical properties of agricultural products has many applications in agricultural operations like planting, cultivating, harvesting and post-harvesting. Calculations related to storing, shipping and storage-coating materials as well as peeling time ...
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Introduction: Fast and accurate determination of geometrical properties of agricultural products has many applications in agricultural operations like planting, cultivating, harvesting and post-harvesting. Calculations related to storing, shipping and storage-coating materials as well as peeling time and surface-microbial concentrations are some applications of estimating product volume and surface area. Sphericity is also a parameter by which the shape differences between fruits, vegetables, grains and seeds can be quantified. This parameter is important in grading systems and inspecting rolling capability of agricultural products. Bayram presented a new dimensional method and equation to calculate the sphericity of certain shapesand some granular food materials (Bayram, 2005). Kumar and Mathew proposed atheoretically soundmethod for estimating the surface area of ellipsoidal food materials (Kumar and Mathew, 2003). Clayton et al. used non-linear regression models for calculation of apple surface area using the fruit mass or volume (Clayton et al., 1995). Humeida and Hobani predicted surface area and volume of pomegranates based on the weight and geometrical diametermean (Humeida and Hobani, 1993). Wang and Nguang designeda low cost sensor system to automatically compute the volume and surface area of axi-symmetricagricultural products such as eggs, lemons, limes and tamarillos (Wang and Nguang, 2007). The main objective of this study was to investigate the potential of Artificial Neural Network (ANN) technique as an alternative method to predict the volume, surface area and sphericity of pomegranates.
Materials and methods: The water displacement method (WDM) was used for measuring the actual volume of pomegranates. Also, the sphericity and surface area are computed by using analytical methods. In this study, the neural MLP models were designed based upon the three nominal diameters of pomegranatesas variable inputs, while the output model consisted of each of the three parameters including the volume, sphericity and surface area. Priorto any ANN training process, the data normalized over the range of [0, 1]. Fig. 1 shows a MLP with one hidden layer. In this study, back-propagation with declininglearning-rate factor (BDLRF) training algorithm was employed. The mean absolute percentage error (MAPE) and the coefficient of determinationof the linear regression line between the predicted values fromthe MLP model and the actual output were used to evaluate the performance of the model.
Results and Discussion: The number of neurons in the hidden layerand also theoptimal values for the learning parameters η and αwere selected bytrial and error method. The bestresult was achieved with five neurons in the hidden layer. The results showed thatthe optimum modelof performance was obtained at constant momentum termequal to 0.8 and learning rate equal to 0.9. In this study, 300 epochs were selected as the starting points of the BDLRF. Some statistical characteristics of the actual values of volume were estimated by WDM, surface area was computed by equation (3) and sphericity of pomegranates was computed by equation (1) and the predicted values of them using the neural network method were shown in Table 1. The obtained results verified that the differences between theactual values and the estimated ones can be ignored. But, the predicted values of the volume using the MLP model in comparison with equation (2) are much closer to the actual values. Statistical comparisons of desired and predicted data and the corresponding p values are given in Table 2. The results showed that P-value was greater than 0.08 in all cases. Therefore, there was no significant difference between the statistical parameters. However, the P-value for equation 2 is much less than that of the MLP model. The results shown in Figures 2, 3 and 4 show that the coefficients of determination between actual and predicted data were greater than 0.9. Considering all the results in our study, the MLP model is more accurate than the WDM and analytical methods.
Conclusions: In this paper, we first measure the actual volume of the pomegranate using WDM and equation (2). Also, assuming an elliptical fruit, the sphericity and surface area are computed analytically based on the three nominal diameters of a pomegranate. Finally, the results of achievements of the MLP designed revealed that the MLP model could be successfully applied to the prediction of thesphericity and surface area. Therefore, the MLP model can be a viable alternative to the analytical methods. However, this is possible only if there is a precise way to compute the three nominal diameters of pomegranates. In addition, according to the MAPE, the accuracy of the MLP model in prediction of volume of pomegranates was twicethe analytical method.
A. Moghimi; M. H. Aghkhani; M. R. Golzarian
Abstract
In recent years, automation in agricultural field has attracted more attention of researchers and greenhouse producers. The main reasons are to reduce the cost including labor cost and to reduce the hard working conditions in greenhouse. In present research, a vision system of harvesting robot was developed ...
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In recent years, automation in agricultural field has attracted more attention of researchers and greenhouse producers. The main reasons are to reduce the cost including labor cost and to reduce the hard working conditions in greenhouse. In present research, a vision system of harvesting robot was developed for recognition of green sweet pepper on plant under natural light. The major challenge of this study was noticeable color similarity between sweet pepper and plant leaves. To overcome this challenge, a new texture index based on edge density approximation (EDA) has been defined and utilized in combination with color indices such as Hue, Saturation and excessive green index (EGI). Fifty images were captured from fifty sweet pepper plants to evaluate the algorithm. The algorithm could recognize 92 out of 107 (i. e., the detection accuracy of 86%) sweet peppers located within the workspace of robot. The error of system in recognition of background, mostly leaves, as a green sweet pepper, decreased 92.98% by using the new defined texture index in comparison with color analysis. This showed the importance of integration of texture with color features when used for recognizing sweet peppers. The main reasons of errors, besides color similarity, were waxy and rough surface of sweet pepper that cause higher reflectance and non-uniform lighting on surface, respectively.
M. Mazidi; M. H. Abbaspour-Fard; M. H. Aghkhani
Abstract
Automation of tractors due to their widespread use in different sectors e.g. agriculture, construction and industry have been seriously considered by researchers. In this study a tele-steering system for tractor was designed and constructed to controling and steering so the operator can control the tractor ...
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Automation of tractors due to their widespread use in different sectors e.g. agriculture, construction and industry have been seriously considered by researchers. In this study a tele-steering system for tractor was designed and constructed to controling and steering so the operator can control the tractor even far away from the stressful condition of tractor cab, . A CCTV camera and an electric motor were used in order to view the path and to rotate the steering shaft accordingly. Bilateral communication between the control center outside the tractor and control unit on the tractor was provided by a Wireless Local Area Network (WLAN). To evaluate the effect of relevant parameters on system performance camera position, steering shaft rotational speed and tractor ground speed were selected as experimental factors in a completely randomized design. Root mean square of error (RMSE) of lateral deviations and frequency of out of range around the reference route (Nout) were used as criteria in variance analysis. The results for two different ground surfaces with three replications showed that the performance of system had less sensitivity on soil surface and had better stability because of deformable structure and condition of soil compare to asphalt. Steering speed alone had no effect on the accuracy of tractor guidance. This is because the accuracy of the system mainly depends on capability, skillfulness and mental concentration of the operator. The position of the camera installed in front of the tractor had higher accuracy than that of rear camera. Moreover, by increasing ground speed the RMSE of lateral deviations and Nout increased and this is in agreement with the results of previous research works.
F. Alipour; M. H. Aghkhani; M. H. Abbaspour-Fard; A. Sepehr
Abstract
Application of satellite imagery and remote sensing techniques in agriculture and other natural resources has been approved by many studies. In this study two ETM+ imagery data for May and September 2012 of Astan Ghods Razavi Great Farm were acquired to identify the boundaries of lands cultivated with ...
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Application of satellite imagery and remote sensing techniques in agriculture and other natural resources has been approved by many studies. In this study two ETM+ imagery data for May and September 2012 of Astan Ghods Razavi Great Farm were acquired to identify the boundaries of lands cultivated with different crops coverage and to create crops maps of that farm. . To classify the images, the supervised classification methods including Maximum Likelihood and artificial neural network were used. In order to compare the results of two applied classification methods, the same training and testing samples were used. To evaluate the accuracy of classification results, the produced map was compared with the ground control points extracted by GPS and local observations. Kappa coefficient and overall accuracy were estimated to be 82% and 85%, respectively by maximum likelihood method and these outputs were estimated to be 84% and 87%, respectively by neural network approach. The difference of cultivated area estimated by maximum likelihood and by neural network methods with actual measured area was 16.8% and 14.2%, respectively. The results of this study showed that satellite imagery has high capabilities to classify and estimate agricultural and cultivated areas. These data can be useful for strategic management to develop mechanization and cultivation plans.
M. Ghasemi; M. Khojastehpour; M. H. Aghkhani
Abstract
Evaluation of mechanical and electrical properties of agricultural products plays an important role in equipment design and optimizing post-harvest operations. Among the crops, tomato and its products are the major processing industries in the world and its economic importance is increasing. Considering ...
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Evaluation of mechanical and electrical properties of agricultural products plays an important role in equipment design and optimizing post-harvest operations. Among the crops, tomato and its products are the major processing industries in the world and its economic importance is increasing. Considering the importance of the quality and various post harvesting uses of tomato, the evaluation of mechanical properties including rupture force and deformation and the work done to establish the rupture of two tomato cultivars (Petoearly CH and Newton) were studied under penetration test based on the electrical conductivity. These properties were measured at three levels of 1, 3 and 5 days after harvesting. The evaluated mechanical properties of both cultivars were decreased by increasing the storage time. Interaction of cultivar and time were significant at the 1% level, for all mechanical parameters except the deformation failure in both cultivars. The electrical conductivity of both cultivars was decreased by increasing the storage time. Interaction of cultivar and time on the electrical conductivity of both cultivars were significant at the 1% level. Significant relationships were found at the 1% level between electrical conductivity and mechanical properties except for deformation of Petoearly CH cultivar. Among the mechanical parameters, rupture forces and rupture works of both cultivars were highly correlated with the electrical conductivity.
A. R. Salari Kia; M. H. Aghkhani; M. H. Abbaspour-Fard
Abstract
Pistachio has a special ranking among Iranian agricultural products. Iran is known as the largest producer and exporter of pistachio in the world. Agricultural products are imposed under different thermal treatments during storage and processing. Designing all these processes requires thermal parameters ...
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Pistachio has a special ranking among Iranian agricultural products. Iran is known as the largest producer and exporter of pistachio in the world. Agricultural products are imposed under different thermal treatments during storage and processing. Designing all these processes requires thermal parameters of the products such as specific heat capacity. Regarding the importance of pistachio processing as an exportable product, in this study the specific heat capacity of nut and kernel of two varieties of Iranian pistachio (Kalle-Ghochi and Badami) were investigated at four levels of moisture content (initial moisture content (5%), 15%, 25% and 40% w.b.) and three levels of temperature (40, 50 and 60°C). In both varieties, the differences between the data were significant at the 1% of probability; however, the effect of moisture content was greater than that of temperature. The results indicated that the specific heat capacity of both nuts and kernels increase logarithmically with increase of moisture content and also increase linearly with increase of temperature. This parameter has altered for nut and kernel of Kalle-Ghochi and Badami varieties within the range of 1.039-2.936 kJ kg-1 K-1, 1.236-3.320 kJ kg-1 K-1, 0.887-2.773 kJ kg-1 K-1 and 0.811-2.914 kJ kg-1 K-1, respectively. Moreover, for any given level of temperature, the specific heat capacity of kernels was higher than that of nuts. Finally, regression models with high R2 values were developed to predict the specific heat capacity of pistachio varieties as a function of moisture content and temperature
Design and Construction
A. Zeinali; A. Farzad; M. H. Aghkhani
Abstract
Torque, speed, and power as mechanical variables are associated with the functional performance of any rotating machinery. The real-time performance and the efficiency of a machine can be determined with on-line measurement of these parameters. In this investigation a rotary torque meter (transducer) ...
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Torque, speed, and power as mechanical variables are associated with the functional performance of any rotating machinery. The real-time performance and the efficiency of a machine can be determined with on-line measurement of these parameters. In this investigation a rotary torque meter (transducer) was constructed from strain gauge sensors for measuring the torque of rotating shafts. The system converts the torque of rotating shaft into voltage signals, based on the principle of strain gauge resistance. The signals are then amplified and converted into digital signals. These digital signals are sent to a RF receiver circuit for displaying and storage. Results of static calibration and a series of dynamic tests confirmed a satisfactory operation of the designed apparatus in various conditions. Also, the torque measuring range, resolution and the accuracy were from 3 to 700 N m, 3 N m and 1%, respectively.
M. H. Aghkhani; M. H. Abbaspour-Fard; M. R. Bayati; H. Mortezapour; S. I. Saedi; A. Moghimi
Abstract
Drying is a high energy consuming process. Solar drying is one of the most popular methods for dehydration of agricultural products. In the present study, the performance of a forced convection solar dryer equipped with recycling air system and desiccant chamber was investigated. The solar dryer is comprised ...
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Drying is a high energy consuming process. Solar drying is one of the most popular methods for dehydration of agricultural products. In the present study, the performance of a forced convection solar dryer equipped with recycling air system and desiccant chamber was investigated. The solar dryer is comprised of solar collector, drying chamber, silica jell desiccant chamber, air ducts, fan and measuring and controlling system. Drying rate and energy consumption in three levels of air temperature (40, 45 and 50 oC) and two modes of drying (with recycling air and no-recycling with open duct system) were measured and compared. The results showed that increasing the drying air temperature decreased the drying time and increased the energy consumption in the mode of non-recycling air system. The dryer efficiency and drying rate were better in the mode of recycling air system than open duct system. The highest dryer efficiency was obtained from drying air temperature of 50 oC and the mode of recycling air system. In general, the efficiency of solar collector and the highest efficiency of the dryer were 0.34 and 0.41, respectively.
M. Jafarian; H. Sadrnia; M. H. Aghkhani
Abstract
Today, the use of coatings is common to maintain the quality of fruits in storage period. Previous studies have shown that the calcium compounds can improve and preserve the strength of fruit’s cell wall. In this research, the effect of calcium chloride dehydrate (CaCl2*2H2O) concentration on two ...
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Today, the use of coatings is common to maintain the quality of fruits in storage period. Previous studies have shown that the calcium compounds can improve and preserve the strength of fruit’s cell wall. In this research, the effect of calcium chloride dehydrate (CaCl2*2H2O) concentration on two varieties of apple (Golden Delicious and Red Delicious), was studied. The apples were immersed in the calcium chloride dihydrate solution and then transferred to a cold storage. The effect of three concentration levels: 0, 3 and 6 percent, and three storage durations: no storage, one month and two months, were investigated on the apples mechanical properties such as failure stress, failure strain, modulus of elasticity and toughness. Statistical factorial experiments in the form of completely randomized design were used to analyze the obtained results. The ANOVA results showed that the effect of calcium chloride concentration was significant on the modulus of elasticity (P
S. I. Saedi; M. H. Aghkhani; A. Farzad
Abstract
Disk plows are one of the most important tillage tools. Two way (reversible) disk plows can perform continues plowing. So they can save time and costs and hence improve overall efficiency. In this study, a “two-way” disk plow was designed based on a λ-formed straight-line, four-bar ...
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Disk plows are one of the most important tillage tools. Two way (reversible) disk plows can perform continues plowing. So they can save time and costs and hence improve overall efficiency. In this study, a “two-way” disk plow was designed based on a λ-formed straight-line, four-bar linkage (Daniel mechanism). This design contains disk and rear wheel reversing mechanism, stabilization mechanism of the plow, a disk angle adjustment tool and transport condition for safe operation of the mechanism. Disk reversing mechanism was designed based on a geometrical analysis considering working condition of the disk plow. The suitable displacement of the plow’s frame was achieved by dimensional analysis of Daniel mechanism and a derived mathematical equation. The rear wheel mechanism was made by means of adding a slotted link to the previous four-bar linkage. The synthesized five-bar linkage was then analyzed for its kinematical and force conditions. For each analysis, related diagrams were plotted and discussed. This innovation has the advantages of low production cost and maintenance as well as easy operation, because of its design simplicity with minimum mechanical auxiliaries. The modeling and analysis was done by the aid of CATIA software.
Design and Construction
M. Khosravi; M. H. Abbaspour-Fard; M. H. Aghkhani
Abstract
The majority of existing tractors in Iran are not equipped with any tools to measure and display slip and ground speed. This is mainly due to the lack of national standards for measuring tools and instruments of tractors. In current research, an interchangeable system for two wheel drive tractors has ...
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The majority of existing tractors in Iran are not equipped with any tools to measure and display slip and ground speed. This is mainly due to the lack of national standards for measuring tools and instruments of tractors. In current research, an interchangeable system for two wheel drive tractors has been designed. Furthermore, it has been assessed after construction. To measure actual and theoretical ground speed, four rotary encoders for sensing the rotation of front and rear wheels have been utilized. Slip and ground speed were measured by means of software which has been developed in an ATmega16PU microprocessor. The measured slip and speed are digitally displayed on tractor dashboard. To evaluate the performance of the system, the measured values of ground speed and slip were compared with their calculated values obtained from conventional method. The Micro-controller has been programmed in such a way that the effect of front wheel sliding on slip is eliminated. In all evaluation conditions (in field and on asphalt), the maximum difference between system measurements for slip and speed and calculated slip and speed via conventional method was 2.4% and 0.2 km h-1, respectively. With slight alteration this system can be fitted on any kind of exiting two wheel drive tractors in the country.
Design and Construction
J. Baradaran Motie; M. H. Aghkhani; M. H. Abbaspour-Fard; A. Lakziyan
Abstract
The issue of soil salinity is one of the snags for increasing agricultural productivity, which must be inhibited by appropriate devise and scientific management. One way to identify salty areas of farm lands is to prepare salinity maps. In this study, a prototype soil apparent electrical conductivity ...
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The issue of soil salinity is one of the snags for increasing agricultural productivity, which must be inhibited by appropriate devise and scientific management. One way to identify salty areas of farm lands is to prepare salinity maps. In this study, a prototype soil apparent electrical conductivity measuring and mapping device, was designed and built. This device employs direct contact method of electrodes with soil (Also called Wenner method). The system inputs include power supply voltage, location signal from a GPS receiver and signal of voltage between the electrodes. The outputs include the apparent electrical conductivity with respective to geographical coordinate that created in a TEXT file, and then transmitted through a RS-232 serial port to a PC. Electrical conductivity data calibrated and mapped using ESAP-95 software package. To evaluate the device, electrical conductivity map of a land with area of 0.8 Ha surveyed in two ways: using the on the go EC mapper and capturing soil samples manually. The results of these two methods were then compared. Assessment of the device in a clay-loamy soil with low salt level, showed a good correlation with the laboratory EC, having mean error (ME) of -15.27μS.cm-1. Point to point comparison between surveyed data and laboratory EC’s shown that in 67 percent of measurements the errors were under 10 percent. These errors are acceptable mainly due to unknown soil variables and in comparison with other research findings.
