University of Tehran PressIranian Journal of Biosystem Engineering2008-480357120260421Identification and Localization of Chickpea Impurities Using SVM and KNN ClassifiersIdentification and Localization of Chickpea Impurities Using SVM and KNN Classifiers11510667610.22059/ijbse.2025.403138.665619FAHosseinBagherpourDepartment of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, IranSiavashShamohammadiDepartment of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, IranJournal Article20250927During chickpea harvesting, various types of impurities are present in the product, which must be identified and removed before market distribution or use as seed. Although pneumatic and mechanical methods can eliminate a substantial portion of these impurities, conventional techniques are insufficient for separating objects such as small stones of similar size to chickpeas or unripe and discolored grains. The objective of this study was to identify the type and determine the location of different chickpea impurities using two intelligent classifiers: Support Vector Machine (SVM) and k-Nearest Neighbors (KNN). For this purpose, 400 RGB images were acquired, encompassing six classes: healthy, green, black, colored, stones, and split chickpeas. After object segmentation and classification into six groups, the total number of samples reached 3,840. Features extracted included mean, median, variance, skewness, histogram, entropy, and texture descriptors derived from the gray-level co-occurrence matrix (GLCM), such as contrast, correlation, energy, and homogeneity. In the SVM model, the RBF kernel exhibited superior performance compared to other kernels. For KNN, the optimal results were obtained with k = 13, the City Block distance metric, and a weighting scheme of 1/(c + D²) with c = 1. Object localization was performed in MATLAB by determining the coordinates of each object's center. Based on the results, the highest classification accuracy for the SVM and KNN models at a resolution of 250×250 pixels were 98.09% and 90.88%, respectively.During chickpea harvesting, various types of impurities are present in the product, which must be identified and removed before market distribution or use as seed. Although pneumatic and mechanical methods can eliminate a substantial portion of these impurities, conventional techniques are insufficient for separating objects such as small stones of similar size to chickpeas or unripe and discolored grains. The objective of this study was to identify the type and determine the location of different chickpea impurities using two intelligent classifiers: Support Vector Machine (SVM) and k-Nearest Neighbors (KNN). For this purpose, 400 RGB images were acquired, encompassing six classes: healthy, green, black, colored, stones, and split chickpeas. After object segmentation and classification into six groups, the total number of samples reached 3,840. Features extracted included mean, median, variance, skewness, histogram, entropy, and texture descriptors derived from the gray-level co-occurrence matrix (GLCM), such as contrast, correlation, energy, and homogeneity. In the SVM model, the RBF kernel exhibited superior performance compared to other kernels. For KNN, the optimal results were obtained with k = 13, the City Block distance metric, and a weighting scheme of 1/(c + D²) with c = 1. Object localization was performed in MATLAB by determining the coordinates of each object's center. Based on the results, the highest classification accuracy for the SVM and KNN models at a resolution of 250×250 pixels were 98.09% and 90.88%, respectively.https://ijbse.ut.ac.ir/article_106676_11ac7ea2b35795347b514858621d6346.pdfUniversity of Tehran PressIranian Journal of Biosystem Engineering2008-480357120260421Improving Performance and Reducing Emissions of a Diesel Engine Using a Hybrid Tri-Fuel: Diesel, Bioethanol, and Iron Oxide (Fe₃O₄) Nanoparticles, An Experimental StudyImproving Performance and Reducing Emissions of a Diesel Engine Using a Hybrid Tri-Fuel: Diesel, Bioethanol, and Iron Oxide (Fe₃O₄) Nanoparticles, An Experimental Study173610667710.22059/ijbse.2025.404789.665625FAAbbasTaghipourInstitute of Manufacturing Engineering and Industrial Technologies, Dez.C. , Islamic Azad University, Dezful, IranBehzadAzizimehrDepartment of Mechanical Engineering, Faculty of Mechanics and Applied Industries, Technical and Vocational University (TVU), Tehran, IranJournal Article20251022This study investigates the simultaneous effect of bioethanol and iron oxide nanoparticles as fuel additives to diesel on the performance parameters and emission of a diesel engine. This ternary combination experimentally demonstrates the mechanism for improving combustion and simultaneously reducing key pollutants. The fuel blends consisted of diesel, bioethanol (0 to 12% by volume), and iron oxide nanoparticles (5-15 ppm). Experiments were conducted in the speed range of 1800 to 2600 rpm, and performance parameters (torque, power, specific fuel consumption) as well as emissions of carbon monoxide, carbon dioxide, unburned hydrocarbons, and nitrogen oxides were measured. The results indicate an improvement in engine performance parameters due to better combustion, resulting from increased oxygen availability. Specifically, the power increase for the B12D88 fuel blend containing 15 ppm of nanoparticles compared to pure diesel fuel is 17.48%. Although the increase in bioethanol, due to its lower calorific value, led to a torque reduction of up to 8.8%, the presence of nanoparticles as a catalyst decreased the SFC by 22.1%, contrary to theoretical predictions. This ternary combination resulted in a reduction of CO by up to 33.3% and CO2 by up to 12.5%, while it did not have a significant effect on unburned hydrocarbons and nitrogen oxides. Based on the results, adding nanoparticles to diesel-bioethanol blends is an effective strategy for improving engine performance and reducing carbon monoxide emissions. Although its effect on nitrogen oxides is less significant, an optimal balance between performance and emissions can be achieved by optimizing the bioethanol ratio.This study investigates the simultaneous effect of bioethanol and iron oxide nanoparticles as fuel additives to diesel on the performance parameters and emission of a diesel engine. This ternary combination experimentally demonstrates the mechanism for improving combustion and simultaneously reducing key pollutants. The fuel blends consisted of diesel, bioethanol (0 to 12% by volume), and iron oxide nanoparticles (5-15 ppm). Experiments were conducted in the speed range of 1800 to 2600 rpm, and performance parameters (torque, power, specific fuel consumption) as well as emissions of carbon monoxide, carbon dioxide, unburned hydrocarbons, and nitrogen oxides were measured. The results indicate an improvement in engine performance parameters due to better combustion, resulting from increased oxygen availability. Specifically, the power increase for the B12D88 fuel blend containing 15 ppm of nanoparticles compared to pure diesel fuel is 17.48%. Although the increase in bioethanol, due to its lower calorific value, led to a torque reduction of up to 8.8%, the presence of nanoparticles as a catalyst decreased the SFC by 22.1%, contrary to theoretical predictions. This ternary combination resulted in a reduction of CO by up to 33.3% and CO2 by up to 12.5%, while it did not have a significant effect on unburned hydrocarbons and nitrogen oxides. Based on the results, adding nanoparticles to diesel-bioethanol blends is an effective strategy for improving engine performance and reducing carbon monoxide emissions. Although its effect on nitrogen oxides is less significant, an optimal balance between performance and emissions can be achieved by optimizing the bioethanol ratio.https://ijbse.ut.ac.ir/article_106677_bf9eca0d27ebe070724ab9fc02e26563.pdfUniversity of Tehran PressIranian Journal of Biosystem Engineering2008-480357120260421Identifying and Analyzing Influential Variables Affecting the Development Pathways of Agricultural Mechanization in Boroujerd Province through PESTEL and Cross-Impact ApproachIdentifying and Analyzing Influential Variables Affecting the Development Pathways of Agricultural Mechanization in Boroujerd Province through PESTEL and Cross-Impact Approach376210667810.22059/ijbse.2026.402239.665612FAMehrdadJalalvandDepartment of Agricultural Machinery Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, IranAsadollahAkramFaculty Member in Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.MajidKhanaliDepartment of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, IranJournal Article20250912Agriculture, as the most critical pillar of food security, requires the adoption of modern and forward-looking technologies in the field of mechanization. The present study was conducted with the aim of identifying and examining the effects of variables influencing the development of agricultural mechanization in Boroujerd Province. To this end, through field studies, documentary reviews, and the collection of expert opinions from specialists in agricultural mechanization, a total of 73 influencing variables were identified and validated. Among these, 64 variables with an importance coefficient higher than 75 percent were selected. After confirming the reliability of the collected questionnaires, cross-impact analysis was conducted across six groups, namely political, economic, sociocultural, technical, environmental, and legal. Then, 19 key variables from different groups were selected, and both direct and indirect influence calculations were performed on these. In the combined analysis of variables, the highest direct influence and dependence scores were obtained for variables education and extension and precision agriculture technology, with respective values of 904 and 1523. Similarly, the highest indirect influence and dependence scores were attributed to government financial support and environmental pressures on natural resources, with respective values of 963 and 1463. According to the results, sustainable development of agricultural mechanization will only be achieved when, alongside technical investments, sociocultural, political, and environmental variables are also given due consideration. Otherwise, the mechanization process will not only lack the necessary efficiency, but may also generate adverse consequences for food security, natural resources, and the overall trajectory of the country's sustainable development.Agriculture, as the most critical pillar of food security, requires the adoption of modern and forward-looking technologies in the field of mechanization. The present study was conducted with the aim of identifying and examining the effects of variables influencing the development of agricultural mechanization in Boroujerd Province. To this end, through field studies, documentary reviews, and the collection of expert opinions from specialists in agricultural mechanization, a total of 73 influencing variables were identified and validated. Among these, 64 variables with an importance coefficient higher than 75 percent were selected. After confirming the reliability of the collected questionnaires, cross-impact analysis was conducted across six groups, namely political, economic, sociocultural, technical, environmental, and legal. Then, 19 key variables from different groups were selected, and both direct and indirect influence calculations were performed on these. In the combined analysis of variables, the highest direct influence and dependence scores were obtained for variables education and extension and precision agriculture technology, with respective values of 904 and 1523. Similarly, the highest indirect influence and dependence scores were attributed to government financial support and environmental pressures on natural resources, with respective values of 963 and 1463. According to the results, sustainable development of agricultural mechanization will only be achieved when, alongside technical investments, sociocultural, political, and environmental variables are also given due consideration. Otherwise, the mechanization process will not only lack the necessary efficiency, but may also generate adverse consequences for food security, natural resources, and the overall trajectory of the country's sustainable development.https://ijbse.ut.ac.ir/article_106678_9b0b696d77d3176695793ea7c7550828.pdfUniversity of Tehran PressIranian Journal of Biosystem Engineering2008-480357120260421Numerical Analysis and Simulation of the Transient Performance of a High-Response Proportional Directional Control Valve in Hydraulic Power Transmission SystemsNumerical Analysis and Simulation of the Transient Performance of a High-Response Proportional Directional Control Valve in Hydraulic Power Transmission Systems638610667910.22059/ijbse.2025.404503.665624FASeyed AlirezaHoseininezhadDepartment of Mechanical Engineering, Faculty of Mechanical Engineering, Jundi-Shapur University of Technology, Dezful, Iran.PezhmanNikandishDepartment of Mechanical Engineering, Faculty of Mechanical Engineering, Jundi-Shapur University of Technology, Dezful, Iran.Journal Article20251017High-response proportional directional control valves play a crucial role in improving the efficiency of hydrostatic power transmission systems in agricultural machinery. However, the rapid switching of these valves can generate undesirable transient phenomena in hydrostatic power transmission systems, thereby compromising overall system stability and energy efficiency. In this study, a comprehensive numerical analysis was performed to investigate the influence of spool displacement speed (2 and 20ms) and the curvature radius of spool lands (0, 2, 4 and 6µm) on the performance characteristics of a high-response proportional directional control valve under both steady-state and transient operating conditions. A three-dimensional computational fluid dynamics model was developed using a moving-mesh approach coupled with the k"-" ε turbulence model to capture the transient flow behavior accurately. To validate the numerical results, a hydraulic power transmission test bench was designed and fabricated to experimentally measure the valve's performance parameters. The comparison revealed that deviations between the numerical and experimental results were less than 5% under steady conditions and less than 6% under transient conditions. Furthermore, reducing the valve switching time from 20 to 2ms resulted in a 19.8% decrease in the average flow rate and a 29.8% increase in the required actuation force. Moreover, introducing a 2µm curvature radius at the spool edges improved the steady-state flow rate by 7.3% and reduced the actuation force by 9.2%. Under transient conditions, this geometric modification further enhanced the flow rate by 15.3% and reduced the required actuation force by 13.4%.High-response proportional directional control valves play a crucial role in improving the efficiency of hydrostatic power transmission systems in agricultural machinery. However, the rapid switching of these valves can generate undesirable transient phenomena in hydrostatic power transmission systems, thereby compromising overall system stability and energy efficiency. In this study, a comprehensive numerical analysis was performed to investigate the influence of spool displacement speed (2 and 20ms) and the curvature radius of spool lands (0, 2, 4 and 6µm) on the performance characteristics of a high-response proportional directional control valve under both steady-state and transient operating conditions. A three-dimensional computational fluid dynamics model was developed using a moving-mesh approach coupled with the k"-" ε turbulence model to capture the transient flow behavior accurately. To validate the numerical results, a hydraulic power transmission test bench was designed and fabricated to experimentally measure the valve's performance parameters. The comparison revealed that deviations between the numerical and experimental results were less than 5% under steady conditions and less than 6% under transient conditions. Furthermore, reducing the valve switching time from 20 to 2ms resulted in a 19.8% decrease in the average flow rate and a 29.8% increase in the required actuation force. Moreover, introducing a 2µm curvature radius at the spool edges improved the steady-state flow rate by 7.3% and reduced the actuation force by 9.2%. Under transient conditions, this geometric modification further enhanced the flow rate by 15.3% and reduced the required actuation force by 13.4%.https://ijbse.ut.ac.ir/article_106679_a330e3dd4e0822d1adbfbcb14c5fd512.pdfUniversity of Tehran PressIranian Journal of Biosystem Engineering2008-480357120260421Identification and Analysis of Suitable Optimization Models for Designing the Supply Chain of Marine Cage Aquaculture under UncertaintyIdentification and Analysis of Suitable Optimization Models for Designing the Supply Chain of Marine Cage Aquaculture under Uncertainty8710510669710.22059/ijbse.2026.408905.665634FAHamidSinisaz-ShahshahaniDepartment of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.MohammadSharifiDepartment of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, IranAsadollahAkramDepartment of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.MajidKhanaliDepartment of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, IranJournal Article20251229
Marine cage aquaculture along the southern coasts of Iran (Bushehr, Hormozgan, Khuzestan, and Sistan and Baluchestan) has experienced an annual growth rate of 15–20% in recent years and constitutes a key component of the national strategy to increase total aquaculture production to over 1.8 million tons. Hormozgan serves as the primary hub for marine species production; Bushehr produces approximately 14,000 tons with more than 20 active farms; Khuzestan targets 5,000 tons; and Sistan and Baluchestan benefits from the substantial potential of the Makran coast and the Oman Sea. Despite climatic constraints, infrastructural limitations, and market volatility, the sector’s high regional capacity and governmental support have positioned it as a strategic pillar of sustainable fisheries development in Iran. This study develops a scenario-based multi-objective mixed-integer linear programming (MILP) model to design the aquaculture supply chain under uncertainty. The model simultaneously addresses economic (minimization of total supply chain costs), social (maximization of sustainable employment), and environmental (reduction of fuel consumption and emissions) objectives. Uncertainty is incorporated through three scenarios—optimistic, moderate, and pessimistic. The model is implemented in Python using the PuLP library, and three solution approaches are compared: the ε-constraint method, the weighted-sum method, and robust optimization. Findings indicate that the weighted-sum approach provides the most practical and balanced solution, activating only the strategic node of Chabahar. This configuration yields a total supply chain cost of approximately 7,418,500 million IRR, generates 390,000 sustainable jobs, and results in energy consumption of 830,000 GJ. In contrast, the ε-constraint and robust optimization methods fail to produce feasible solutions due to rigid constraints and high sensitivity to pessimistic scenarios, respectively. Accordingly, the weighted-sum method is recommended as a flexible and context-appropriate approach for southern Iran. However, the relatively high energy consumption underscores the need to increase the environmental weight (w<sub>3</sub>=0.3) to enhance sustainability under uncertainty.
Marine cage aquaculture along the southern coasts of Iran (Bushehr, Hormozgan, Khuzestan, and Sistan and Baluchestan) has experienced an annual growth rate of 15–20% in recent years and constitutes a key component of the national strategy to increase total aquaculture production to over 1.8 million tons. Hormozgan serves as the primary hub for marine species production; Bushehr produces approximately 14,000 tons with more than 20 active farms; Khuzestan targets 5,000 tons; and Sistan and Baluchestan benefits from the substantial potential of the Makran coast and the Oman Sea. Despite climatic constraints, infrastructural limitations, and market volatility, the sector’s high regional capacity and governmental support have positioned it as a strategic pillar of sustainable fisheries development in Iran. This study develops a scenario-based multi-objective mixed-integer linear programming (MILP) model to design the aquaculture supply chain under uncertainty. The model simultaneously addresses economic (minimization of total supply chain costs), social (maximization of sustainable employment), and environmental (reduction of fuel consumption and emissions) objectives. Uncertainty is incorporated through three scenarios—optimistic, moderate, and pessimistic. The model is implemented in Python using the PuLP library, and three solution approaches are compared: the ε-constraint method, the weighted-sum method, and robust optimization. Findings indicate that the weighted-sum approach provides the most practical and balanced solution, activating only the strategic node of Chabahar. This configuration yields a total supply chain cost of approximately 7,418,500 million IRR, generates 390,000 sustainable jobs, and results in energy consumption of 830,000 GJ. In contrast, the ε-constraint and robust optimization methods fail to produce feasible solutions due to rigid constraints and high sensitivity to pessimistic scenarios, respectively. Accordingly, the weighted-sum method is recommended as a flexible and context-appropriate approach for southern Iran. However, the relatively high energy consumption underscores the need to increase the environmental weight (w<sub>3</sub>=0.3) to enhance sustainability under uncertainty.https://ijbse.ut.ac.ir/article_106697_51fc06a734fa27d867938319d5b12e0e.pdfUniversity of Tehran PressIranian Journal of Biosystem Engineering2008-480357120260421Simulation and Performance Analysis of the Solar Preheater of the Cogeneration Power Plant of the Sugarcane IndustrySimulation and Performance Analysis of the Solar Preheater of the Cogeneration Power Plant of the Sugarcane Industry10712810671310.22059/ijbse.2026.406402.665627FAAyoubKaabimofradDepartment of Mechanical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, IranAbbasAsakerehDepartment of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Iran, Ahvaz, IranEbrahimHajidavallooDepartment of Mechanical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, IranMostafaKiani Deh KianiDepartment of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, IranJournal Article20251116This research investigated the technical and environmental feasibility of a solar preheater at the Dehbal Khuzayi CHP plant. The goal was to reduce fossil fuel consumption and boost thermal efficiency by using solar energy for boiler feedwater preheating. Dynamic simulations were performed using TRNSYS software to evaluate and compare the thermal behavior of the system, including evacuated tube and parabolic trough collectors. Weather data and the technical characteristics of the base system were considered in the model, and the model’s validity was confirmed by matching its outputs with experimental data. he results showed that the ETC is capable of producing 26,519 GJ of thermal energy per hectare annually, while the PTC has the capacity to produce 16,239 GJ per hectare annually. The outlet temperature of both collector types is capable of reaching the system’s design temperature during peak solar radiation hours. From an environmental perspective, the use of solar collectors resulted in an annual reduction of 4,243 tons of CO₂-eq in the ETC and 3,096 tons of CO₂-eq in the PTC. The economic analysis showed that the ETC is more economical, with a payback period of 2.7 years and an internal rate of return of 31.9 percent. Overall, the results indicate the high efficiency of integrating solar energy into boiler feedwater preheating and its positive impact on reducing fuel consumption, improving thermal efficiency, and decreasing greenhouse gas emissions at the Dehbal Khuzayi power plant.This research investigated the technical and environmental feasibility of a solar preheater at the Dehbal Khuzayi CHP plant. The goal was to reduce fossil fuel consumption and boost thermal efficiency by using solar energy for boiler feedwater preheating. Dynamic simulations were performed using TRNSYS software to evaluate and compare the thermal behavior of the system, including evacuated tube and parabolic trough collectors. Weather data and the technical characteristics of the base system were considered in the model, and the model’s validity was confirmed by matching its outputs with experimental data. he results showed that the ETC is capable of producing 26,519 GJ of thermal energy per hectare annually, while the PTC has the capacity to produce 16,239 GJ per hectare annually. The outlet temperature of both collector types is capable of reaching the system’s design temperature during peak solar radiation hours. From an environmental perspective, the use of solar collectors resulted in an annual reduction of 4,243 tons of CO₂-eq in the ETC and 3,096 tons of CO₂-eq in the PTC. The economic analysis showed that the ETC is more economical, with a payback period of 2.7 years and an internal rate of return of 31.9 percent. Overall, the results indicate the high efficiency of integrating solar energy into boiler feedwater preheating and its positive impact on reducing fuel consumption, improving thermal efficiency, and decreasing greenhouse gas emissions at the Dehbal Khuzayi power plant.https://ijbse.ut.ac.ir/article_106713_c701283d7bf5e851ec1392d5c8618c93.pdf