Journal of Researches in Mechanics of Agricultural Machinery

Abstract Dust is one of the environmental issues that have adverse effects in all sectors of agriculture and natural resources. The aim of this research is to predict the concentration of dust in the air. A laboratory system for acquiring images of dust was implemented including a glass chamber, a blower, a dust meter, an imaging camera, and a personal computer. Using clay soil, dust storms with different concentrations of 0, 275, 1289, 1896, 2316, 2585 and 2750 µm/m3 were created inside the glass chamber. For each studied dust concentration, 15 images were obtained and after their preprocessing, mean value of different image channels in various color spaces were extracted. The features of the images were used to predict dust concentration using artificial intelligence technology. The data were divided into three groups, 60% of the data were used for training, 20% for validation, and 20% for testing the network. Different models of multilayer perceptron artificial neural networks were investigated and 10-11-1 structure with tansig activation function in hidden and output layers has the highest accuracy (93.55 %). The findings of the present research show the high capability of image processing and artificial intelligence technologies in predicting dust concentration with high accuracy and low cost.

Abstract In this research, wheat, rice, and corn residue were used as a substrate for biogas production. Due to the high amount of lignin in all three substrates (> 9.9) and in order to increase the degradability of these substrates, an ultrasonic pretreatment with a power of 150 w at 15 min was used prior to initiating enzymatic digestion process. Some physical and chemical properties including solid and volatile particles and contents of lignin, cellulose and hemicellulose were measured before and after digesting the substances; and in addition, the biogas compounds including hydrogen, methane, hydrogen sulfide and carbon monoxide was measured during digestion. The metabolic pathways of converting glucose as the main constituent of all three waste types into biogas were studied to determine the factors affecting biogas compounds. The results showed that use of ultrasonic pretreatment in all three wastes increased the breakdown of lignin structures, which decreased the content of these structures in the feedstock compared to the substrate. The amount of solid and volatile particles of the feedstock obtained from the substrate of wheat residue was 35.1% and 95.3%, respectively, which was more than that of the other substrates. The highest amounts of reduction of solid particles (19.6%), volatile particles (18%), cellulose (12.6%), hemicellulose (4.4%) and lignin (3.6%) were related to the feedstock obtained from wheat residue. Analyses of biogas compounds showed that the highest biohydrogen production obtained for wheat substrate (ppm 18000), but its biomethane production was lower than the other substrates. The highest amounts of biohydrogen production of all the substrates occurred after seven days, which was related to the butyrate acidification stage. With increasing digestion time, hydrogen production decreased while the other biogas compounds increased. One of the probable reasons was the consumption of hydrogen produced in the stages of hydrolysis, acidification and acetate formation in the stages of alcoholization and methanation. The highest amount of hydrogen production was related to the stage of butyrate formation and then acetate formation. The higher production of biohydrogen by wheat residue is most likely due to its high volume of volatile, hydrocarbon and hemicellulose compounds. While the low production of hydrogen by corn residue was due to driving the reactions towards the production of ethanol and consuming hydrogen.

Abstract The research projects conducted in the field of biogas shows that the type of reactor and the composition of different animal wastes have a direct effect on the amount of biogas extraction. Therefore, the main goal of this research is to design and build a multi-bed reactor with a new capability and investigate the effect of the combination of livestock and poultry waste on the gas production process. For this purpose, a multi-bed cylindrical reactor equipped with a separate stirrer for each bed was designed and built, and the effect of different combinations of livestock and poultry wastes in three levels including 60% by weight of chicken waste and 40% by weight of cow waste, 50% by weight of chicken waste and 50% by weight of cow waste, and finally 40% by weight of chicken waste and 60% by weight of cow waste. , the compound concentration at two levels of TS=10% and TS=15% and the reactor temperature at two levels of 37 and 40 degrees Celsius were examined on the pH and percentage of extracted biogas. The results showed that the use of a bed stirrer in this type of reactor increased the volume of produced gas by 17%. Increasing the ratio of animal waste to poultry, balanced the acidity of the environment and finally increased the percentage of extracted biogas. Diluting the composition from TS=15% to TS=10% led to an increase in the pH level and approaching the neutral environment. Also, reducing the temperature of the reactor from 40°C to 37°C increased the percentage of extracted biogas by 8%.

Abstract Nettle is one of the most important and abundant medicinal plants that is available seasonally. Increasing the shelf life, along with achieving the quality characteristics expected by the consumer markets, is one of the most important goals of the drying process and is one of the influencing factors on the process time as well as the quality characteristics. The purpose of this research is to find a suitable mathematical model to describe the experimental drying process, to evaluate the diffusion coefficient, to obtain the activation energy to determine the thermodynamic properties during the nettle drying process. Nettle leaves with initial moisture content (2.15 ± 0.05 kg of water/kg of dry matter) in an infrared dryer at three temperatures of 40, 45 and 50 degrees Celsius and with two times of ultrasonic pretreatment for They were dried for 5 and 10 minutes until reaching a constant weight. The best model to describe the nettle drying process was chosen by Midilli et al. The moisture diffusivity coefficient of nettle increased with increasing drying temperature and duration of ultrasound treatment. The activation energy during drying of nettle was 11.45 - 40.54 kJ.mol-1. Enthalpy and entropy decreased with increasing drying temperature and duration of ultrasound pretreatment, while Gibbs free energy increased. Enthalpy value changed between 37.8-76.94 kJ.mol-1, entropy value between -178.00 and -73.18 kJ.mol-1 and Gibbs free energy value between 60.85-66.28 kJ.mol-1.

Abstract In recent decades, human activities have introduced various pollutants into the environment at significant levels. Among these pollutants, oil pollution poses considerable threats to both human health and the environment. Therefore, the detection and remediation of oil pollution have become critical tasks. Numerous methods for detecting oil pollution in soil have emerged, including gas chromatography, mass spectrometry, and electronic nose technology.
In this study, we utilized an electronic nose system equipped with eight metal oxide semiconductor sensors from the MQ and TGS sensor series to detect and assess soil samples contaminated with crude oil. The soil samples were obtained from the agricultural fields at the University of Tehran's Faculty of Agriculture and Natural Resources. The samples were deliberately contaminated with crude oil at four concentrations: 200 ppm, 500 ppm, 1000 ppm, and 5000 ppm. Notably, the 1000 ppm concentration represents the permissible limit, while the 5000 ppm concentration leads to soil destruction. We collected two samples from each concentration, totaling eight samples, which were stored and tested over a 14-day. The sensor responses were transformed into voltage signals and normalized using the differential method. The pattern recognition methods yielded results of 92% accuracy for Principal Component Analysis, 100% for Linear Discriminant Analysis, and 100% for the Support Vector Machine method. Additionally, we compared the electronic nose system's results with those of the gas chromatography system, demonstrating the efficiency and speed of our method in classifying and distinguishing different concentrations of oil pollution. Also, in this research, a method was used, with the help of which the sensors can be examined separately and the accuracy of each can be obtained using machine learning algorithms. The factorial experiment was conducted with two main factors, day and time, and for analysis, 80% of the data were selected for training and 20% for testing, and decision tree regression, support vector regression, enhanced gradient regression, and random forest regression algorithms were used. After obtaining the results, it was found that the MQ3 sensor has the highest accuracy and the lowest error rate, With the best performance with an average of 95.5%, they show the detection rate of pollution levels. Therefore, the selected sensors from the results obtained from the gas chromatography system research on soil contaminated with crude oil have had an acceptable sensitivity, and in general, the electronic nose system can be replaced by other methods as a cheaper and easier method.

Abstract In this research, field experiments were carried out in two types of soil (sandy clay loam and clay) to model the traction performance of the tractor considering drawbar power, rolling resistance, and traction efficiency, using deep learning and convolutional neural network while having some parameters such as soil type and conditions, tool parameters, and operation parameters. The tests were conducted within each soil texture in the form of factorial tests based on the randomized complete block design (RCBD) in triplicates. The tests were done in various moisture levels (8-17% for dry soils and 18-40% for moist soils), tractor forward speed (1.2, 1.6, 1.8, and 2.2 km h-1), working depth (30 and 50 cm), the number of pass (2 and 6 times), and tire inflation pressure (20 and 25 psi). The cone index, dynamic load, draft force, and moisture content were measured in each tests. The networks designed to model the drawbar power, rolling resistance, and traction efficiency were of convolutional neural network type. Various algorithms such as Sgdm, Adam, and Rmsprop were utilized to train the network. The results showed that the neural network developed by Sgdm algorithm outperformed the others. Therefore, this algorithm was utilized for the modeling process. Statistical criteria such as R2 and MSE were also employed to evaluate the performance of the network. For the drawbar power, the 8-499-499-1 architecture showed the best performance with R2=0.9953 and MSE=0.0016. Concerning the rolling resistance, the best performance was observed in 8-301-305-1 architecture with R2=0.9903 and MSE=0.0039. The best performance for the traction efficiency was obtained by 8-371-371-1 architecture with R2=0.9888 and MSE=0.003. The results showed that these networks can be used to model parameters by removing convolution layers and reducing dimensions.

Abstract In this research, first, a moldboard plow was attached to the tractor and the coordinates of the path of lower and upper hitch points were measured in the movement range of the lift arms. Then, with the aim of investigating the effect of the geometric parameters of 3-point hitch system on its performance, SolidWorks software was used to simulate the motion of the 3-point hitch system. By using the measured data, path of the hitch points was plotted and geometric performance parameters were calculated.
The workshop results showed that when the upper link was attached to the lower pivot point, the vertical convergence distance was less than the ASAE standard value. Therefore, when using tillage implements, it is better that the upper link to be attached to 2rd or 3rd pivot point, and if the lower pivot point is used, the stability of the tractor may be disturbed. The simulation results showed that by increasing the distance of the connection point of the lift rod to the lower link, the mechanical advantage increased to 3.18, but the movement range of the arms decreased by 95.28 mm. Also, by reducing the length of the lift rod, the mechanical advantage increased to 3.16, while the movement range of the arms decreased by 487.11 mm.
By reducing the distance of the connection point of the lift rod to the lower link, as well as increasing the length of the lift rod at heights lower than the ASAE standard for lower links, the position of the virtual hitch point was moved to the rear of the rear wheels of the tractor. This may affect the stability of the tractor, especially on hills.

Abstract Tragacanth gum is considered as one of the valuable export products of natural resources of Iran and Isfahan province. This product is used in the food and cosmetic industries as a stabilizing agent, viscosity increaser in food, pharmaceutical and cosmetic emulsions and formulas. In this research, the effect of grinding method, type of Tragacanth and the final size of crushed particles on the quality indicators of Tragacanth were evaluated. For this purpose, using a factorial experiment in the form of a completely random design, the effect of the grinding method in two levels, one-stage and two-stage, the type of Tragacanth in two levels of Ribbon and Flake and the final size of the particles of Tragacanth milled in three levels, 2, o.5 and 0.25 mm in three repetitions on gel color and viscosity indices were investigated as two very important factors in determining the quality of Tragacanth gum. The results showed that the effect of all three factors (type of Tragacanth, grinding steps and particle size) on viscosity values of Tragacanth gel and color parameters (R, G and B) were significant at 1% probability level. Viscosity of Ribbon between 2140-3040 centipoise and Flake between 390-610 centipoise was obtained, which shows the higher quality and more economic value of Ribbon type. In both types of Tragacanth, with the reduction of particle size, a higher viscosity reduction was observed, especially in the one-stage grinding method, so that in one-stage grinding, the viscosity of Tragacanth was 9.3% less than in two-stage grinding. The examination of the color indices of Tragacanth showed that based on the Euclidean distance (ΔE) obtained, the color difference of Ribbon and Flake type Tragacanth in terms of brightness is 11.67 units and the color difference between one and two stages of grinding is 8.85 units. This shows that with two-stage grinding, the brightness of the color decreases compared to one-stage grinding.

Abstract Mechanizing and improving agricultural operations have always been an interest to experts due to the diverse and growing human needs. One of the processes in agricultural products is post-harvest operations. Transferring straw with a mechanized method uses a straw collector. During this process, there is a possibility of mixing gravel and other particles on the ground with the straw. These particles ultimately reduce the quality of the harvested straw. In this study, a laboratory cyclone was constructed and evaluated to handle these challenges. The results of this study were conducted using a factorial experiment in a completely randomized design, with four gravel-to-straw ratios (3.5%, 5%, 10%, and 15%). The experiments were performed at three levels of cyclone inlet opening (1, 0.6, and 0.3), two heights of the vortex finder (0 and 15 cm), and two suction impeller (2574 and 2860 rpm). By performing three repetitions for each of the experiments, a total of 144 data were obtained. The cyclone performance was determined by calculating two separation efficiency factors, the percentage of the separated gravels, and the percentage of straw separated from the mixture. The analysis of variance (ANOVA) and comparison of the means was performed using the Duncan post-test at a 5% probability level using SPSS software version 26. The results showed that the most effective factor in the separation efficiency of gravel and straw was the cyclone inlet opening level. Additionally, the highest separation efficiency occurred at a suction impeller frequency of 50 Hz and a vortex finder position of zero. Also, the cyclone performance was maximum for gravel and straw ratios of 3.5% and 5% respectively.

Abstract Tea, this popular drink is produced in several ways, one of the methods used in Iran for tea processing is the orthodox method. In this method, the tea is first added and then rubbed, and after passing through the fermentation period, it enters the dryer. In order to check the quality of tea in the rubbing section, this research has evaluated the two parameters of the speed and the distance of the cylinder from the bottom of the machine. To investigate the effect of the speed and distance of the cylinder on the quality of the final tea, first, using Solidwork software, a device similar to rubbing tea in the orthodox way with a capacity of 10 kg was designed and built. After weighing, the samples were divided into 10 kg parts and rubbed 27 times with speeds of 20, 30 and 40 rpm and distances of 2, 3 and 4 cm and with a 10 kg household tea rubbing machine. The rubbed samples were examined in terms of failure percentage and rubbing time. According to the analysis of the results and the analysis of the average comparison tables, it was observed that there is a significant difference between the values of percentage of failure and time in the constant cycle, among all the distance levels, and the lower the distance of the cylinder from the bottom of the machine, the higher the percentage of failure and the rubbing time. It will be shorter. At a fixed distance between some levels of rotation speed, there is no significant difference between the time values, which varies according to the distance, but the failure percentage values at a fixed distance are significantly different from each other, and the higher the rotation speed, the higher the percentage of failure. . Due to the need for speed in carrying out the process while maintaining quality, the recommended speed and distance is 20 revolutions per minute (RPM) and the distance is 3 cm.