Research Article-en
Precision Farming
F. Fatehi; H. Bagherpour; J. Amiri Parian
Articles in Press, Corrected Proof, Available Online from 31 May 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.88066.1249
Abstract
Manually picking the flowers of the Damask rose is significantly challenging due to the numerous thorns on its stems. Consequently, the accurate detection of bloomed Damask roses in open fields is crucial for designing a robot capable of automating the harvesting process. Considering the high speed and ...
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Manually picking the flowers of the Damask rose is significantly challenging due to the numerous thorns on its stems. Consequently, the accurate detection of bloomed Damask roses in open fields is crucial for designing a robot capable of automating the harvesting process. Considering the high speed and precise capabilities of deep convolutional neural networks (DCNN), the objective of this study is to investigate the effectiveness of the optimized YOLOv8s model in detecting bloomed Damask roses. To assess the impact of the YOLO model size on network performance, the precision and detection speed of other YOLO network versions, including v5s and v6s, were also examined. Images of Damask roses were taken under two lighting conditions: normal light conditions (from civil twilight to sunrise) and intense light conditions (from sunrise to 10 AM). The outcomes demonstrated that YOLOv8s exhibited the highest performance, with a mean average precision (mAP50) of 98% and a detection speed of 243.9 fps. This outperformed the mAP50 and detection speed of YOLOv5s and YOLOv6s networks by margins of 0.3%, 6.1%, 169.3 fps and 198.6 fps, respectively. Experimental results show that YOLOv8s performs better on images taken in normal lighting than on those taken in intense lighting. A decline of 5.2% in mAP50 and 2.4% in detection speed signifies the adverse influence of intense ambient light on the model's effectiveness. This research indicates that the real-time detector YOLOv8s provides a feasible solution for the identification of Damask rose and provides guidance for the detection of other similar plants.
Research Article-en
The relationship between machine and soil
T. A. Medhn; A. G. Levshin; S. G. Teklay
Articles in Press, Corrected Proof, Available Online from 30 December 2024
©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89995.1286
Abstract
The efficient use of agricultural machinery significantly improves both the quantity and quality of field operations; therefore, it is essential to optimize operational speed and field time. Factors such as field shape complexities and soil surface roughness (SSR) significantly impact seeding performance. ...
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The efficient use of agricultural machinery significantly improves both the quantity and quality of field operations; therefore, it is essential to optimize operational speed and field time. Factors such as field shape complexities and soil surface roughness (SSR) significantly impact seeding performance. The objective of this research was thus to evaluate how these key factors affect seeder performance: (1) field size and shape, and (2) the interaction of seeder speed and SSR. The performance metrics, effective field capacity (Feff), efficiency (η), and average working speed (va), were analyzed using SAS software. The convexity (Icon) and rectangularity (IR) indices for each plot were calculated using the ArcGIS minimal bounding geometry Data Management tool, while the elevation standard deviation (σe) was computed using Python. The resulting values for Feff, η, and va varied widely, with values ranging from 10.2 to 3.1 ha h-1, 30% to 65.7%, and 5.2 to 17 km h-1, respectively. A va process capability index (Cpk) of 0.22 indicates a significant challenge in meeting the established limits. As the plot run-length increased, the Feff also increased (R2 = 42%), while it decreased with a rising perimeter to area ratio (P/A) (R2 = 51%). Additionally, Feff exhibited an upward trend as the Icon and IR indices rose, while it experienced a decline with greater compactness (Icom) and square perimeter (Isp) indices; albeit these relationships were not statistically significant. Higher roughness levels generally resulted in a decline in η. Furthermore, operating the planter at higher speed on uneven terrain led to a significant decrease in efficiency. Hence, redesigning the plots to minimize border complexities, eliminating topographic abnormalities, and implementing tailored plot-specific pre-sowing procedures, will significantly enhance planter performance.
Research Article-en
Modeling
M. Rafiei; F. Khoshnam; M. Namjoo
Articles in Press, Corrected Proof, Available Online from 31 May 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.88417.1256
Abstract
In the current study, the modeling and optimization of various seedling growth and germination indices for parsley seeds were investigated. A lab-scale quadrupole magnetic field was developed, and experiments were conducted using a completely randomized factorial design with three replications. The factors ...
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In the current study, the modeling and optimization of various seedling growth and germination indices for parsley seeds were investigated. A lab-scale quadrupole magnetic field was developed, and experiments were conducted using a completely randomized factorial design with three replications. The factors considered were magnetic field intensity (150, 300, and 450 mT), exposure time (30, 60, and 90 minutes), and culture time (0, 7, and 14 days after applying the magnetic field). The results revealed that the magnetic field significantly affected shoot length, fresh root weight, and fresh shoot weight, while exposure time significantly impacted root length. Sowing day also significantly influenced root length and fresh root weight, along with other factors. Immediate sowings after magnetic field application enhanced root length, while sowing 14 days following the exposure increased shoot length, fresh root weight, and fresh shoot weight. A 30-minute exposure to magnetic field intensities of 150 to 300 mT did not significantly affect seedling growth parameters. However, higher field strengths of 450 mT for 60 to 90 minutes proved beneficial, leading to enhanced shoot length, fresh root weight, fresh shoot weight, germination rate, germination percentage, and reduced mean germination time. The analysis and optimization using Response Surface Methodology revealed that the optimal magnetization condition, with a desirability of 0.682, was achieved at a magnetic field of 450 mT, an exposure time of 60 minutes, and sown 14 days post-exposure. Higher magnetic fields appeared to enhance field durability and significantly impact seedling growth indices.
Research Article-en
Image Processing
I. Ahmadi
Articles in Press, Corrected Proof, Available Online from 31 May 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.88500.1258
Abstract
In the context of plant diseases, the selection of appropriate preventive measures, such as correct pesticide application, is only possible when plant diseases have been diagnosed quickly and accurately. In this study, a transfer learning model based on the pre-trained EfficientNet model was implemented ...
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In the context of plant diseases, the selection of appropriate preventive measures, such as correct pesticide application, is only possible when plant diseases have been diagnosed quickly and accurately. In this study, a transfer learning model based on the pre-trained EfficientNet model was implemented to detect and classify some diseases in tomato crops, using an augmented training dataset of 2340 images of tomato plants. The study's findings indicate that during the model's validation phase, the rate of image categorization was roughly 5 fps (frames per second), which makes sense for a deep learning model operating on a laptop computer equipped with a standard CPU. Furthermore, the model was learned well because increasing the number of epochs no longer improved its accuracy. After all, the curves of the train and test accuracies, as well as the losses versus epoch numbers, remained largely horizontal for epoch numbers greater than 20. Notably, the highest coefficient of variation across these four cases was only 7%. Furthermore, the cells of the primary diagonal of the confusion matrix were filled with larger numbers in comparison with the values of the other cells; precisely, 88.8%, 7.7%, and 3.3% of the remaining cells of the matrix (cells of the primary diagonal excluded) were filled with 0, 1, and 2, respectively. The model's performance metrics are: sensitivity 85%, specificity 98%, precision 86%, F1-score 84%, and accuracy 85%.
Research Article-en
Post-harvest technologies
C. N. Onwusiribe; J. Mbanasor; P. O. Nto; M. C. Ndukwu
Articles in Press, Corrected Proof, Available Online from 31 May 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89115.1267
Abstract
Rice is a major staple food consumed worldwide, but its processing has significant environmental impacts due to water and energy consumption and greenhouse gas emissions. As a result, rice producers are adopting sustainable processing techniques to reduce negative environmental impacts and increase profitability. ...
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Rice is a major staple food consumed worldwide, but its processing has significant environmental impacts due to water and energy consumption and greenhouse gas emissions. As a result, rice producers are adopting sustainable processing techniques to reduce negative environmental impacts and increase profitability. This study analyzed the sustainability of modern and traditional paddy rice processing techniques among smallholder rice farmers in Southeast Nigeria. The data was collected from 240 rice producers using statistical approaches such as descriptive statistics, sustainability indicator (Weight Assessment Ratio Analysis), and multinomial regression analysis. The results showed that 34.7% of rice farmers used modern processing techniques while 65.3% used traditional methods. Traditional milling produced substantial carbon emissions, according to 77% of small-scale farmers, while 68% rated noise pollution as high. 80-100% of small-scale farmers using modern techniques cared about the environment and wanted to reduce their gas emissions, solid waste, energy use, and water use. The sustainability index for farmers using traditional and modern processing techniques was affected by gender experience, labor size, investment, income, cost of production, understanding of climate change, and environmental sustainability. The study recommends using renewable energy sources to increase productivity and reduce environmental effects.
Research Article-en
The relationship between machine and soil
H. Asadollahi; B. Mohammadi-Alasti; A. Mardani; M. Abbasgholipour
Articles in Press, Corrected Proof, Available Online from 31 May 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89154.1269
Abstract
Understanding soil deformation dynamics is critical in various fields, such as off-road vehicle mobility, agriculture, and soil mechanics. In particular, evaluating soil-tire interactions is essential for optimizing energy consumption and minimizing the negative effects of soil compaction. This study ...
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Understanding soil deformation dynamics is critical in various fields, such as off-road vehicle mobility, agriculture, and soil mechanics. In particular, evaluating soil-tire interactions is essential for optimizing energy consumption and minimizing the negative effects of soil compaction. This study investigates the effect of soil deformation rates on the pressure-sinkage relationship and energy consumption using a controlled soil bin environment and a bevameter system. The primary objective of the study is to examine how different traffic levels and varying penetration rates influence the energy required to achieve specific sinkage depths. The study employed a completely randomized block design, with each treatment replicated three times to ensure precision and reliability. Quantitative measurements were obtained using a load cell attached to a bevameter, capturing the forces at a sampling frequency of 30 Hz. Results demonstrated a significant influence of both traffic level and penetration velocity on soil resistance and energy consumption. For the larger plate, the pressure required for penetration increased with higher velocities and traffic levels. At the highest velocity (45 mm s-1) and with 8 passes, the pressure needed for sinkage was maximal. The energy consumption for each scenario was calculated by integrating the area under the force-sinkage curve. The analysis of variance (ANOVA) revealed that the number of wheel passes, plate size, and penetration velocity significantly affected energy consumption. At the highest sinkage depth (60 mm), the energy consumption for the larger plate at 45 mm s-1 and with 8 passes was nearly double that of the smaller plate. These results emphasize the importance of considering both traffic-induced compaction and velocity when designing off-road vehicles or agricultural machinery that interact with deformable terrains.
Research Article-en
Image Processing
O. Doosti Irani; M. H. Aghkhani; M. R. Golzarian
Articles in Press, Corrected Proof, Available Online from 01 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2023.83054.1174
Abstract
Robotic harvesting in agriculture is an effective method for producing healthy fruit, reducing costs, and increasing productivity. Detecting and harvesting sweet peppers, however, remains a challenging task. This study aims to develop an unsupervised machine vision algorithm to recognize colored sweet ...
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Robotic harvesting in agriculture is an effective method for producing healthy fruit, reducing costs, and increasing productivity. Detecting and harvesting sweet peppers, however, remains a challenging task. This study aims to develop an unsupervised machine vision algorithm to recognize colored sweet peppers using a combination of geometric features (Fast Point Feature Histogram- FPFH) and color features (H, S, and V). Depth images were captured using a Kinect v2 sensor, and a 3D model was reconstructed. After extracting the geometric and color features, data preprocessing involved undersampling to ensure balance and applying the Z-score criterion to eliminate outliers. Principal component analysis (PCA) was used to reduce the feature dimensions, and the K-means clustering model was implemented to categorize the data using six geometric features and three color features. The silhouette coefficient was employed to evaluate clustering quality, and human evaluation demonsterated that the algorithm achieved a detection accuracy of 95.10% for sweet peppers.
Research Article-en
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
M. M. Naserian; R. Khodabakhshian
Articles in Press, Corrected Proof, Available Online from 01 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89307.1274
Abstract
The buildings and the agri-food sectors nearly consume 40% and 21% of the world's total energy, respectively. This research aims to combine these two significant energy-consuming sectors to decrease the total society’s energy consumption. For this purpose, a novel small-scale building integrated ...
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The buildings and the agri-food sectors nearly consume 40% and 21% of the world's total energy, respectively. This research aims to combine these two significant energy-consuming sectors to decrease the total society’s energy consumption. For this purpose, a novel small-scale building integrated agriculture system was designed and constructed. In this research, the total energy and water consumption, annual CO2 production, and the total cost of employing the novel system were analyzed from the building residents’ and social points of view. Moreover, the results were compared with the total results of a building and a separate standard greenhouse with the same product. The results show that the total energy reduction because of using the novel system was 31.2%. According to the results, the novel system will cause approximately 3400 kgCO2 emission reduction over a life cycle of 20 years. Moreover, yearly water consumption reduction was 19.2 L kg-1 of lettuce production. The payback period was approximately 5 years based on the cost analysis results comprising investment, operational, and social costs. Sensitivity and Scenarios analyses were conducted to better understand the effect of probable influential parameters and make the investment for the novel system secure and attractive.
Review Article-en
The relationship between machine and soil
S. Manoj Kumar; R. Karthikeyan; K. Thirukumaran; A. Senthil; P. Dhananchezhiyan
Articles in Press, Corrected Proof, Available Online from 02 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.87897.1247
Abstract
The traditional method of transplanting rice seedlings is labor-intensive, prompting a shift towards direct seeding of rice as an alternative crop establishment method. Direct seeding offers several advantages, including reduced labor requirements, timely sowing, and water conservation. Innovations in ...
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The traditional method of transplanting rice seedlings is labor-intensive, prompting a shift towards direct seeding of rice as an alternative crop establishment method. Direct seeding offers several advantages, including reduced labor requirements, timely sowing, and water conservation. Innovations in machinery have significantly enhanced the efficiency of direct-seeded rice cultivation, spanning advancements from land preparation to harvest. Techniques such as no-till methods and laser leveling promote efficient resource utilization and water conservation while minimizing soil disturbance. Specialized seeders and precision seed meters ensure accurate seed placement and uniform germination. Power-operated seeders and hand-held rotary dibblers further improve sowing efficiency. Modern irrigation systems, including drip irrigation, alternate wetting and drying, and automated soil moisture sensing, optimize water productivity. Weed management has advanced with mechanical, solar-powered, and autonomous weeding technologies. Additionally, crop mapping, variable rate technology, and unmanned aerial vehicles enable precise and site-specific weed control. Overall, modern machinery has transformed direct-seeded rice cultivation, resulting in increased input use efficiency, reduced labor demands, higher crop yields, and improved sustainability. Continued innovation offers significant potential for optimizing plant establishment, minimizing post-harvest losses, enhancing profitability, and conserving natural resources. This review article examines these advancements and their implications for the future of direct-seeded rice cultivation.
Review Article-en
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
M. Bamdad; M. Zangeneh; S. H. Peyman
Articles in Press, Corrected Proof, Available Online from 02 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89290.1273
Abstract
Agricultural cooperatives (ACs) play a vital role in the global agricultural sector, yet their success in food production and supply varies significantly across countries. This study presents a comprehensive review of existing literature on ACs using the PRISMA methodology and proposes a methodological ...
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Agricultural cooperatives (ACs) play a vital role in the global agricultural sector, yet their success in food production and supply varies significantly across countries. This study presents a comprehensive review of existing literature on ACs using the PRISMA methodology and proposes a methodological framework to guide future research. Each selected study was analyzed based on four key dimensions: purpose, methodology, factors examined, and key findings. These variables were then categorized to enable a more robust comparative analysis. The review highlights that the success of ACs is driven by effective management, strong marketing strategies, and a dedicated workforce. Education emerges as a critical factor, irrespective of age or gender. However, strategies for success differ among cooperatives, underscoring the need for context-specific research to accurately assess the status and needs of ACs in various regions.
Review Article-en
Precision Farming
S. Rishikesavan; P. Kannan; S. Pazhanivelan; R. Kumaraperumal; N. Sritharan; D. Muthumanickam; M. Mohamed Roshan Abu Firnass; B. Venkatesh
Articles in Press, Corrected Proof, Available Online from 22 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2024.89334.1276
Abstract
Drones have emerged as a promising technology in precision agriculture, supporting Sustainable Development Goals (SDGs) by enhancing sustainable farming practices, improving food security, and reducing environmental impact. This review article is intended to meticulously analyze the multiple applications ...
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Drones have emerged as a promising technology in precision agriculture, supporting Sustainable Development Goals (SDGs) by enhancing sustainable farming practices, improving food security, and reducing environmental impact. This review article is intended to meticulously analyze the multiple applications of drone technology in agriculture, such as crop health monitoring, pesticide and fertilizer spraying, weed control, and data-driven decision-making for farm optimization. It emphasizes the role of drones in precision spraying, promoting targeted interventions, and minimizing environmental impact compared to conventional methods. Drones play a vital role in weed management and crop health assessment. The paper focuses on the importance of data collected by drones to acquire the necessary information for decision-making concerning irrigation, fertilization, and overall farm management. However, using Unmanned Aerial Vehicles (UAVs) in agriculture faces challenges caused by batteries and their life, flight time, and connectivity issues, particularly in remote areas. There are legal challenges whereby regulatory frameworks and restrictions are present in different regions that affect the operation of drones. With the help of continuous research and development initiatives, the challenges depicted above could be solved, and the fullest potential of drones can be tapped for achieving Sustainable Agriculture.
Research Article
Design and Construction
H. Samimi akhijahani; M. S. Barghi Jahromi
Articles in Press, Accepted Manuscript, Available Online from 07 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.90199.1294
Abstract
IntroductionWalnut (Juglans regia L.) is a highly valued horticultural product, and significant efforts are underway to enhance its production in Iran. Despite the development of various tools aimed at increasing productivity and improving harvesting efficiency, over 90% of walnuts in Iran are still ...
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IntroductionWalnut (Juglans regia L.) is a highly valued horticultural product, and significant efforts are underway to enhance its production in Iran. Despite the development of various tools aimed at increasing productivity and improving harvesting efficiency, over 90% of walnuts in Iran are still harvested manually, often with the aid of specialized tools or by striking the trees with sticks. Although numerous mechanical devices have been introduced, the considerable height of walnut trees and the asynchronous ripening of the nuts continue to make traditional harvesting methods predominant. In this research, a novel walnut peeling system incorporating a horizontally rotating cutting plate was developed and evaluated. The cutting plate, designed with specific grooves and curvature, aims to enhance the mechanical efficiency of the peeling process. This analysis investigates the influence of rotational speed and groove depth on system performance. In addition, the life cycle assessment is conducted to evaluate the environmental and operational impacts of the proposed system, with comparative analysis against conventional peeling methods.Materials and MethodsThe designed and constructed system consists of three main parts: the container, the rotating disk, and the power system, which includes the electric motor. The rotating disk, as the heart of the system, is made from a 1.5 mm thick steel sheet with a diameter of 640 mm. It has been laser-cut with sufficient precision to cut and transfer walnuts. The third part of the system is the power unit, which includes a 3-hp, 1400 rpm electric motor. Power transmission is carried out using a V-shaped belt. In this system, the product is first collected from the designated garden and stored in equally weighted bags. The rotating plate is the most important component of the walnut peeler, essentially the heart of the system. On this plate, there are 12 oval grooves, each 5 mm in diameter and 150 mm in length. One side of each groove is raised, with a depth that can be varied. Increasing the groove depth increases the amount of peel removed and exposes a larger surface of the walnut. The plate is connected to the driven pulley and then to the electric motor via a shaft. In this research, a life cycle assessment was also used to evaluate the impact of various parameters of the walnut peeling system on the environment and its pollution level.Results and DiscussionThe findings from the variance analysis regarding the impact of groove depth and rotation speed on peeling percentage indicate that variations in plate groove depth and electric motor rotation speed during walnut peeling are significant at the 1% level. Furthermore, the impact of changes in the groove depth of the cutting plate on machine performance and the reduction of walnut losses is substantial, showing significance at the 1% probability level. The effect of this factor on the amount of damage to walnuts is significant at the 5% level. By increasing the groove depth from 1.5 to 3 mm and from 3 to 5 mm, changes of 6.99% and 5.12% in walnut skin removal were observed. By reducing the elevation of the groove, the amount of cutting removed from the walnut surface is also reduced, and the peeling process becomes more abrasive. In this case, for proper peeling, the cycle duration and retention time in the machine should be increased. By increasing the rotational speed from 218 to 275 rpm, the momentum and linear velocity increase, resulting in more green shell removal. Conversely, reducing the rotational speed decreases the impact, leaving more green skin on the product. The interaction between rotational speed and groove depth is also significant in the amount of peeled product at the 1% level. The results of the life cycle assessment showed that the human health index has the highest value due to the use of electric power, iron profile (in the system chassis and container), and copper wire in the electric motor armature. Optimizing the system and using clean energy can help improve system efficiency and reduce environmental impact.ConclusionUtilizing a walnut peeling machine achieves an impressive 94% efficiency in walnut peeling while ensuring less than 5% damage. The results of the life cycle assessment showed that the use of a walnut peeling machine has less environmental damage than the traditional method and is highly cost-effective.
Research Article
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
M. Bamdad; M. Zangeneh; S. H. Peyman
Articles in Press, Accepted Manuscript, Available Online from 21 April 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89685.1280
Abstract
IntroductionThe cooperative system for agricultural mechanization services holds significant potential to boost agricultural production. Key benefits include providing services during crop cultivation to reduce labor demands, delivering centralized and specialized services to lower production costs, ...
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IntroductionThe cooperative system for agricultural mechanization services holds significant potential to boost agricultural production. Key benefits include providing services during crop cultivation to reduce labor demands, delivering centralized and specialized services to lower production costs, facilitating the adoption of new technologies, and improving productivity in agricultural processes and supply chains. However, in Gilan Province, Iran, over 198 of the 260 registered mechanization service cooperatives, approximately 76%, are currently inactive. This significant decline highlights an urgent need to assess the performance of the mechanization service system to ensure its sustainability. Therefore, this study aims to identify the main challenges underlying the inactivity of these cooperatives in Gilan Province.Materials and MethodsThis study aims to evaluate the performance of mechanization service cooperatives in Gilan Province. To achieve this objective, a combined methodology incorporating Delphi methods, hierarchical analysis process, and the SWOT (strengths, weaknesses, opportunities, and threats) analysis was employed. Initially, factors influencing the performance of agricultural service cooperatives were identified through a review of existing literature concerning the performance pathology of agricultural cooperatives, as well as the specific factors impacting mechanization cooperatives and the associated challenges they face. The Delphi method was utilized to align the identified factors with the operational conditions of agricultural mechanization service cooperatives in Gilan Province. The Delphi process was conducted over three rounds, culminating in the identification and prioritization of the primary factors. Subsequently, the SWOT matrix was applied to assess the strengths, weaknesses, opportunities, and threats related to the mechanization service cooperatives, with input from a panel of experts for ranking purposes. Ultimately, strategies to address the performance challenges were developed based on the SWOT results and prioritized using AHP.Results and DiscussionThe findings of this research indicate that the lack of capital in the cooperative company, coupled with financial and credit difficulties, insufficient tools and equipment needed for generating income for members, stringent bank policies regarding the provision of financial aid, and the presence of discrepancies in the selection of cooperative members constitute the primary obstacles faced by these companies. The most important recommended strategies are as follows: Leverage internal investment from cooperative members. Attract capital from entrepreneurs. Organize tours to visit successful cooperatives for information exchange and learning. Reduce service fees. Increase access to financial assistance. Lower guarantee requirements for newly established cooperatives and entrepreneurs seeking financial supportConclusionIn this study, a comprehensive review of existing literature was conducted to identify the challenges affecting cooperative performance. These challenges were categorized into six main groups: financial, operational, organizational, structural, social, and environmental. The Delphi method, involving a panel of nine field experts, was used to evaluate these issues. Additionally, a SWOT analysis, based on previous research, was carried out to assess the strengths, weaknesses, opportunities, and threats related to cooperatives. To determine the relative importance of each challenge, a hierarchical analysis was performed to rank them accordingly.The results revealed that the most pressing challenges are primarily financial or have a significant financial impact on cooperative operations. Key issues include strict bank loan requirements, internal financial and credit difficulties, limited capital resources, and a lack of necessary tools and equipment to generate income for members. Moreover, the member selection process was identified as a critical concern, as it can lead to reduced motivation and inadequate fulfillment of responsibilities among cooperative members.
Research Article
Precision Farming
N. Salehi Babamiri; H. Haji Agha Alizadeh; M. Dowlati
Abstract
IntroductionSoil surface roughness is an important factor in determining the intensity and quality of tillage operations, and obtaining accurate information essential for precision tillage. Using an inappropriate technique due to the lack of precise discrepancy detection can lead to increased time spent ...
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IntroductionSoil surface roughness is an important factor in determining the intensity and quality of tillage operations, and obtaining accurate information essential for precision tillage. Using an inappropriate technique due to the lack of precise discrepancy detection can lead to increased time spent on analysis and potential damage. Generally, there are two methods for measuring soil surface roughness: contact and non-contact. Contact methods are less accurate for measuring the roughness of soft soil because they involve physical contact, which can partially disturb the soil. Most non-contact measurement methods are also performed in stop-and-go conditions, which increases measurement time and related analysis. The aim of this study is to measure soil surface roughness in real-time using optical sensors in the field. The accuracy and precision of two non-contact measurement methods will be compared to determine the best approach for precision tillage operations.Materials and MethodsIn the current research, a real-time soil surface roughness measurement system consisting of mechanical and electrical modules, data collection, and processing was built. The system performance was evaluated at different forward speeds and roughness categories, with two types of infrared and laser sensors. To assess the sensors’ accuracy, the collected data was compared against the pin gauge method, which served as the reference standard. The method exhibiting the least variation from this reference is considered to provide the most reliable data. Also, to further examine the accuracy of the sensors, the roughness data obtained from the sensor at various frequencies was compared against the roughness data obtained from the pin measuring device at the same level, resulting in a suitable curve plot. The interpretation of the obtained mathematical relationship indicates the precision of the sensor data.Results and DiscussionThe results obtained from the optical sensors were compared to the pin meter, used as the reference method, in both stationary and moving conditions. It was demonstrated that the optical sensors detect distance in the static state similarly to the reference pin meter. The calibration curve interpretation factor was 0.99 for the infrared sensor and 1 for the laser sensor, indicating a strong correlation between the sensor signals and their distance from the soil surface. The random roughness index was significant for different roughness classes at the 1% probability level, showing that this index effectively distinguishes between the resulting roughness classes. Analysis of variance results revealed that the measurement method had a significant effect at the 1% level. The method with the smallest difference from the reference method is considered the most appropriate measurement technique. The effect of forward speed was also significant at the 1% level; the speed at which the sensor’s performance did not significantly differ from the reference method was identified as the optimal speed for the system. Additionally, the effect of roughness class was significant at the 1% level, confirming that the created roughness classes had meaningful differences. The results of the sensor accuracy evaluation showed that the data obtained from the laser sensor at speeds of 1 and 2.6 km h-1 had no significant difference with the reference method. Therefore, it is appropriate to use the laser sensor at speeds of 1 and 2.6 km h-1. At speeds higher than 3.5 km h-1, the laser sensor successfully detected smooth surfaces, but did not correctly distinguish uneven surfaces. In general, the laser sensor was able to detect all categories of roughness at a speed of 2.6 km h-1. One reason the laser sensor did not perform well at speeds above 2.6 km h-1 was its low data acquisition rate. By using laser sensors with a higher data collection rate, the soil height profile can be plotted similarly to a pin scale. The infrared sensor was successful only in detecting smooth surfaces but failed to detect other types of surfaces.ConclusionDue to limited accuracy and the risk of damaging or altering the surface roughness, the contact method is not recommended for use on soft soil surfaces. Among non-contact methods, the most suitable technique is the one that provides the highest accuracy and precision while minimizing cost and time for data collection and analysis. In this study, two types of sensors including laser and infrared ranging were selected based on their reasonable price, ease of operation, compatibility with a mobile system, and ability to deliver real-time roughness measurements in the shortest possible time. The results demonstrated that real-time measurement of soil surface roughness can effectively replace traditional, tedious, and time-consuming methods.
Research Article
Bioenergy
B. Dosti; A. Asakereh
Articles in Press, Accepted Manuscript, Available Online from 07 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.91098.1319
Abstract
IntroductionProper lighting and safety equipment on roads are essential for the optimal use of roadside services and the timely, safe transportation of goods. Supplying electricity for road lighting, especially in remote and hard-to-reach areas via the power grid, involves high costs for building power ...
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IntroductionProper lighting and safety equipment on roads are essential for the optimal use of roadside services and the timely, safe transportation of goods. Supplying electricity for road lighting, especially in remote and hard-to-reach areas via the power grid, involves high costs for building power transmission infrastructure. Using renewable energy enables electricity generation directly at the point of use and on a local scale. This approach reduces transmission and distribution costs and significantly lowers the environmental impact associated with fossil fuel-based electricity generation. Kermanshah province plays a key role in road transportation, yet most of its roads lack lighting systems. The province has significant wind energy potential, but wind power has not been utilized to supply electricity for road lighting. This suggests that installing small-scale wind turbines along the roads could be a promising solution. This study aims to assess the wind energy potential for powering road lighting and to prioritize the counties of Kermanshah province for installing small-scale wind turbines to supply electricity to road lighting systems.Materials and MethodsThe main steps of the study include data collection, preparation of the wind atlas, identification of locations with high wind potential, determination of effective factors and indicators for siting wind turbines, weighting of these factors and indicators, scoring counties based on them, and finally ranking the counties for installing wind turbines to supply electricity for the road lighting system using multi-criteria decision-making models. Using the wind atlas, we evaluated wind energy potential within a 3 km buffer zone around roads and identified 46 points with high wind potential. Based on these points, the counties of Kermanshah province were assessed and ranked for installing small-scale turbines to power the road lighting system. The indicators considered to determine suitable turbine locations included wind energy potential, distance from roads, traffic volume, distance from high-voltage power lines, distance from protected areas, distance from rivers and flood-prone zones, distance from faults, distance from residential areas, and land slope. Counties were scored on these indicators based on previous studies and expert opinions. A decision-making matrix was created using these scores, and indicator weights were calculated using Shannon entropy combined with expert evaluation. The SAW, TOPSIS, ELECTRE, and VIKOR methods were then applied to rank and prioritize the counties.Results and DiscussionThe energy potential of wind, with a weight of 0.360, was the most important indicator for selecting locations for wind turbine installation and road lighting systems. Traffic and distance from the road were the next most significant factors, with weights of 0.228 and 0.151, respectively. Kermanshah County had the highest wind energy potential, featuring seven high-potential sites, while Sarpole Zahab and Qasr Shirin counties each had only one suitable site, indicating lower wind potential. The top three counties in terms of wind energy potential were Kermanshah, Ravansar, and Paveh. Kermanshah County also had the highest traffic volume, carrying the greatest weight in that category. For distance from the road, Sanghar and Sahneh ranked first and second, with unscaled weights of 0.094 and 0.070, respectively, and Kermanshah ranked third with 0.047. Kermanshah County scored highest on all indicators except distance from faults and protected areas. Across all decision-making methods, Kermanshah and Sanghar consistently ranked first and second. Overall, Kermanshah, Sanghar, and Ravansar were prioritized as the top three counties for installing wind turbines to supply electricity for road lighting systems.ConclusionAccording to the wind atlas, 46 points with suitable wind potential for the road lighting system were determined. Based on multi-criteria decision-making methods, Kermanshah, Sanghar, and Ravansar counties were prioritized for installing road lighting systems powered by wind turbines.Acknowledgement The authors would like to thank Shahid Chamran University of Ahvaz and its Vice Chancellor for Research and Technology for their financial support in the form of funding (SCU.AA1400.29747).
Research Article
Precision Farming
M. Safaeinezhd; M. Ghasemi-Nejad Raeini; M. Taki
Abstract
IntroductionOne of the key structural factors in agricultural mechanization is the selection of appropriate technology. Today, examining the effects of technology application and development on agricultural production remains of highly importance. Innovative technologies, such as spraying drones, play ...
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IntroductionOne of the key structural factors in agricultural mechanization is the selection of appropriate technology. Today, examining the effects of technology application and development on agricultural production remains of highly importance. Innovative technologies, such as spraying drones, play a critical role in advancing agriculture and ensuring food security. Without these technologies and proper input management, environmental impacts are likely to intensify. Achieving sustainable production and ensuring food security is a major challenge for researchers and global policymakers. This study evaluates and compares the performance of spraying drones and boom sprayers in controlling weeds and yellow rust disease in wheat fields. The aim of this study is to optimize pesticide use and achieve sustainable agriculture.Materials and MethodsThis research was conducted to evaluate the field performance and economic feasibility of using spraying drones compared to boom sprayers for controlling weeds and yellow rust disease in wheat fields. Experiments were carried out in regional Khorramabad, Iran, using a DJI Agras MG-1P spraying drone and a 400-liter 400B8 TF boom sprayer. The aim was to investigate the impact of modern technology, specifically spraying drones, compared to traditional methods, such as boom sprayers, for managing weeds and yellow rust disease. Additionally, the study assessed the profitability of these technologies. The experiments followed a randomized complete block design with three treatments: boom sprayer, spraying drone, and control. They were conducted in two separate, independent fields to examine treatment effects on weeds and yellow rust in wheat. For weeds control, 2-4-D herbicide was applied at 1.5 L ha-1, and for yellow rust control, Tilt fungicide was used at 0.5 L ha-1.Results and DiscussionResults showed that the deposition rate of pesticides in boom sprayers (82.8%) was higher than with drone spraying (69.9%). Furthermore, the average dry weight of weeds in boom sprayer was 172 g m-2, and in drone spraying, it was 163 g m-2, which was not statistically significant. Additionally, the average weed density was 25 plants per square meter for boom sprayers and 29.3 plants per square meter for drone spraying, with no statistically significant difference. The average harvest index in weed control experiments was 44% for boom sprayer and 41% for drone spraying, which was statistically significant at the 1% level. The average severity of yellow rust infection in wheat fields was 30.7% for boom sprayer and 25.3% for drone spraying, which was not statistically significant at the 1% level, but both treatments were significantly different from the control (68.3%). The harvest index in yellow rust experiments was better in drone spraying (43.8%) compared to boom sprayer (41.9%). The total annual cost for drone owners in the studied region (2980.3 million rials) was higher than the total cost for boom sprayer owners (513.48 million rials). However, the benefit-cost ratio for drone owners (1.215) exceeded that of boom sprayer owners (1.030), demonstrating economic viability for both sprayers. Overall, drones are found to be more economical for spraying than boom sprayers due to their higher efficiency and profitability. The use of drones can significantly increase the efficiency and profitability of spraying operations.ConclusionThe results of this study showed that both drone and boom sprayer were effective in reducing the dry weight of weeds, but there was no statistically significant difference between them. Weed density was higher with drone spraying, and the harvest index was better with drone spraying compared to boom sprayer. The costs of using drones were higher than boom sprayers, but despite the higher costs, drones are superior option for spraying due to their increased efficiency and profitability.
Research Article
Design and Construction
A. Sadin; M. H. Aghkhani; M. A. Ebrahimi-Nik; J. Baradaran Motie
Articles in Press, Accepted Manuscript, Available Online from 08 March 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2023.84424.1190
Abstract
IntroductionPlanting rice seedlings in the main field followed by periodic or intermittent irrigation is often considered a form of dry farming. Research suggests that flood irrigation in rice cultivation is primarily favored by farmers for its ability to control weeds and ensure a reliable water supply, ...
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IntroductionPlanting rice seedlings in the main field followed by periodic or intermittent irrigation is often considered a form of dry farming. Research suggests that flood irrigation in rice cultivation is primarily favored by farmers for its ability to control weeds and ensure a reliable water supply, rather than necessarily enhancing rice quality or yield. Depending on the rice variety, intermittent irrigation can sometimes improve both the quality and yield per unit area. The transplanting process in this method can be carried out manually without machinery or through mechanized methods using a planter.Materials and MethodsConventional rice transplanters designed for use in flooded land are not suitable for transplanting in dry land farming due to technical constraints. Therefore, it is necessary to develop a specialized rice transplanter tailored for such soil condition. This transplanter encompasses essential components, including a furrow opener, coverer, seedling storage tank or tray, seedling mechanism (distributor), seedling transfer mechanism (seedling transport piston), end separator for seedlings in the soil, power transmission system, depth adjustment shoe, and main and sub chassis. To evaluate the planter's performance, various parameters were assessed, including the percentage of lost plants, the average vertical angle of plant orientation, the average spacing between plants in the crop row, and the average number of seedlings per plant. Moreover, a factorial randomized block design was employed, with three replications for each level of the independent variables. The independent variables were forward speed (X1) at three levels of 0.25, 0.5, and 1 m s-1, planting depth (X2) at three levels of 4, 8, and 12 cm, and the size of the outlet opening of the seedling tray (X3) in three levels of 10, 15, and 20 mm.Results and DiscussionThe developed single-row planter features key specifications, including a working width of 250 mm, a power requirement of 0.57 kW, a theoretical field capacity of 0.06 ha h-1, and a field efficiency of 66.67%. The research findings revealed that forward speed, planting depth, and outlet opening size, along with their interactions, significantly impact the percentage of lost plants at the 99% confidence level. Among the three levels of forward speed (X1), the best speed level is 0.25 m s-1, as it results in the lowest percentage of lost seedlings. As the forward speed increases, the percentage of lost seedlings increases. The lowest percentage of lost plants (Y1) occurs at the planting depth of 8 cm and an outlet opening size of 20 mm. Furthermore, forward speed, planting depth, and their interaction have a noteworthy influence on the vertical angle of plants are established, at the 99% confidence level. With the increase of forward speed and planting depth, the average vertical angle of seedling establishment deviates from the vertical position. The forward speed of 0.25 meters per second and the planting depth of 8 cm show the best results for the establishment of seedlings. The sole factor affecting the spacing between plants in the row is the forward speed. The size of seedling tray’s outlet opening significantly affects the number of seedlings per plant at the 99% confidence level, while planting depth affects it at the 95% confidence level.ConclusionGiven the recent water crisis, adopting the dry rice farming method and using transplanters offers a viable solution for managing and conserving water in agriculture. Implementing dry planting with a custom-made transplanter yields several benefits, including reduced water consumption, lower cultivation costs, improved soil aeration, increased efficiency, and simplified planting processes. Utilizing this transplanter is an effective strategy to decrease both the time and expenses related to transplanting, while also mechanizing rice planting in dry fields.
Research Article
Nanotechnology (packaging films, biocomposites, solar cells)
N. Tajari; H. Sadrnia; F. Hosseini
Articles in Press, Accepted Manuscript, Available Online from 08 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.90838.1316
Abstract
Polylactic acid (PLA) is a thermoplastic, biodegradable, and bioactive polymer obtained from renewable resources such as beets and potatoes. PLA is regarded as a polymer that is nearly brittle, which can restrict its applications in the packaging industry. The mechanical properties of this polymer can ...
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Polylactic acid (PLA) is a thermoplastic, biodegradable, and bioactive polymer obtained from renewable resources such as beets and potatoes. PLA is regarded as a polymer that is nearly brittle, which can restrict its applications in the packaging industry. The mechanical properties of this polymer can be improved by adding nanoparticles and plasticizers. In this research, zinc oxide nanoparticles (1 wt% of PLA), Polyethylene glycol 400 (20 wt% of PLA), and Polysorbate 80 (0.25 wt% of the solution) were used to improve the mechanical properties of PLA films. The effects of these materials on the films were measured at two time points: the first month and the tenth month, with the aim of investigating physical aging, a precursor to polymer degradation. Statistical analysis was performed on the mechanical properties measured during these periods to identify significant differences between the produced films. Results showed that the highest tensile strength (82.99± 1.90 MPa, neat PLA), elongation at break (76.82± 27.22 %, PLA/PEG/ZnO), toughness (20.13± 7.89 J cm-3, PLA/PEG/ZnO), and Young's modulus (2.74± 0.10 GPa, neat PLA) were observed in the first month. Analysis of variance results regarding the effect of time on each film revealed that in most cases, the mechanical properties did not change significantly after ten months. Based on the stress-strain curves, it was found that the neat PLA film is among the resistant materials. The PLA/Polysorbate/ZnO film exhibited brittle behavior in the tenth month. The remaining samples exhibited characteristics that fell between resistant and ductile materials in both the first and tenth months.
Short Article- en
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
T. T. Truong; J. Selassie Nortey; T. H. Nguyen
Articles in Press, Accepted Manuscript, Available Online from 21 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2024.89769.1281
Abstract
As a growing global concern, water and climate changes have had a notable influence on agriculture. The main factor of this issue is food security, particularly in terms of food production and food pricing. This study investigates how climate change affects food security in Vietnam and Ghana, where agriculture ...
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As a growing global concern, water and climate changes have had a notable influence on agriculture. The main factor of this issue is food security, particularly in terms of food production and food pricing. This study investigates how climate change affects food security in Vietnam and Ghana, where agriculture is essential to socio-economic growth. The main study methodologies include ethnographic techniques and in-depth interviews with 50 farmers in each nation; 100 farmers in total. Results show that agricultural production and farmer health in these areas are highly vulnerable to increasing temperatures and erratic precipitation patterns. Vietnamese farmers mainly face flooding, sea-level rise, and saltwater intrusion, which endangers rice production, whereas Ghanaian farmers are more susceptible to droughts, which limit the amount of water available for rain-fed agriculture. Food security necessitates a change to alternate, robust crop types and improvements in agricultural technologies to counter these risks. The study highlights the need for adaptive measures such as enhanced irrigation systems, drought-resistant seeds, and early-warning systems for severe weather. These insights can help governments, agricultural stakeholders, and consumers develop policies and practices that improve food quality and stability, supporting sustainable agriculture.
Research Article-en
Modeling
E. Elena Vivanco-Cuba; D. Vivanco-Pezantes
Articles in Press, Accepted Manuscript, Available Online from 21 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.89911.1283
Abstract
Seaweeds are well known for their technological, nutritional, and health values, and their preservation by drying is essential to stabilize and maintain the quality of the product during storage. The research presents the obtaining of mathematical models in polynomial functions using the response surface ...
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Seaweeds are well known for their technological, nutritional, and health values, and their preservation by drying is essential to stabilize and maintain the quality of the product during storage. The research presents the obtaining of mathematical models in polynomial functions using the response surface methodology. The influence of the independent drying variables was studied: load density (1.70-15 kg m-2), incandescent lamp wattage (0-500 W), temperature (30-70 °C) and air velocity (0.5-2.5 m s-1) on the response variables: global acceptance (--), total phenolic content (mg GAC/100 gdb) and drying time (min). The study also showed that the conditions of temperature and incandescent lamp wattage during drying significantly affected the total phenolic content. The optimum conditions were: load density 9.13 kg m-2, incandescent lamp wattage 374.5 W, temperature and drying air velocity of 63.3 °C and 1.88 m s-1, respectively. The results show that increasing the power of the incandescent lamps leads to a shorter drying time of approximately 40-45%. For these optimized conditions, mathematical models were applied to simulate the drying curve and kinetics of the material studied. Using the Quasi-Newton Simplex method, the models of Midilli et al. and Page in second place, achieved a better performance in the quality of fit of the curves to the experimental data. Under these conditions, the value of the effective diffusivity of water was of the order of 2.03×10-11 m2 s-1, a value very similar to those published for agro-industrial products. The information obtained can be of great help in the use of the obtained parameters and applied techniques for the development of equipment and process control in the drying of red seaweed.
Research Article-en
Design and Construction
S. K. Busse; T. K. Hurisa; E. A. Esleman
Articles in Press, Accepted Manuscript, Available Online from 21 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.90012.1288
Abstract
Efficient control of agricultural machinery is crucial in sugar plants for maintaining product quality, managing operational costs, and improving productivity. The Ethiopian sugar industry is vital to the country's economy; however, issues with machinery management can lead to higher maintenance costs ...
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Efficient control of agricultural machinery is crucial in sugar plants for maintaining product quality, managing operational costs, and improving productivity. The Ethiopian sugar industry is vital to the country's economy; however, issues with machinery management can lead to higher maintenance costs and poor operational efficiency. This study aims to evaluate the agricultural machinery management system at the Arjo Diddessa sugar factory and optimize operational costs. Between 2016 and 2022, data were collected through surveys, interviews, and observations. To improve machinery running costs, a linear programming model was studied using Linear Interactive and Discrete Optimizer )LINDO( software. The findings revealed that 49% of non-operational machinery required minor repair, whereas 14% required disposal. The anticipated work rate exceeded the actual rate by 35.33%. Among the tasks, uprooting exhibited the smallest variance at 5.73%, while inter-row cultivation displayed the greatest discrepancy at 67.21%. Initial repair expenses were minimal but increased as the equipment aged. The optimization model achieved a maximum reduction of 10.60% in operational costs during 2021-22, highlighting the importance of accurate machinery work rate estimation and performance analysis for enhancing efficiency. The study identified critical inefficiencies in machinery management and emphasized the need for robust maintenance systems and strategic replacement plans for aging equipment. Optimizing operational efficiency is essential for improving productivity and reducing costs in sugar production processes.
Research Article-en
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
B. Mohammadi; A. R. Yousefi; M. Namdari; M. Heydari
Articles in Press, Accepted Manuscript, Available Online from 21 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.91522.1329
Abstract
This study evaluates the energy consumption and economic performance of three different weed control methods employed in olive orchards in Tarom County, Zanjan Province, Iran, with an emphasis on sustainable agriculture. The objective is to assess the energy efficiency and cost-effectiveness of different ...
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This study evaluates the energy consumption and economic performance of three different weed control methods employed in olive orchards in Tarom County, Zanjan Province, Iran, with an emphasis on sustainable agriculture. The objective is to assess the energy efficiency and cost-effectiveness of different weed management systems. The analysis includes chemical weed control (System I), mechanical control (System II), and integrated weed management (System III). Data were collected through interviews with 50 olive farmers, supplemented by official agricultural records. Results show that total energy consumption was highest in System III (93,069.16 MJ ha-1), and lowest in System I (64,297.16 MJ ha-1). System I also demonstrated superior energy efficiency (0.74), output energy (47,648.40 MJ ha-1), and energy productivity (0.06 kg MJ-1), making it the most viable option for optimizing energy consumption. Economically, System I generated the highest net profit (4,662.28 $ ha-1) and benefit-cost ratio (2.66), outperforming Systems II (3,073.31 $ ha-1; BCR: 2.16) and III (2,953.57 $ ha-1; BCR: 1.97). The study concludes that System I, with its efficient use of renewable energy, is the most viable option in terms of both energy and economic performance, providing a balance between low energy input and high yield, thus maximizing profits and minimizing production costs. These findings emphasize the importance of selecting appropriate weed control methods to optimize energy use and reduce overall production costs in olive cultivation.
Research Article-en
J. Allahnouri; A. Marzban; M. Ghasemi-Nejad Raeini; M. Rahnama; M. Savari
Articles in Press, Accepted Manuscript, Available Online from 21 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2025.91786.1336
Abstract
Agriculture is the most prominent industry in developing countries and also ranks as one of the most dangerous professions. Tractors and grain combine harvesters are two of the main self-propelled agricultural machines. Agricultural machines, despite their irreplaceable role in increasing productivity, ...
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Agriculture is the most prominent industry in developing countries and also ranks as one of the most dangerous professions. Tractors and grain combine harvesters are two of the main self-propelled agricultural machines. Agricultural machines, despite their irreplaceable role in increasing productivity, contribute significantly to agricultural accidents. This study was conducted to investigate the current rates and severity of accidents and human casualties related to agricultural tractors and grain combine harvesters in Ilam province, Iran. Evaluations were conducted using data from the years 2019-2023.Over these five years, the accident frequency for agricultural combines and tractors was 61 and 43, respectively, indicating a statistically significant difference. Among the tractor drivers in this research, the most frequent accidents occurred due to the power take-off shaft (P.T.O.), helices, and feeding rollers. Among combine drivers, accidents were most common at the shear points of the machine (cutter bars, gears, etc.). This research evaluated the factors affecting field accidents related to tractors and combines and estimated the accident rates. Accident rates, including AFR (Accident Frequency Rate), ASR (Accident Severity Rate), FIR (Fatal Incident Rate), and FSI (Frequent Severity Index), were calculated. The rates of AFR, ASR, FIR, and FSI were 25.84, 45.82, 1.66, and 1.066% for combine harvesters, and 5.60, 12.63, 4.44, and 0.262% for tractor accidents, respectively. The nonfatal rate for combine harvesters was 6445 per 100,000, and for agricultural tractors, it was 4334 per 100,000. Tractor accidents had a higher fatality rate than combine harvesters, with 445 fatalities per 100,000 for tractors compared to 333 per 100,000 for combine harvesters.
Research Article-en
Design and Construction
B. Adugna; K. Purushottam Kolhe; M. Gutu
Articles in Press, Accepted Manuscript, Available Online from 21 June 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2025.91751.1334
Abstract
This research aimed to enhance the design and functionality of an integrated enset processing machine by focusing on key components such as the shaft, cylinder drum, breastplate, and drum blade. Existing enset processing machines suffer from inefficiencies due to component wear, mechanical breakdowns, ...
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This research aimed to enhance the design and functionality of an integrated enset processing machine by focusing on key components such as the shaft, cylinder drum, breastplate, and drum blade. Existing enset processing machines suffer from inefficiencies due to component wear, mechanical breakdowns, and suboptimal design, leading to operational challenges. To address these issues, targeted design modifications were planned for the machine’s components. The materials for these components were selected according to ASTM standards. The modified components were rigorously analyzed using the Finite Element Method in the Workbench module of ANSYS 2023 R1 software at Adama Science and Technology University, Adama, Ethiopia. The study reported maximum stresses of 120 MPa, 250 MPa, 400 MPa, and 260 MPa, and minimum stresses of 30 MPa, 70 MPa, 120 MPa, and 80 MPa for the shaft, cylinder drum, blade, and breastplate, respectively. Maximum deformations were found to be 0.15 mm, 0.3 mm, 0.55 mm, and 0.35 mm for these components, with a maximum safety factor of 15 for all. These results indicate that the modifications provide safe working conditions. The design ensures that the drum, drum blade, and breastplate possess sufficient rigidity to withstand operational forces, with minimal deformation (2.39×10⁻⁶ mm for the drum blade), remaining within a safety factor limit of 1.25. Additionally, the machine demonstrated excellent energy dissipation and vibrational response, indicating structural robustness.
Research Article-en
Design and Construction
Gh. Ahmadzade; M. R. Maleki; P. Salami; K. Mollazade
Articles in Press, Accepted Manuscript, Available Online from 07 July 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.92546.1353
Abstract
Grain harvesting operations account for approximately 25-30% of total direct energy consumption in crop production systems. Developing appropriate blades for harvesting canola (Brassica napus L.) is crucial due to its distinct characteristics compared to other cereal grains. This study investigated the ...
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Grain harvesting operations account for approximately 25-30% of total direct energy consumption in crop production systems. Developing appropriate blades for harvesting canola (Brassica napus L.) is crucial due to its distinct characteristics compared to other cereal grains. This study investigated the effects of blade angles (placement angles: 30°, 45°, and 60°; sharpness angles: 30°, 45°, and 60°), reciprocating movement speed (800, 1100, and 1400 courses per minute), and moisture levels (19%, 22%, and 24%) on reducing force, shear stress, and energy consumption during canola harvesting. Results showed that a blade sharpness angle of 30° yielded the lowest shear stress (0.175 N mm-2) compared to 60° (0.303 N mm-2). The 45° blade placement angle demonstrated minimum shear stress (0.177 N mm-2) versus 60° (0.320 N mm-2). Increasing moisture content from 19% to 24% reduced shear stress from 0.256 N mm-2 to 0.200 N mm-2. The highest reciprocating speed (1400 courses per minute) resulted in the lowest shear stress (0.167 N mm-2) compared to 800 courses per minute (0.286 N mm-2). Life cycle assessment revealed that varying blade placement angles (30° to 60°) could increase marine aquatic ecotoxicity by up to 55,762.55 kg dichlorobenzene equivalent, while changes in blade sharpness angles and reciprocating speed could lead to increases of 377,429.87 kg and 143,185.69 kg dichlorobenzene equivalent, respectively. The optimal configuration—comprising a sharpness angle of 30°, a placement angle of 45°, a moisture content of 24%, and a reciprocating speed of 1400 courses per minute—significantly reduced both shear energy and environmental impact.
Research Article-en
Bioenergy
M. Ghaderi; P. Salami; H. Samimi-Akhijahani; S. Zareei; M. Safvati
Articles in Press, Accepted Manuscript, Available Online from 07 July 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://doi.org/10.22067/jam.2025.92457.1349
Abstract
The rapid growth of the global population and the increasing demand for energy, coupled with the urgent need for environmental conservation, have prompted researchers to explore renewable energy sources as viable alternatives to non-renewable fossil fuels. This study evaluates the performance enhancement ...
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The rapid growth of the global population and the increasing demand for energy, coupled with the urgent need for environmental conservation, have prompted researchers to explore renewable energy sources as viable alternatives to non-renewable fossil fuels. This study evaluates the performance enhancement of photovoltaic/thermal (PVT) systems using an immersion cooling method with copper oxide nanofluids. The experimental setup included a glass chamber immersing the panel surface, tested at nanofluid volume ratios of 0.025% and 0.05%, and flow rates of 0.01 and 0.02 L s-1. The immersion height was 5 cm within the glass chamber. The tests were conducted under ambient conditions, which included an ambient temperature of 20.6-31.2 ℃ and an irradiance of 343-924 W m-2. Results demonstrate that copper oxide nanofluids at a 0.05% volume ratio and a 0.02 L s-1 flow rate improved thermal efficiency to 31.87% and reduced panel surface temperature by up to 11.8 °C compared to water cooling. Also, the electrical efficiency of the PVT system exceeded that of the reference panel. The overall efficiency of the PVT system reached 41.89%. These findings highlight the potential of nanofluid-based cooling to optimize PVT system efficiency by enhancing thermal management.
Research Article-en
Nanotechnology (packaging films, biocomposites, solar cells)
A. Nahalkar; A. Rajaei; H. Mirzaee Moghaddam
Articles in Press, Accepted Manuscript, Available Online from 07 July 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2025.90690.1312
Abstract
This study investigated the effects of walnut oil incorporation on the physicomechanical and structural properties of sodium carboxymethyl cellulose-based edible films, with a focus on two methods of oil addition: bilayer and composite configurations. For this purpose, firstly walnut oil Pickering emulsion ...
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This study investigated the effects of walnut oil incorporation on the physicomechanical and structural properties of sodium carboxymethyl cellulose-based edible films, with a focus on two methods of oil addition: bilayer and composite configurations. For this purpose, firstly walnut oil Pickering emulsion (10% oil) was stabilized using chia seed gum, which was then incorporated into the formulation of bilayer and composite films. SEM revealed that bilayer film exhibited a more cohesive and homogeneous structure compared to the composite film. XRD analysis indicated a semi-crystalline amorphous structure across all films, with bilayer film displaying slightly sharper peaks than composite film. Moisture content and solubility tests highlighted the hydrophobic influence of walnut oil, with bilayer films exhibiting the lowest moisture content and solubility due to their surface-localized oil layer. Thermal analysis using DSC and TGA demonstrated improved thermal stability and reduced weight loss in bilayer film. Mechanical tests showed that the bilayer film had the highest elongation at break (34.3%) and the lowest tensile strength (3.4 MPa). Color analysis revealed significant changes in chromatic indices, with composite films showing higher saturation and total color difference. These findings underscore the potential of walnut oil emulsion stabilized with chia seed gum, particularly in bilayer configurations, to enhance the functional properties of sodium carboxymethyl cellulose-based films.
Research Article-en
Precision Farming
H. Karimi; M. J. Assari; F. Ranjbar-Varandi
Articles in Press, Accepted Manuscript, Available Online from 07 July 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2025.90276.1297
Abstract
The Dubas bug (Ommatissus lybicus) poses a significant threat to agriculture in the Middle East by weakening palm trees and reducing fruit production. Effective pest control depends on accurate and timely localization of the infestation. However, regular field inspections are difficult and time-consuming, ...
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The Dubas bug (Ommatissus lybicus) poses a significant threat to agriculture in the Middle East by weakening palm trees and reducing fruit production. Effective pest control depends on accurate and timely localization of the infestation. However, regular field inspections are difficult and time-consuming, especially for large areas. This research investigates the potential of Sentinel-2 satellite imagery for detecting Dubas bug infestations. The aim is to improve monitoring capabilities, accelerate intervention strategies, and mitigate the associated economic impact. The field trial to assess the infestation occurred in May 2023, coinciding with the peak of the pest outbreak. The severity of the infestation was assessed through pest counts conducted in date palm groves within the urban area of Bam, Iran. Sentinel-2 multispectral images of a specific area were acquired and processed for correction, raw data preparation, and information extraction. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method was used for the atmospheric correction of the acquired images. The Nearest Neighbor Interpolation method was used to resample satellite images, standardizing all bands to a uniform 10-meter resolution. Following the pre-processing phase, the KD-tree-based K-Nearest Neighbor classifier model was selected to develop a model specifically designed for identifying areas infested by the Dubas bug. For training, 70% of the measured field data were used, including uninfested areas and areas with three levels of infestation from light to heavy, as well as other land features such as buildings, roads, etc. The remaining 30% of the data was utilized to evaluate the trained model, using the correct prediction rate as the assessment criterion. The trained classifier, validated against the ground truth data, achieved an accuracy of approximately 83% on the test dataset. This accuracy highlights the ability of Sentinel-2 multispectral imagery and machine learning to detect Dubas bug infestations in date palm groves and can facilitate targeted and sustainable pest management strategies.
Research Article-en
Image Processing
R. Külcü; A. Süslü
Articles in Press, Accepted Manuscript, Available Online from 07 July 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2025.89763.1284
Abstract
The Soil and Plant Analysis Development (SPAD) value is a significant parameter indicating chlorophyll content, particularly in the green parts of plants. Conventional SPAD meters determine this value by measuring the transmission and absorption of red and infrared radiation at a single point (2×3 ...
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The Soil and Plant Analysis Development (SPAD) value is a significant parameter indicating chlorophyll content, particularly in the green parts of plants. Conventional SPAD meters determine this value by measuring the transmission and absorption of red and infrared radiation at a single point (2×3 mm2 sensor size). However, obtaining a comprehensive value for an entire leaf requires multiple measurements, increasing processing time. In this study, a non-destructive method for predicting SPAD values was developed using image processing techniques to determine dominant wavelength values from leaf photographs. A custom-designed photo box with controlled 6000 lux white LED lighting was used to capture images at a fixed distance of 15 cm. Images were processed using Color Picker (2024) software, where green components of the leaf were analyzed to extract dominant wavelength values. The results demonstrated that SPAD values could be accurately predicted using dominant wavelength data, with a 98.33% accuracy for the linear model (RMSE: 1.308) and 98.43% for the polynomial model (RMSE: 5.467). The findings indicate that a linear model provides a more precise correlation. This novel approach enhances the efficiency of SPAD measurement and offers a rapid, non-destructive alternative to conventional methods.
Research Article-en
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
M. ALmoosa; S. Al-Atab; S. Almaliki
Articles in Press, Accepted Manuscript, Available Online from 07 July 2025
©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
https://doi.org/10.22067/jam.2024.90031.1290
Abstract
Soil properties play a fundamental role in the success of agricultural operations through their impact on crop growth and quality, as they determine their ability to retain water and absorb nutrients, and affect soil aeration and the root system. The aim of this study is to predict bulk density and resistance ...
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Soil properties play a fundamental role in the success of agricultural operations through their impact on crop growth and quality, as they determine their ability to retain water and absorb nutrients, and affect soil aeration and the root system. The aim of this study is to predict bulk density and resistance to soil penetration under different moisture levels during tillage operations. It includes four moisture levels: 7, 14, 22, and 28%, and three types of plows: the moldboard plow, chisel plow, and disc plow. Moreover, soil samples were collected at two depths: 15 cm and 30 cm. The change in the physical properties of the studied soil is also measured during the growth periods of wheat crop (after tillage, beginning of the season and end of the season). The study is conducted in Al-Qurna district, north of Basra Governorate, Iraq, in clay loam soil. The results are analyzed and mathematical equations are obtained to predict the studied properties using the response surface methodology. The obtained results indicate that soil moisture during plowing, plow type, soil depth, and crop growth periods have a significant effect on soil bulk density and penetration resistance. The 14% moisture treatment is superior, recording the lowest bulk density and lowest penetration resistance of 1.12 Mg m-3 and 1133 kN m-2, respectively. While the 28% moisture treatment provided the highest bulk density and highest penetration resistance of 1.22 Mg m-3 and 1379 kN m-2, respectively. The results also show that increasing the soil depth from 15 to 30 cm increases the bulk density and soil penetration resistance, by 12 and 45.70%, respectively. Plowing with a disc plow improves soil properties, giving the lowest bulk density and penetration resistance of 1.12 Mg m-3 and 1074 kN m-2, respectively. While using the chisel plow leads to recording the highest bulk density and penetration resistance, which reached 1.22 Mg m-3 and 1442 kN m-2, respectively. As for the moldboard plow, the bulk density and soil penetration resistance reached 1.18 Mg m-3 and 1282 kN m-2, respectively. The growth periods have a significant effect on the studied soil properties where the beginning of the growing season provided the lowest bulk density. The bulk density reached 1.17, 1.13, and 1.23 Mg m-3 for the periods after plowing, at the beginning of the season and its end, respectively. While the penetration resistance after plowing is superior with the lowest resistance compared to the beginning of the season and its end, as it reached 897, 1327, and 1573 kN m-2, respectively. The results of data analysis show that the obtained mathematical models accurately and efficiently predict bulk density and soil resistance to penetration under the experimental conditions, with a high coefficient of determination (R2) of 0.6460 and 0.8114 for the bulk density and penetration resistance, respectively.
