University of Tabriz Journal of Agricultural Mechanization 2383-126X 9 4 2024 12 21 Performance Evaluation of Semi-continuous Plug-flow Baffled Digester and Batch Digester for Biogas Production from Cattle Manure under the Influence of Different Fe3O4 Nanoparticle Concentrations Performance Evaluation of Semi-continuous Plug-flow Baffled Digester and Batch Digester for Biogas Production from Cattle Manure under the Influence of Different Fe3O4 Nanoparticle Concentrations 1 14 18869 10.22034/jam.2024.63590.1296 FA Alireza Kolouri Pirlou Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil, Iran Tarahom Mesri Gundoshmian Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil, Iran 0000-0002-7302-7269 Reza Tabatabaeikoloor Department of Farm Machinery, Sari University of Agricultural Sciences & Natural Resources, Iran Mansour Ahmadi Department of Farm Machinery, Sari University of Agricultural Sciences & Natural Resources, Iran Journal Article 2024 09 24 Introduction A stable and readily available energy supply is of paramount importance for economic development. This is evidenced by historical global competition for energy resources, which has been driven by their significance for national security and governmental stability. The current global energy consumption trend presents significant resource depletion and environmental degradation challenges. Two principal solutions are put forth: the enhancement of energy efficiency and the transition to renewable energy sources, with the latter being the optimal long-term strategy. Nanoparticles, due to their minute size, diverse shapes, high reactivity, and stability, have garnered considerable research interest. This study assesses the impact of Fe₃O₄ nanoparticles on the anaerobic digestion of cow manure in two types of digesters: discontinuous and semi-continuous. Materials and Methods This study utilized four transparent plastic batch-flow digesters, each with a volume of 4 liters, and four semi-continuous horizontal plug-flow digesters, constructed from a combination of PVC and plexiglass pipes. The length of the digesters was approximately 120 centimeters, divided into three sections by two baffles to create a three-stage digester system. The volume of each digester was approximately 12 liters, resulting in a volume of approximately 4 liters per section. Each section was furnished with a gas discharge valve and an inspection and sampling port. The four digesters were situated within an enclosure. The experiments were conducted at temperatures suitable for mesophilic organisms. A thermostat module and two 1000-watt heaters were employed to regulate the temperature. Two fans were positioned behind the heaters to facilitate air circulation. To prevent the accumulation of sediment, clogging, and the formation of foam on the surface of the substrate, and to ensure the uniform dispersion of nanoparticles within the substrate, agitators were installed within the digesters. The experiments were conducted using iron oxide nanoparticles with a diameter of 50-100 nanometers, manufactured by Sigma-Aldrich. Three different concentrations of Fe3O4 nanoparticles were utilized: 50, 100, and 200 milligrams per liter, respectively, for the first, second, and third experiments. Results and Discussion During the initial four-day period, digesters one, two, and three generated greater quantities of biogas than the control in both batch and plug-flow systems, despite the overall low production levels observed initially. Digester 2 in the batch system demonstrated the highest biogas production, with a volume of approximately 37 liters over 39 days, representing a 41% increase compared to the control. In the plug-flow system, digesters 2 and 3 produced 165.68 and 149.45 liters of biogas, respectively, representing a 36% and 23% increase over the control. The biogas production of Digester 3 was comparable to that of the control. The decomposition of organic matter was found to be accelerated by lower concentrations of Fe₃O₄ nanoparticles, while higher concentrations were observed to inhibit anaerobic digestion. The highest methane production in the batch system was 11.94 liters in digester 2, representing a 51% increase over the control, while digesters 1 and 3 exhibited comparatively smaller increases. It is necessary to allow sufficient time for methanogenic microorganisms to adapt to additions of nanoparticles. In the plug-flow system, digester 2 produced a total of 50.3 liters of methane, representing a 48% increase over the control. This result demonstrates the effectiveness of a 100 mg/L dose. The findings indicate that there is no linear relationship between nanoparticle concentration and methane production. Instead, effective concentrations vary based on nanoparticle size and other factors. Conclusion The study revealed that the incorporation of nanoparticles into anaerobic digestion processes enhances biogas and methane production. However, the optimal concentration of nanoparticles varies depending on the specific conditions, feedstock type, and size of the system. The highest biogas and methane production was observed at 100 mg/L in a semi-continuous digester, with a 36% and 48% increase, respectively. The highest biogas and methane production was observed in tank number two (36%), followed by tank number three (34%), and the lowest in tank number one (29%). This indicates that biogas production necessitates an adequate period for microorganisms to effectively engage in methanogenesis. Introduction A stable and readily available energy supply is of paramount importance for economic development. This is evidenced by historical global competition for energy resources, which has been driven by their significance for national security and governmental stability. The current global energy consumption trend presents significant resource depletion and environmental degradation challenges. Two principal solutions are put forth: the enhancement of energy efficiency and the transition to renewable energy sources, with the latter being the optimal long-term strategy. Nanoparticles, due to their minute size, diverse shapes, high reactivity, and stability, have garnered considerable research interest. This study assesses the impact of Fe₃O₄ nanoparticles on the anaerobic digestion of cow manure in two types of digesters: discontinuous and semi-continuous. Materials and Methods This study utilized four transparent plastic batch-flow digesters, each with a volume of 4 liters, and four semi-continuous horizontal plug-flow digesters, constructed from a combination of PVC and plexiglass pipes. The length of the digesters was approximately 120 centimeters, divided into three sections by two baffles to create a three-stage digester system. The volume of each digester was approximately 12 liters, resulting in a volume of approximately 4 liters per section. Each section was furnished with a gas discharge valve and an inspection and sampling port. The four digesters were situated within an enclosure. The experiments were conducted at temperatures suitable for mesophilic organisms. A thermostat module and two 1000-watt heaters were employed to regulate the temperature. Two fans were positioned behind the heaters to facilitate air circulation. To prevent the accumulation of sediment, clogging, and the formation of foam on the surface of the substrate, and to ensure the uniform dispersion of nanoparticles within the substrate, agitators were installed within the digesters. The experiments were conducted using iron oxide nanoparticles with a diameter of 50-100 nanometers, manufactured by Sigma-Aldrich. Three different concentrations of Fe3O4 nanoparticles were utilized: 50, 100, and 200 milligrams per liter, respectively, for the first, second, and third experiments. Results and Discussion During the initial four-day period, digesters one, two, and three generated greater quantities of biogas than the control in both batch and plug-flow systems, despite the overall low production levels observed initially. Digester 2 in the batch system demonstrated the highest biogas production, with a volume of approximately 37 liters over 39 days, representing a 41% increase compared to the control. In the plug-flow system, digesters 2 and 3 produced 165.68 and 149.45 liters of biogas, respectively, representing a 36% and 23% increase over the control. The biogas production of Digester 3 was comparable to that of the control. The decomposition of organic matter was found to be accelerated by lower concentrations of Fe₃O₄ nanoparticles, while higher concentrations were observed to inhibit anaerobic digestion. The highest methane production in the batch system was 11.94 liters in digester 2, representing a 51% increase over the control, while digesters 1 and 3 exhibited comparatively smaller increases. It is necessary to allow sufficient time for methanogenic microorganisms to adapt to additions of nanoparticles. In the plug-flow system, digester 2 produced a total of 50.3 liters of methane, representing a 48% increase over the control. This result demonstrates the effectiveness of a 100 mg/L dose. The findings indicate that there is no linear relationship between nanoparticle concentration and methane production. Instead, effective concentrations vary based on nanoparticle size and other factors. Conclusion The study revealed that the incorporation of nanoparticles into anaerobic digestion processes enhances biogas and methane production. However, the optimal concentration of nanoparticles varies depending on the specific conditions, feedstock type, and size of the system. The highest biogas and methane production was observed at 100 mg/L in a semi-continuous digester, with a 36% and 48% increase, respectively. The highest biogas and methane production was observed in tank number two (36%), followed by tank number three (34%), and the lowest in tank number one (29%). This indicates that biogas production necessitates an adequate period for microorganisms to effectively engage in methanogenesis.

https://jam.tabrizu.ac.ir/article_18869_03ef366f1074fd0a6c2a0c3687632492.pdf

University of Tabriz Journal of Agricultural Mechanization 2383-126X 9 4 2024 12 21 Development of an Electronic System to Measure Cattle Rumination Development of an Electronic System to Measure Cattle Rumination 15 28 18888 10.22034/jam.2024.58598.1257 FA Mahsa Javani Helan Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Hossein Navid Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Hadi Karimi Agricultural Engineering Research Department, Kerman Agricultural and Natural Resources Research and Education Center, Areeo, Kerman, Iran Ali Hossein Khani Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Elnaz Vahedi Tekmehdash Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Journal Article 2023 09 26 Introduction Agriculture is a vital sector in Iran, with the livestock industry playing a significant role. Rumination is a key activity in livestock, and its condition can indicate overall health. Abnormal rumination patterns may signal health issues that can reduce productivity, making monitoring essential. Traditional visual observation is costly and often inaccurate; therefore, an electronic system was developed to monitor cattle rumination. Materials and Methods The system utilizes an accelerometer to detect muscle movement in animals. It comprises an Arduino Pro Mini board, ADXL345 accelerometer, LF33CV3 voltage regulator, Wi-Fi module, lithium battery, dual battery holder, and a smartphone. Acceleration data is captured along three directions (X, Y, Z) and transmitted to a smartphone via Wi-Fi. The necessary code was written in the Arduino programming environment. Outlier data were filtered using R software before transferring the remaining data to Excel for further analysis. Results and Discussion The system was tested in two configurations: as a necklace and on the snout of livestock. The snout configuration yielded optimal results with 88% sensitivity, 94% precision, and 94% F-score. Ensuring comfort for the livestock while using the monitoring system was crucial; thus, efforts were made to design lighter and smaller electronic components using SMD technology. Final evaluations showed sensitivity at 91%, accuracy at 82%, and F-score at 86%. Conclusion The ADXL345 accelerometer with ±8g sensitivity is ideal for measuring acceleration across X, Y, and Z directions due to its low data dispersion and high accuracy. Its affordability and compact size make it suitable for research applications comparable to a priority booklet. A waterproof bag installation proved effective as it maintains sensor position while protecting against environmental factors like rain or humidity. In this study, the optimal installation location was determined to be on the muzzle due to significant muscle activity during chewing. This positioning allows for accurate acceleration measurements across all three axes during rumination while maximizing accuracy, sensitivity, and F-score. The circuit was installed in SMD mode with minimal error at a compact size on the animal's muzzle, ensuring nearly zero disconnection risk and improved data collection performance. Introduction Agriculture is a vital sector in Iran, with the livestock industry playing a significant role. Rumination is a key activity in livestock, and its condition can indicate overall health. Abnormal rumination patterns may signal health issues that can reduce productivity, making monitoring essential. Traditional visual observation is costly and often inaccurate; therefore, an electronic system was developed to monitor cattle rumination. Materials and Methods The system utilizes an accelerometer to detect muscle movement in animals. It comprises an Arduino Pro Mini board, ADXL345 accelerometer, LF33CV3 voltage regulator, Wi-Fi module, lithium battery, dual battery holder, and a smartphone. Acceleration data is captured along three directions (X, Y, Z) and transmitted to a smartphone via Wi-Fi. The necessary code was written in the Arduino programming environment. Outlier data were filtered using R software before transferring the remaining data to Excel for further analysis. Results and Discussion The system was tested in two configurations: as a necklace and on the snout of livestock. The snout configuration yielded optimal results with 88% sensitivity, 94% precision, and 94% F-score. Ensuring comfort for the livestock while using the monitoring system was crucial; thus, efforts were made to design lighter and smaller electronic components using SMD technology. Final evaluations showed sensitivity at 91%, accuracy at 82%, and F-score at 86%. Conclusion The ADXL345 accelerometer with ±8g sensitivity is ideal for measuring acceleration across X, Y, and Z directions due to its low data dispersion and high accuracy. Its affordability and compact size make it suitable for research applications comparable to a priority booklet. A waterproof bag installation proved effective as it maintains sensor position while protecting against environmental factors like rain or humidity. In this study, the optimal installation location was determined to be on the muzzle due to significant muscle activity during chewing. This positioning allows for accurate acceleration measurements across all three axes during rumination while maximizing accuracy, sensitivity, and F-score. The circuit was installed in SMD mode with minimal error at a compact size on the animal's muzzle, ensuring nearly zero disconnection risk and improved data collection performance.

https://jam.tabrizu.ac.ir/article_18888_136b9cd85185f417e498a0542dc3259a.pdf

University of Tabriz Journal of Agricultural Mechanization 2383-126X 9 4 2024 12 21 Assessing Rice Farming Mechanization Indicators in Lahijan and Astaneh Ashrafiyeh Counties of Guilan Province Assessing Rice Farming Mechanization Indicators in Lahijan and Astaneh Ashrafiyeh Counties of Guilan Province 29 42 18974 10.22034/jam.2024.64248.1299 FA Roohollah Yousefi Assistant Professor, Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran. Journal Article 2024 10 29 Introduction The requirement for correct planning regarding agricultural mechanization is sufficient recognition of the existing situation. To determine the existing situation and compare the mechanization status of each region with another region, there is a need for have been to fully defined and meaningful indicators and criteria. The consciousness of the current situation and the distance between each region obtaining the optimal level can be used to provide a suitable program and development of mechanization for finding and resolving the disturbances and inequalities. In this research, the indicators of rice mechanization in Lahijan and Astaneh Ashrafiyeh counties of Guilan province were investigated and compared. From the data, the current state of mechanization of rice has been determined and the necessary solutions for their improvement have been provided. Materials and Methods Guilan province is one of the northern provinces of Iran, with an area of 14711 square kilometers which stands the second-ranking (31% of the total) in terms of area harvested. A study was conducted during the years 2020 and 2021 to determination of indicators that determine the mechanization development process in Lahijan and Astaneh Ashrafiyeh counties of Guilan province. The field method or field study, which broad-based (holistic) and deep-based (depth-based) methods are its subset, and questioning and observation as its tools, was the basis of investigations and data collection in this research. In this way, due to the lack of access to all the villages of each county, from the villages covered by the agricultural jihad centers, villages randomly have been selected and after examining their condition, the relative homogeneity of the area was determined and the obtained information has been generalized to other places. Collecting the required information and data has been done by completing the questionnaire and by referring to the available statistical sources, field surveys, and interviews with the exploiters. The desired statistics were collected from reliable centers such as the province's agricultural jihad organization, agricultural jihad management of the cities, agricultural jihad centers, and the statistics of the Ministry of Agricultural Jihad were also used. From the obtained information, the mechanization indices including the degree of mechanization, mechanization level, mechanization capacity, machine executive level, machine productivity level, mechanization economic efficiency, and machine farm efficiency were calculated. Results and Discussion The results revealed that in Lahijan and Astaneh Ashrafiyeh counties of Guilan, the degree of mechanization of tillage operations was 100 and 100 percent, transplanting 55.42 and 89.75 percent, spraying 34.09 and 57.98 percent, weeding 2.23 and 5.04 percent and mechanized rice harvesting with rice harvesters and combines 88.45 and 93.54 percent, respectively. The level, economic efficiency, and average capacity of rice mechanization in Lahijan and Astaneh Ashrafiyeh counties were determined to be 3.24 and 4.86 horsepower per hectare, 0.69 and 0.51 ton per horsepower and 201.57 and 437.92 horsepower-hour per hectare, respectively. On average, in Lahijan and Astaneh Ashrafiyeh counties, there was one tractor for every 34 and 36 hectares, a tiller for every 6 and 2 hectares, a transplanter for every 40 and 29 hectares, and a combine harvester for every 40 and 29 hectares, respectively. According to the results, the number of machines available in Lahijan county in tillage (Primary tillage, Secondary tillage, Puddling, Leveling), spraying and harvesting (Rice reaper, rice combine harvester, baler) is 67.1, 70.2 and 40.8% more and in planting and weeding are 25.5 and 64.3% less than the estimated number and in Astaneh Ashrafiyeh county in tillage (Primary tillage, Secondary tillage, Puddling, Leveling), planting and harvesting (Rice reaper, rice combine harvester, baler) are 88.3, 23.6 and 45.9% more and in spraying and weeding are 8.2 and 10.7% less than the estimated number. Conclusion The results of this study show that the number of tillage machines and transplanters available in Lahijan and Astaneh Ashrafiyeh counties of Guilan province is suitable, and only by improving the management of machines, the level of implementation of mechanized transplanting operations should be increased. In the case of harvesting machines, there is a need to strengthen and introduce more machines to improve the degree of mechanization, and in the case of weeding operations, due to the low degree of mechanization, there is an urgent need to plan for the introduction of suitable machines. Due to the high cost of purchasing self-propelled machinery and the smallness of the land, the average ratio of self-propelled machinery to the operator was not suitable, which caused the decision-making power of operators to be low in operating at the proper time. Introduction The requirement for correct planning regarding agricultural mechanization is sufficient recognition of the existing situation. To determine the existing situation and compare the mechanization status of each region with another region, there is a need for have been to fully defined and meaningful indicators and criteria. The consciousness of the current situation and the distance between each region obtaining the optimal level can be used to provide a suitable program and development of mechanization for finding and resolving the disturbances and inequalities. In this research, the indicators of rice mechanization in Lahijan and Astaneh Ashrafiyeh counties of Guilan province were investigated and compared. From the data, the current state of mechanization of rice has been determined and the necessary solutions for their improvement have been provided. Materials and Methods Guilan province is one of the northern provinces of Iran, with an area of 14711 square kilometers which stands the second-ranking (31% of the total) in terms of area harvested. A study was conducted during the years 2020 and 2021 to determination of indicators that determine the mechanization development process in Lahijan and Astaneh Ashrafiyeh counties of Guilan province. The field method or field study, which broad-based (holistic) and deep-based (depth-based) methods are its subset, and questioning and observation as its tools, was the basis of investigations and data collection in this research. In this way, due to the lack of access to all the villages of each county, from the villages covered by the agricultural jihad centers, villages randomly have been selected and after examining their condition, the relative homogeneity of the area was determined and the obtained information has been generalized to other places. Collecting the required information and data has been done by completing the questionnaire and by referring to the available statistical sources, field surveys, and interviews with the exploiters. The desired statistics were collected from reliable centers such as the province's agricultural jihad organization, agricultural jihad management of the cities, agricultural jihad centers, and the statistics of the Ministry of Agricultural Jihad were also used. From the obtained information, the mechanization indices including the degree of mechanization, mechanization level, mechanization capacity, machine executive level, machine productivity level, mechanization economic efficiency, and machine farm efficiency were calculated. Results and Discussion The results revealed that in Lahijan and Astaneh Ashrafiyeh counties of Guilan, the degree of mechanization of tillage operations was 100 and 100 percent, transplanting 55.42 and 89.75 percent, spraying 34.09 and 57.98 percent, weeding 2.23 and 5.04 percent and mechanized rice harvesting with rice harvesters and combines 88.45 and 93.54 percent, respectively. The level, economic efficiency, and average capacity of rice mechanization in Lahijan and Astaneh Ashrafiyeh counties were determined to be 3.24 and 4.86 horsepower per hectare, 0.69 and 0.51 ton per horsepower and 201.57 and 437.92 horsepower-hour per hectare, respectively. On average, in Lahijan and Astaneh Ashrafiyeh counties, there was one tractor for every 34 and 36 hectares, a tiller for every 6 and 2 hectares, a transplanter for every 40 and 29 hectares, and a combine harvester for every 40 and 29 hectares, respectively. According to the results, the number of machines available in Lahijan county in tillage (Primary tillage, Secondary tillage, Puddling, Leveling), spraying and harvesting (Rice reaper, rice combine harvester, baler) is 67.1, 70.2 and 40.8% more and in planting and weeding are 25.5 and 64.3% less than the estimated number and in Astaneh Ashrafiyeh county in tillage (Primary tillage, Secondary tillage, Puddling, Leveling), planting and harvesting (Rice reaper, rice combine harvester, baler) are 88.3, 23.6 and 45.9% more and in spraying and weeding are 8.2 and 10.7% less than the estimated number. Conclusion The results of this study show that the number of tillage machines and transplanters available in Lahijan and Astaneh Ashrafiyeh counties of Guilan province is suitable, and only by improving the management of machines, the level of implementation of mechanized transplanting operations should be increased. In the case of harvesting machines, there is a need to strengthen and introduce more machines to improve the degree of mechanization, and in the case of weeding operations, due to the low degree of mechanization, there is an urgent need to plan for the introduction of suitable machines. Due to the high cost of purchasing self-propelled machinery and the smallness of the land, the average ratio of self-propelled machinery to the operator was not suitable, which caused the decision-making power of operators to be low in operating at the proper time.

https://jam.tabrizu.ac.ir/article_18974_d99c966d4beaa27192ee2f121b854dab.pdf

University of Tabriz Journal of Agricultural Mechanization 2383-126X 9 4 2024 12 21 Simulation of Mixing Effect on Methane Production in Anaerobic Digestion Simulation of Mixing Effect on Methane Production in Anaerobic Digestion 43 58 18826 10.22034/jam.2024.63498.1294 FA Mohammad Mohammadi Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Arman Jalali Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Shamsollah Abdollahpur Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran Journal Article 2024 09 23 Anaerobic digestion of materials is one of the accepted technologies in the field of industry. In this technology, providing the necessary conditions for optimal mixing of materials is of great importance. In this research, the mixing process was simulated using Computational Fluid Dynamics (CFD), and the possibility of predicting the kinetic process of biogas production from animal waste and determining the optimum speed of the stirrer during the process was investigated. In the initial stages of the work, data related to an anaerobic digester with an agitator, and mixing speeds of 0, 100, and 150 rpm were recorded for one month, and the measured characteristics were converted into the inputs of the ADM1 model. Then, the initial values that were reported during the start-up stage of the digester were estimated. The reactor was optimized to a volume of 400 liters. The stirring system is mechanical and works for five minutes every 6 hours at speeds of zero, 100, and 150 rpm. According to the graphs and the results, the produced gas has almost a constant trend from the 15th day onwards and reaches 75% of methane, and the highest average percentage of methane produced is 64%, which happened at a stirring speed of 100 rpm. During the experiments, the pH was in the range of 5.7 to 7.3. Introduction As the population increases and energy resources are limited, all countries will face energy problems. The crises that threaten countries and societies are the lack of energy resources (fossil fuels) and the increase in environmental pollution caused by excessive consumption of fossil fuels, which shows the necessity and importance of using alternative energy sources. The close connection between economic and environmental issues has created new approaches in the field of international environmental law, one of the most prominent of which is the green economy, and since one of the main goals of the green economy is to reduce greenhouse gas emissions, the use of renewable energy sources is a fast way to Achieving a green economy. Mixing is an important process in AD that has the following advantages: (1) It promotes direct contact among enzymes, bacteria, and substrates; (2) It avoids foam formation and sedimentation; (3) It enhances heat and mass transfer; (4) It facilitates the release of biogas; (5) It disperses any toxic materials in the influent to avoid inhibitions. Some researchers also compared different intermittently mixed anaerobic digesters. Materials and Methods In this research, a digester with a diameter of 60 cm was used and the volume of the digester was 0.4 cubic meters. The standard volume of the maximum substrate that can be loaded is 0.325 cubic meters. Digester stirring is done by a mechanical stirrer connected to an electric motor in the central part of the top of the cap. The whole digester has a capacity of three layers of materials, each layer has its own sensors. Acidity and temperature sensors collect the relevant variable status and store and transfer it to virtual memory through the electronic control system. The anaerobic digester system in the bioenergy and recycling laboratory unit has been repaired, and a sample of cow manure was prepared from the animal husbandry unit around Tabriz and transferred to the laboratory as a substrate for conducting research. The experiment was done in three repetitions, and in each repetition, 150 kg of fresh animal waste was poured into the digester tank with 150 liters of water. Then, to add methanogenic microorganisms to the substrate, 10% of the total weight of the tank (substrate), i.e. 30 kg of animal rumen, was prepared and added. Each repetition of this process continued for 30 days, and the temperature inside the tank was kept at the same temperature as the outside environment (30 degrees Celsius) in the first repetition, and at 35 degrees Celsius in the second and third repetitions. Mixing was done automatically for 5 minutes only in the second and third repetitions and every 6 hours, and the mixing speed was set to 100 and 150 rpm, respectively. After the system started working, gas was discharged twice a day (every 12 hours) according to the production rate and pressure. The total amount of methane produced until that day was measured on the meter and the percentage of methane gas produced daily was measured by the methanometer. Also, in this research, using computational fluid dynamics (CFD), the prediction of the kinetic process of biogas production from animal waste and the provision of the appropriate stirring cycle during the anaerobic digestion process was investigated. In the initial stages of the work, data related to an anaerobic digester with an agitator, and mixing speeds of 0, 100, and 150 rpm were recorded for one month, and the measured characteristics were converted into the inputs of the ADM1 model. Then, the initial values that were reported during the start-up stage of the digester were estimated. Results and Discussion According to the graphs and the results, the produced gas has almost a constant trend from the 10th day onwards and reaches 75% of methane, and the highest average percentage of methane produced is 64%, which happened at a stirring speed of 100 rpm. During the experiments, the pH was in the range of 5.7 to 7.3. Gas production is approximately fixed from the 15th day onwards and reaches 80% of methane. As can be seen in the figure, biogas production usually decreases on days with increased loading; In every change of the input organic load, the largest amount of freshly undigested feed enters the system, so the digestion steps begin with cell destruction and hydrolysis. These steps are often time-consuming and, in addition, the products of the hydrolysis step are acidic. Therefore, it is expected that the activity of biogas production microorganisms will decrease with the acidification of the environment. Conclusion In this work, the effects of mixing time on AD performance were studied experimentally and numerically. The results showed that when the mixing time in intermittent mixing mode was long enough to homogenize the digester, then increasing the mixing time would not increase biogas yield but increase energy input. However, if the digester cannot reach homogeneity within the mixing time in intermittent mixing mode, then the digester cannot operate in its optimum condition. These results indicated that simulated mixing time can be used as a reference to determine the minimal experimental mixing time to increase the AD efficiency. Anaerobic digestion of materials is one of the accepted technologies in the field of industry. In this technology, providing the necessary conditions for optimal mixing of materials is of great importance. In this research, the mixing process was simulated using Computational Fluid Dynamics (CFD), and the possibility of predicting the kinetic process of biogas production from animal waste and determining the optimum speed of the stirrer during the process was investigated. In the initial stages of the work, data related to an anaerobic digester with an agitator, and mixing speeds of 0, 100, and 150 rpm were recorded for one month, and the measured characteristics were converted into the inputs of the ADM1 model. Then, the initial values that were reported during the start-up stage of the digester were estimated. The reactor was optimized to a volume of 400 liters. The stirring system is mechanical and works for five minutes every 6 hours at speeds of zero, 100, and 150 rpm. According to the graphs and the results, the produced gas has almost a constant trend from the 15th day onwards and reaches 75% of methane, and the highest average percentage of methane produced is 64%, which happened at a stirring speed of 100 rpm. During the experiments, the pH was in the range of 5.7 to 7.3. Introduction As the population increases and energy resources are limited, all countries will face energy problems. The crises that threaten countries and societies are the lack of energy resources (fossil fuels) and the increase in environmental pollution caused by excessive consumption of fossil fuels, which shows the necessity and importance of using alternative energy sources. The close connection between economic and environmental issues has created new approaches in the field of international environmental law, one of the most prominent of which is the green economy, and since one of the main goals of the green economy is to reduce greenhouse gas emissions, the use of renewable energy sources is a fast way to Achieving a green economy. Mixing is an important process in AD that has the following advantages: (1) It promotes direct contact among enzymes, bacteria, and substrates; (2) It avoids foam formation and sedimentation; (3) It enhances heat and mass transfer; (4) It facilitates the release of biogas; (5) It disperses any toxic materials in the influent to avoid inhibitions. Some researchers also compared different intermittently mixed anaerobic digesters. Materials and Methods In this research, a digester with a diameter of 60 cm was used and the volume of the digester was 0.4 cubic meters. The standard volume of the maximum substrate that can be loaded is 0.325 cubic meters. Digester stirring is done by a mechanical stirrer connected to an electric motor in the central part of the top of the cap. The whole digester has a capacity of three layers of materials, each layer has its own sensors. Acidity and temperature sensors collect the relevant variable status and store and transfer it to virtual memory through the electronic control system. The anaerobic digester system in the bioenergy and recycling laboratory unit has been repaired, and a sample of cow manure was prepared from the animal husbandry unit around Tabriz and transferred to the laboratory as a substrate for conducting research. The experiment was done in three repetitions, and in each repetition, 150 kg of fresh animal waste was poured into the digester tank with 150 liters of water. Then, to add methanogenic microorganisms to the substrate, 10% of the total weight of the tank (substrate), i.e. 30 kg of animal rumen, was prepared and added. Each repetition of this process continued for 30 days, and the temperature inside the tank was kept at the same temperature as the outside environment (30 degrees Celsius) in the first repetition, and at 35 degrees Celsius in the second and third repetitions. Mixing was done automatically for 5 minutes only in the second and third repetitions and every 6 hours, and the mixing speed was set to 100 and 150 rpm, respectively. After the system started working, gas was discharged twice a day (every 12 hours) according to the production rate and pressure. The total amount of methane produced until that day was measured on the meter and the percentage of methane gas produced daily was measured by the methanometer. Also, in this research, using computational fluid dynamics (CFD), the prediction of the kinetic process of biogas production from animal waste and the provision of the appropriate stirring cycle during the anaerobic digestion process was investigated. In the initial stages of the work, data related to an anaerobic digester with an agitator, and mixing speeds of 0, 100, and 150 rpm were recorded for one month, and the measured characteristics were converted into the inputs of the ADM1 model. Then, the initial values that were reported during the start-up stage of the digester were estimated. Results and Discussion According to the graphs and the results, the produced gas has almost a constant trend from the 10th day onwards and reaches 75% of methane, and the highest average percentage of methane produced is 64%, which happened at a stirring speed of 100 rpm. During the experiments, the pH was in the range of 5.7 to 7.3. Gas production is approximately fixed from the 15th day onwards and reaches 80% of methane. As can be seen in the figure, biogas production usually decreases on days with increased loading; In every change of the input organic load, the largest amount of freshly undigested feed enters the system, so the digestion steps begin with cell destruction and hydrolysis. These steps are often time-consuming and, in addition, the products of the hydrolysis step are acidic. Therefore, it is expected that the activity of biogas production microorganisms will decrease with the acidification of the environment. Conclusion In this work, the effects of mixing time on AD performance were studied experimentally and numerically. The results showed that when the mixing time in intermittent mixing mode was long enough to homogenize the digester, then increasing the mixing time would not increase biogas yield but increase energy input. However, if the digester cannot reach homogeneity within the mixing time in intermittent mixing mode, then the digester cannot operate in its optimum condition. These results indicated that simulated mixing time can be used as a reference to determine the minimal experimental mixing time to increase the AD efficiency.

https://jam.tabrizu.ac.ir/article_18826_162fd99dd77571893eda0c69e1d06066.pdf

University of Tabriz Journal of Agricultural Mechanization 2383-126X 9 4 2024 12 21 Life Cycle Assessment (LCA) of Peach Fruit in Mazandaran Province Life Cycle Assessment (LCA) of Peach Fruit in Mazandaran Province 59 70 19033 10.22034/jam.2025.64261.1301 FA Abolfazl Azizi Sharafdar Kalaei Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran Hossein Haji Agha Alizadeh Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran Behdad Shadidi Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran Journal Article 2024 10 29 increase in population growth has increased the demand for agricultural and horticultural products, and given the limitations of arable land, a strategy must be pursued to increase production per unit area. This strategy requires the use of various chemical inputs in the cultivation of various products, which will have many harmful effects. The present study investigated the environmental impacts (using SimaPro software) during the one-year growth period of peach fruit in Mazandaran province. In this study, environmental indicators in peach fruit production were determined using the life cycle assessment and the IMPACT 2002+ method. Input data were determined using a questionnaire and output data were determined using the Ecoinvent database available in SimaPro 9.00.48 software and the methods and standards used by researchers in previous studies. The highest contribution to eutrophication was calculated for diesel fuel at 0.00195 in terms of PO4. The highest contribution to ozone depletion was calculated for diesel fuel and pesticides at 0.00000466 and 0.00000698 in terms of CFC-11eq, respectively. The most important factors in the number of environmental indicators for producing one ton of peach fruit in a year were nitrogen fertilizer, the use of agricultural machinery, and also diesel fuel used in the orchard. According to the results obtained and also the research conducted in this field, nitrogen fertilizer was the main factor in environmental indicators. Introduction Environmental risks are a major concern in Iran. On the other hand, agriculture plays a key role in environmental impacts in this country, as this sector is both a producer and consumer of energy and can increase or decrease environmental impacts. Some methods can help reduce the environmental consequences of agricultural production. One of the most common tools for analyzing environmental systems is life cycle assessment. A technique called life cycle assessment (LCA) evaluates a product's possible environmental impact at each stage of production, from the extraction of raw materials to waste management. It would appear vital to look into the environmental effects of peach production in Mazandaran, as it is the province with the highest volume of peach production in Iran. The life cycle assessment of the peach product will be examined and studied in this study as no research has been conducted in Mazandaran province on the evaluation of this product. Materials and Methods The majority of the data gathered in the province was in the cities of Neka, Miandoroud, and Sari because they have the largest peach production areas in the province. The quantity of inputs used and the costs incurred were assessed following the creation of the questionnaires and their completion by various gardeners around the province. All peach gardeners in Mazandaran province are included in the research's statistical population. There are roughly 4250 peach orchards in the province overall, based on data gathered from Sari's Agricultural Jihad Department. A simple method of random sampling was applied in this study. Sima Pro 9.00.48 software was used to enter the data gathered from peach fruit production, and the result was calculated according to one ton of peach fruit. A large amount of information in the database related to every product around the world is stored in this software, at each stage of production the collected data is entered into the software separately and then for the final evaluation of the IMPACT 2002+ model, among the models that There is in the software was selected. The information that was stored in the software was considered as input and other information from the inputs consumed for a production period as well as the coefficients related to the consumption of fuel, fertilizer, etc. were also entered into the software. Results and Discussion Overuse of agricultural inputs, such as fossil fuels and chemical fertilizers, has resulted in negative environmental effects, such as increased global warming, a decline in biodiversity, and deterioration of soil quality, such as erosion, compaction, or a decrease in soil organic matter. The amount of global warming index for the production of one ton of peach fruit was calculated to be 120 kg CO2 equivalent, and the largest share of this index belonged to greenhouse emissions and consumption of diesel fuel and nitrogen fertilizer. The amount of ozone depletion potential for the production of one ton of peaches was calculated as 0.00000712 kilograms to CFC-11 eq. The use of diesel fuel and the use of pesticides has had the greatest effect on this environmental index. The number of environmental indicators such as respiratory organic matter, aquatic environmental toxicity, terrestrial environmental toxicity, and soil acidity were calculated as 0.0212, 0.00676, 0.00141, and 0.593 kg equivalent of BD (dichlorobenzene) respectively, that the consumption of nitrogen fertilizer and the use of agricultural machinery during the planting and harvesting of corn have contributed the most to the distribution of these indicators. Conclusion The most important factors in the number of environmental indicators for producing one ton of peach fruit in a year were nitrogen fertilizer, the use of agricultural machinery, and diesel fuel. According to the results obtained and the research conducted in this field, nitrogen fertilizer was the main factor in environmental indicators. For better environmental management of peach production, it is recommended that farmers be encouraged to choose fertilizers with low environmental impacts, such as biofertilizers or chemical fertilizers with a lower environmental burden than nitrogen fertilizers. The use of organic fertilizers can also improve performance and reduce the emission of environmental impacts of chemical fertilizers. Environmental regulations such as labeling food products with environmental impacts can also be considered as a way to reduce the environmental impacts of peach production. increase in population growth has increased the demand for agricultural and horticultural products, and given the limitations of arable land, a strategy must be pursued to increase production per unit area. This strategy requires the use of various chemical inputs in the cultivation of various products, which will have many harmful effects. The present study investigated the environmental impacts (using SimaPro software) during the one-year growth period of peach fruit in Mazandaran province. In this study, environmental indicators in peach fruit production were determined using the life cycle assessment and the IMPACT 2002+ method. Input data were determined using a questionnaire and output data were determined using the Ecoinvent database available in SimaPro 9.00.48 software and the methods and standards used by researchers in previous studies. The highest contribution to eutrophication was calculated for diesel fuel at 0.00195 in terms of PO4. The highest contribution to ozone depletion was calculated for diesel fuel and pesticides at 0.00000466 and 0.00000698 in terms of CFC-11eq, respectively. The most important factors in the number of environmental indicators for producing one ton of peach fruit in a year were nitrogen fertilizer, the use of agricultural machinery, and also diesel fuel used in the orchard. According to the results obtained and also the research conducted in this field, nitrogen fertilizer was the main factor in environmental indicators. Introduction Environmental risks are a major concern in Iran. On the other hand, agriculture plays a key role in environmental impacts in this country, as this sector is both a producer and consumer of energy and can increase or decrease environmental impacts. Some methods can help reduce the environmental consequences of agricultural production. One of the most common tools for analyzing environmental systems is life cycle assessment. A technique called life cycle assessment (LCA) evaluates a product's possible environmental impact at each stage of production, from the extraction of raw materials to waste management. It would appear vital to look into the environmental effects of peach production in Mazandaran, as it is the province with the highest volume of peach production in Iran. The life cycle assessment of the peach product will be examined and studied in this study as no research has been conducted in Mazandaran province on the evaluation of this product. Materials and Methods The majority of the data gathered in the province was in the cities of Neka, Miandoroud, and Sari because they have the largest peach production areas in the province. The quantity of inputs used and the costs incurred were assessed following the creation of the questionnaires and their completion by various gardeners around the province. All peach gardeners in Mazandaran province are included in the research's statistical population. There are roughly 4250 peach orchards in the province overall, based on data gathered from Sari's Agricultural Jihad Department. A simple method of random sampling was applied in this study. Sima Pro 9.00.48 software was used to enter the data gathered from peach fruit production, and the result was calculated according to one ton of peach fruit. A large amount of information in the database related to every product around the world is stored in this software, at each stage of production the collected data is entered into the software separately and then for the final evaluation of the IMPACT 2002+ model, among the models that There is in the software was selected. The information that was stored in the software was considered as input and other information from the inputs consumed for a production period as well as the coefficients related to the consumption of fuel, fertilizer, etc. were also entered into the software. Results and Discussion Overuse of agricultural inputs, such as fossil fuels and chemical fertilizers, has resulted in negative environmental effects, such as increased global warming, a decline in biodiversity, and deterioration of soil quality, such as erosion, compaction, or a decrease in soil organic matter. The amount of global warming index for the production of one ton of peach fruit was calculated to be 120 kg CO2 equivalent, and the largest share of this index belonged to greenhouse emissions and consumption of diesel fuel and nitrogen fertilizer. The amount of ozone depletion potential for the production of one ton of peaches was calculated as 0.00000712 kilograms to CFC-11 eq. The use of diesel fuel and the use of pesticides has had the greatest effect on this environmental index. The number of environmental indicators such as respiratory organic matter, aquatic environmental toxicity, terrestrial environmental toxicity, and soil acidity were calculated as 0.0212, 0.00676, 0.00141, and 0.593 kg equivalent of BD (dichlorobenzene) respectively, that the consumption of nitrogen fertilizer and the use of agricultural machinery during the planting and harvesting of corn have contributed the most to the distribution of these indicators. Conclusion The most important factors in the number of environmental indicators for producing one ton of peach fruit in a year were nitrogen fertilizer, the use of agricultural machinery, and diesel fuel. According to the results obtained and the research conducted in this field, nitrogen fertilizer was the main factor in environmental indicators. For better environmental management of peach production, it is recommended that farmers be encouraged to choose fertilizers with low environmental impacts, such as biofertilizers or chemical fertilizers with a lower environmental burden than nitrogen fertilizers. The use of organic fertilizers can also improve performance and reduce the emission of environmental impacts of chemical fertilizers. Environmental regulations such as labeling food products with environmental impacts can also be considered as a way to reduce the environmental impacts of peach production.

https://jam.tabrizu.ac.ir/article_19033_eea74dab412e7155766393b51dfd7e34.pdf

University of Tabriz Journal of Agricultural Mechanization 2383-126X 9 4 2024 12 21 Agricultural Mechanization Assessment in Boroujerd County by Mechanization Evaluation Indices Agricultural Mechanization Assessment in Boroujerd County by Mechanization Evaluation Indices 71 88 18916 10.22034/jam.2024.62765.1285 FA Mehrdad Jalalvand Department of Agricultural Machinery Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran Asadollah Akram Department of Agricultural Machinery Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran Majid Khanali Department of Agricultural Machinery Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran Journal Article 2024 08 02 This study aimed to investigate agricultural mechanization status by agricultural mechanization indices in Boroujerd County. Statistics and Data were collected by specially designed questionnaires, field surveys, and data received from Boroujerd Agricultural Jihad Management and National Meteorological Organization. In this research Degree, Level, Economic Efficiency, Ratio of Power Sources to cultivated area and stakeholder, Executive Power, Productivity Coefficient, and Capacity of Mechanization indices were investigated. Based on the obtained results, in terms of the degree of mechanization of the Boroujerd county, the degree of power-intensive operations e.g., primary tillage had the highest value compared to control-intensive operations. The level of mechanization was computed in two forms that are standard and real, and values of 1.41 hp per ha and 3.08 hp per ha were obtained respectively. Economic efficiency was determined to be 261630.35 ton per hp for standard and 119772.33 tons per hp for real forms. There are approximately 6 tractors and 8.08 cereal combine machines for a 100 ha of underplanted area in the region. Also, the results show that one tractor and one cereal combine machine belong to 8.8 and 915 Stakeholder respectively. Executive power potentially is 520797.42 ha and with regard to Real Executive power (32369 ha), the productivity coefficient is 6.21 percent. The capacity of mechanization for harvested cereal by combines and harvester machines is 7.50 and 17.82 hp per h per ha respectively, and 7.40 hp per h per ha for alpha and clover crops. Introduction Agriculture plays an essential role in providing the basic necessary needs of humans. The increase in population and the decrease in production resources indicate the need to change the attitude in different sectors of agriculture by producers, specialists, and decision-makers. In the first view of this change, agricultural mechanization appears as a general concept. In the first step, agricultural mechanization appears as a general concept. The role of mechanization is more than a principle and an input in agricultural production. The most comprehensive definition of agricultural mechanization says that: agricultural mechanization is the use of mechanical equipment and tools, and in more general terms, it is the use of modern technology in agriculture to increase productivity, and in other words, it is a way to achieve sustainable development. Agricultural mechanization has experienced different situations in Iran. A review of the process of agricultural mechanization in the country and looking at the current situation reveals the non-implementation of written programs, which is caused by hasty decisions and a lack of logical justification. The first step in order to improve the agricultural mechanization of any region is to recognize and analyze the current situation. There are defined comparative factors that are called indices. These indices describe the agricultural mechanization status in each region. There are several indices such as Degree, Level, and Capacity of Mechanization. In this research, Degree, Level, Economic Efficiency, Ratio of Power Sources to cultivated area and stakeholder, Executive Power, Productivity Coefficient, and Capacity of mechanization indices were investigated. The purpose of this research is to investigate the agricultural mechanization status in Borujerd County by calculating agricultural mechanization indices. Materials and Methods This research was conducted in Boroujerd County. There are 23000 ha of irrigated crops, 35000 ha of dryland crops, and more than 13000 ha of horticulture plants in this region. Necessary data were gathered by questionnaire, field survey, and data received from Boroujerd Agricultural Jihad Management and National Meteorological Organization. About 80% of the cultivated area is cereals and fodder plants (45.66% wheat and barley and 13.43% alfalfa and clover) and the share of other crops is insignificant. For this reason, this research is focused on the mechanization status of six important and major crops in the region, namely water wheat, dry wheat, water barley, dry barley, alfalfa, and clover. In this research, Degree, Level, Economic Efficiency, Ratio of Power Sources to cultivated area and stakeholder, Executive Power, Productivity Coefficient, and Capacity of mechanization indices were investigated. Results and Discussion Based on the obtained results, in terms of the degree of mechanization in Boroujerd County, the degree of power-intensive operations e.g., primary tillage had the highest value compared to control-intensive operations. The level of mechanization was computed in two forms, standard and real, and values of 1.41 hp per ha and 3.08 hp per ha were obtained respectively. Economic efficiency was determined to be 261630.35 and 119772.33 tons per ha for standard and real forms respectively. There are approximately 6 tractors and 8.08 cereal combine machines for 100 ha of cultivated area in the region. Also, the results show that one tractor and one cereal combine machine belong to 8.8 and 915 stakeholders respectively. Executive power potentially is 520797.42 ha and with regard to real executive power (32369 ha), the productivity coefficient is 6.21 percent. The capacity of mechanization for harvested cereal by combine and harvester machine is 7.50 and 17.82 hp per h per ha respectively, and 7.40 hp - h per ha for alpha and clover crop. Conclusion According to the results of this study, the following offers will be effective in improving mechanization evaluation indices in Borujerd County and other places with similar conditions: - Observance of all necessary standards in the manufacture of agricultural machines and equipment by Producers - Renovation of the agricultural machines and equipment - Facilitating the conditions of receiving self-propelled machines and other equipment - Supply of agricultural machines with various brands if there are suitable after-sales services. - Timely provision of the machines and equipment - Production of simpler machines and equipment that requires a lower level of technology - Reducing the interest rate of bank facilities - Preventing land fragmentation - Teaching and explaining the need for mechanized agriculture instead of traditional agriculture - Continuous and targeted training on the principle use of machines and equipment, including settings, time, and manner of use This study aimed to investigate agricultural mechanization status by agricultural mechanization indices in Boroujerd County. Statistics and Data were collected by specially designed questionnaires, field surveys, and data received from Boroujerd Agricultural Jihad Management and National Meteorological Organization. In this research Degree, Level, Economic Efficiency, Ratio of Power Sources to cultivated area and stakeholder, Executive Power, Productivity Coefficient, and Capacity of Mechanization indices were investigated. Based on the obtained results, in terms of the degree of mechanization of the Boroujerd county, the degree of power-intensive operations e.g., primary tillage had the highest value compared to control-intensive operations. The level of mechanization was computed in two forms that are standard and real, and values of 1.41 hp per ha and 3.08 hp per ha were obtained respectively. Economic efficiency was determined to be 261630.35 ton per hp for standard and 119772.33 tons per hp for real forms. There are approximately 6 tractors and 8.08 cereal combine machines for a 100 ha of underplanted area in the region. Also, the results show that one tractor and one cereal combine machine belong to 8.8 and 915 Stakeholder respectively. Executive power potentially is 520797.42 ha and with regard to Real Executive power (32369 ha), the productivity coefficient is 6.21 percent. The capacity of mechanization for harvested cereal by combines and harvester machines is 7.50 and 17.82 hp per h per ha respectively, and 7.40 hp per h per ha for alpha and clover crops. Introduction Agriculture plays an essential role in providing the basic necessary needs of humans. The increase in population and the decrease in production resources indicate the need to change the attitude in different sectors of agriculture by producers, specialists, and decision-makers. In the first view of this change, agricultural mechanization appears as a general concept. In the first step, agricultural mechanization appears as a general concept. The role of mechanization is more than a principle and an input in agricultural production. The most comprehensive definition of agricultural mechanization says that: agricultural mechanization is the use of mechanical equipment and tools, and in more general terms, it is the use of modern technology in agriculture to increase productivity, and in other words, it is a way to achieve sustainable development. Agricultural mechanization has experienced different situations in Iran. A review of the process of agricultural mechanization in the country and looking at the current situation reveals the non-implementation of written programs, which is caused by hasty decisions and a lack of logical justification. The first step in order to improve the agricultural mechanization of any region is to recognize and analyze the current situation. There are defined comparative factors that are called indices. These indices describe the agricultural mechanization status in each region. There are several indices such as Degree, Level, and Capacity of Mechanization. In this research, Degree, Level, Economic Efficiency, Ratio of Power Sources to cultivated area and stakeholder, Executive Power, Productivity Coefficient, and Capacity of mechanization indices were investigated. The purpose of this research is to investigate the agricultural mechanization status in Borujerd County by calculating agricultural mechanization indices. Materials and Methods This research was conducted in Boroujerd County. There are 23000 ha of irrigated crops, 35000 ha of dryland crops, and more than 13000 ha of horticulture plants in this region. Necessary data were gathered by questionnaire, field survey, and data received from Boroujerd Agricultural Jihad Management and National Meteorological Organization. About 80% of the cultivated area is cereals and fodder plants (45.66% wheat and barley and 13.43% alfalfa and clover) and the share of other crops is insignificant. For this reason, this research is focused on the mechanization status of six important and major crops in the region, namely water wheat, dry wheat, water barley, dry barley, alfalfa, and clover. In this research, Degree, Level, Economic Efficiency, Ratio of Power Sources to cultivated area and stakeholder, Executive Power, Productivity Coefficient, and Capacity of mechanization indices were investigated. Results and Discussion Based on the obtained results, in terms of the degree of mechanization in Boroujerd County, the degree of power-intensive operations e.g., primary tillage had the highest value compared to control-intensive operations. The level of mechanization was computed in two forms, standard and real, and values of 1.41 hp per ha and 3.08 hp per ha were obtained respectively. Economic efficiency was determined to be 261630.35 and 119772.33 tons per ha for standard and real forms respectively. There are approximately 6 tractors and 8.08 cereal combine machines for 100 ha of cultivated area in the region. Also, the results show that one tractor and one cereal combine machine belong to 8.8 and 915 stakeholders respectively. Executive power potentially is 520797.42 ha and with regard to real executive power (32369 ha), the productivity coefficient is 6.21 percent. The capacity of mechanization for harvested cereal by combine and harvester machine is 7.50 and 17.82 hp per h per ha respectively, and 7.40 hp - h per ha for alpha and clover crop. Conclusion According to the results of this study, the following offers will be effective in improving mechanization evaluation indices in Borujerd County and other places with similar conditions: - Observance of all necessary standards in the manufacture of agricultural machines and equipment by Producers - Renovation of the agricultural machines and equipment - Facilitating the conditions of receiving self-propelled machines and other equipment - Supply of agricultural machines with various brands if there are suitable after-sales services. - Timely provision of the machines and equipment - Production of simpler machines and equipment that requires a lower level of technology - Reducing the interest rate of bank facilities - Preventing land fragmentation - Teaching and explaining the need for mechanized agriculture instead of traditional agriculture - Continuous and targeted training on the principle use of machines and equipment, including settings, time, and manner of use

https://jam.tabrizu.ac.ir/article_18916_360e0efccb7a2cea4889dc0b71d0c215.pdf