Journal of Agricultural Machinery

Research Article Modeling

Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm

S. Sharifi; N. Hafezi; M. H. Aghkhani

Volume 15, Issue 2 , June 2025, Pages 145-164

https://doi.org/10.22067/jam.2022.77064.1108

Abstract

IntroductionEfficient use of energy in paddy production can lower greenhouse gas emissions, safeguard agricultural ecosystems, and promote the growth of sustainable agriculture. Meanwhile, intelligent agriculture has come to the aid of farmers and policy-makers by harnessing cutting-edge technologies, ... Read More IntroductionEfficient use of energy in paddy production can lower greenhouse gas emissions, safeguard agricultural ecosystems, and promote the growth of sustainable agriculture. Meanwhile, intelligent agriculture has come to the aid of farmers and policy-makers by harnessing cutting-edge technologies, which will lead to sustainable welfare and the comfort of human society in the present and the future. Therefore, this study aimed to analyze energy consumption and production, as well as model and optimize the yield of two paddy cultivars using Artificial Bee Colony (ABC) and Genetic Algorithms (GA).Materials and MethodsExtensive research data was collected by thoroughly examining documentary and library resources, as well as conducting face-to-face questionnaires with 120 paddy farmers and farm owners in Rezvanshahr city, located in the province of Guilan, Iran, during the 2019-2020 production year. The farms consisted of 80 high-grading and 40 high-yielding paddies. The independent variables were machinery, diesel and gasoline fuels, electricity, seed, compost and straw, biocides, fertilizers, and labor. The dependent variable was paddy yield per hectare [of the farm area]. In the first step, energy consumption and production were calculated by multiplying the variables by their corresponding coefficients. In the second step, all the variables that maximize paddy yield were entered into MATLAB software. An artificial bee colony (ABC) algorithm with a novel and straightforward elitism structure was utilized to enhance the fitness function of the genetic algorithm (GA). The Sphere, Repmat, and Unifrnd functions were employed to determine the objective function, define the position of the bee colony, and quantify the position of the bee colony, respectively. In each generation, 900 new solutions were created, and the algorithm iterated 200 times. For the genetic algorithm, the population was defined as a double vector with a size of 100.Results and DiscussionThe findings revealed that the Hashemi (high-grading) paddy cultivar had an average energy consumption and production of 55.973 and 30.742 GJ·ha-1, respectively. The Jamshidi (high-yielding) paddy cultivar had an average energy consumption of 54.796 GJ·ha-1 and double the energy production of the Hashemi at 62.522 GJ·ha-1. In both cultivars, agricultural machinery consumed the highest amount of energy, while straw consumed the lowest amount. The average energy consumption of tractors in the Hashemi and Jamshidi cultivars was 25.111 and 25.865 GJ·ha-1, respectively, accounting for 44.862% and 47.202% of the total average consumed energy. This undoubtedly demonstrates the significant effect of this input and reflects the operators' skill and experiential knowledge. The evaluation indexes, including R², RMSE, MAPE, and EF, as well as statistical comparisons such as mean, STD, and distribution, consistently demonstrated that the ABC algorithm provided the essential conditions for the fitness function. The results of the bee-genetic algorithm optimization revealed that the majority of the consumed resources could be effectively managed on the farm to closely match optimal conditions. Through this optimization, energy consumption in the Hashemi and Jamshidi cultivars was reduced by 53.96% and 39.41%, respectively.ConclusionGiven its impressive performance and potential for minimizing energy consumption, the ABC-GA algorithm offers an opportunity for policymakers in energy resource management and rice industry managers to develop innovative strategies for significantly reducing energy usage in rice production. This approach could lead to more sustainable and efficient practices in the agricultural sector.

Research Article Design and Construction

Construction and Performance Evaluation of a Flow Meter Based on Thermal Pulse to Measure Plant Sap Flow in Vascular Tissues

M. Teimorzadeh; J. Baradaran Motie; A. Rohani; Y. Selahvarzi

Volume 15, Issue 2 , June 2025, Pages 165-177

https://doi.org/10.22067/jam.2023.81221.1150

Abstract

IntroductionNeglecting the water requirements of trees can result in inefficient irrigation practices, leading to either water wastage or drought stress. Effective irrigation management necessitates precise information on the quantity and pattern of water consumption by trees. To achieve optimal irrigation, ... Read More IntroductionNeglecting the water requirements of trees can result in inefficient irrigation practices, leading to either water wastage or drought stress. Effective irrigation management necessitates precise information on the quantity and pattern of water consumption by trees. To achieve optimal irrigation, a reliable method for quantifying plant water needs is crucial, ensuring that trees avoid drought stress. Current methods for assessing tree water requirements often focus on specific components, such as stems or leaves. These techniques typically require manual intervention, which is time-consuming and resource-intensive, thereby restricting their application mainly to research environments.Materials and MethodsA sap-flow meter device was developed to generate a heat pulse in a tree trunk at 15-minute intervals. The device comprises measuring probes, a processing unit, and a data logger. For a comprehensive evaluation, device probes were positioned on the trunk of a Ficus benjamina tree within a controlled environment at two distinct heights. The resulting sap flow through the vascular tissue was then compared to data obtained using the lysimetric method. The Ficus benjamina tree, with a trunk diameter of 3.5 cm and a height of 196 cm, was prepared during the summer of 2022. By measuring the rate of heat pulse dissipation and applying heat transfer principles, sap flow is estimated under the assumption that heat transfer occurs primarily through the sap flow within the vascular tissue. This estimation was achieved using the heat ratio method (HRM).The trunk was triple drilled with holes of 1.5 mm in diameter and 25 mm in depth. Following drilling, the probes were inserted into these holes (Figure 1). To prevent heat transfer from the probes to the surrounding environment, the trunk was wrapped with glass wool insulation. To assess the reliability of the device, the lysimetric method was employed to measure tree transpiration. For this purpose, the soil surface of the pot was covered with cellophane to ensure that evaporation and weight loss of the pot occurred exclusively through the tree's leaves. Hourly measurements of the pot's weight were taken using a digital scale. Changes in the pot's weight indicate the amount of water evaporated, which corresponds to the water transpired by the tree through its vascular tissue.Results and DiscussionThe results showed that the sap-flow meter device slightly overestimates the tree's water consumption compared to the values obtained using the lysimetric method. Sap flow and transpiration follow a similar trend, both escalating throughout the day and reaching their highest levels in the early afternoon. This value reached 17.98 ml h-1 for sap flow and 16 ml h-1 for transpiration (by lysimetric method), followed by a rapid decrease in the late afternoon as the air cooled down. In addition, the results of device measurements showed that spraying water on the leaves lowers both the rate and volume of sap flow. When the canopy becomes wet, the evaporation of water from the leaf surface leads to a drop in the temperature, which in turn significantly slows down the flow of sap.The v1/v2 ratio is not constant over time, making it crucial to choose the right starting point for measurements to ensure effective data acquisition during the device's operational cycle. It is essential to measure (by the device) the difference between temperature probes 40 seconds after heat pulse generation. The sap flow and transpiration followed a similar trend during the experiments. The sap flow and transpiration increased throughout the day, peaking in the early afternoon. On the first day, sap flow reached 17.98 ml h-1, while the second day recorded an even higher rate of 19.75 ml h-1. Correspondingly, the transpiration measured using the lysimetric method peaked at 16 ml h-1, followed by a rapid decline in the late afternoon.ConclusionThe results obtained from the developed device indicate several key findings. Sap flow and transpiration exhibit a similar trend during the test period, with the estimated sap flow value being approximately 30% higher than that obtained using the lysimetric method. The device effectively demonstrated the impact of surface irrigation; spray irrigation influences the sap flow rate such that when the canopy becomes wet, the sap flow rate decreases significantly. Additionally, sap flow and transpiration are positively correlated with air and canopy temperatures, and negatively correlated with relative humidity. Following calibration, the results show that the heat pulse method can accurately and effectively measure sap flow in the vascular tissue of trees.

Research Article Design and Construction

Monitoring Livestock Health by Modeling Rumination Behavior According to Accelerometer-Based Information

E. Vahedi Tekmehdash; H. Navid; H. Ghasemzadeh; H. Karimi; M. Javani Holan

Volume 15, Issue 2 , June 2025, Pages 179-192

https://doi.org/10.22067/jam.2024.86082.1216

Abstract

IntroductionThe livestock sector excels in the production of dairy and meat products. These products, serving as vital sources of animal protein, hold a significant position in household diets. The significance of these two products in the food basket has heightened awareness around animal health. Regularly ... Read More IntroductionThe livestock sector excels in the production of dairy and meat products. These products, serving as vital sources of animal protein, hold a significant position in household diets. The significance of these two products in the food basket has heightened awareness around animal health. Regularly tracking rumination time serves as a vital and insightful measure to obtain information about the rest and overall health of an animal. This information enables prompt intervention for health or nutritional issues, allowing for earlier management adjustments and veterinary care to effectively combat the onset of disease. In the past, rumination was usually monitored through visual observation by on-site staff or through videos recorded by cameras installed on the livestock. Nowadays, the growing scale of livestock farms makes it impractical to effectively monitor the animals individually. The traditional method of visual observation demands the continuous presence of livestock professionals and is extremely time-consuming. Currently, sensors and digital technologies have become important tools for accurate animal husbandry, enabling real-time monitoring of rumination. A review of the research in the field of precision animal husbandry shows that many efforts are being made to develop precision monitoring sensors to overcome the mentioned problems. Continuous and automatic monitoring of animal behavior through sensors can offer valuable insights into nutrition, reproduction, health, and overall well-being of dairy cows.Materials and MethodsIn this research, an accelerometer-based sensor was developed and used in the precision agriculture laboratory of Tabriz University, Iran. The sensor was installed in three different positions on the cow's body to collect data. Important factors were calculated from the raw data, and the modeling was done using the logistic regression method. The logistic regression model was trained to distinguish rumination from the other cow's behaviors. The developed model was evaluated using the receiver operating characteristic (ROC) curve, and three other evaluation criteria: precision, sensitivity, and F-score. Finally, the performance of the final model and sensor was evaluated in the field for a few days.Results and DiscussionAfter calculating the evaluation criteria for different calculation factors, four optimal factors were finally selected from the 50 arrays. Muzzle mode was found to be the best place to install the sensor. Logistic regression was the best modeling method for binary classification between rumination and other behaviors. The evaluation criteria of the model in the proposed sensor are the highest, and the values of sensitivity 88%, accuracy 94%, and F-score 91% were obtained through logistic regression analysis. The final test results of the model revealed that the sensor demonstrated an impressive detection capability of 89.47%. Furthermore, the developed system exhibited strong alignment with the actual field observations, highlighting its effectiveness and reliability. Finally, the results of the current study were compared with other studies in the literature.ConclusionThis study investigated recording and monitoring rumination behavior using an accelerometer, which can help prevent financial losses in cattle farms. After examining different mounting locations of the sensor, it was found that the muzzle position provided more accurate detections than the other mounting locations. The final model was created using the statistical factors and the calculation of the evaluation criteria. The results showed that the proposed model provided more correct diagnoses and achieved the optimal solution.AcknowledgmentWe would like to express our gratitude to the Khalat Poushan Cattle Farming Complex of the University of Tabriz, Iran, its professors and staff for supporting this project, and for their commitment to promote animal husbandry science.

Research Article Design and Construction

Design, Construction, and Evaluation of a Spatial Depth Measurement System for Subsoiler in Sugarcane Fields

N. Loveimi; A. Azizi; A. Kaab; A. Neisi

Volume 15, Issue 2 , June 2025, Pages 193-209

https://doi.org/10.22067/jam.2024.87809.1242

Abstract

IntroductionSubsoiling is a critical tillage operation for many crops, particularly sugarcane, due to the impact of agricultural machinery traffic and its significance in managing heavy-textured and compacted soils. Given the extensive size of sugarcane fields and the time-intensive nature of subsoiling ... Read More IntroductionSubsoiling is a critical tillage operation for many crops, particularly sugarcane, due to the impact of agricultural machinery traffic and its significance in managing heavy-textured and compacted soils. Given the extensive size of sugarcane fields and the time-intensive nature of subsoiling operations, the application of intelligent control techniques for monitoring and managing these processes is of considerable importance. Currently, subsoiling operations are monitored using manual gauges. This approach involves collecting a limited number of samples per hectare, typically after the operation is completed, which makes it nearly impossible to implement real-time corrections. To address this limitation, the development and implementation of a depth measurement system offer a promising solution. Such a system enables real-time observation of working depth by both the operator, via an on-screen display, and by a remote observer through an online platform. This capability allows for immediate adjustments during the operation, ensuring greater precision and efficiency. Furthermore, by integrating recorded depth data with geospatial information, it becomes possible to generate detailed maps illustrating depth variations across the field. These maps can serve as valuable tools for further evaluations, such as performance monitoring in areas where subsoiling depth deviates from the desired range, either being too shallow or excessively deep. This technological advancement has the potential to significantly enhance the accuracy and effectiveness of subsoiling operations in modern agricultural practices.Materials and MethodsThis study focused on the design, development, and evaluation of a depth measurement system for a subsoiler attached to a track-type tractor, specifically tailored for sugarcane fields. The system not only provided real-time depth display but also recorded the location and transmitted it online. The research employed three distinct depth measurement techniques and was conducted using a randomized complete block design with split plots. The main plots are the three depth measurement techniques: based on the angles of the driving profiles of the subsoiler shanks (T1), the laser distance measurement method (T2), and the ultrasonic distance measurement method (T3), and sub-plots are depth ranges at three levels: 0-30 cm (R1: surface range), 30-60 cm (R2: mid-range), and 60-90 cm (R3: deep range). Initially, we calculated the absolute difference between the depths recorded by the system and those measured manually with a rod at each location. Following this, we analyzed key statistical indicators, including the average, standard deviation, and the minimum and maximum of errors, for comparison.Results and DiscussionThe results showed that the depth measurement error was significantly influenced by the technique employed. The angle technique yielded the lowest average error of 1.91 cm, while the ultrasonic technique resulted in the highest average error of 3.83 cm. Across all depth ranges, statistical indicators for depth error were significant. Specifically, within these ranges, the deep range exhibited an average depth error of 2.33 cm, and the surface range had an average error of 3.65 cm. Statistical analysis revealed that only indices related to minimum and maximum errors for interactions between factors were significant. The lowest minimum error value (0.05 cm) was observed with the angle technique at deeper depths, whereas the highest minimum error (0.34 cm) occurred with ultrasonic measurements at shallower depths on surfaces. Similarly, maximum errors followed this trend: The lowest maximum error (3.21 cm) was associated with angle measurements at deeper depths, while ultrasonic measurements on surfaces yielded a higher maximum error (8.63 cm). Both laser and ultrasonic techniques consistently demonstrated greater errors across all three depth ranges compared to angle-based methods. This discrepancy may be attributed to inaccuracies inherent in rangefinders when their beams encounter obstacles like clods or pits during field operations. Notably, as working depths increased across all measurement techniques, errors in depth measurement decreased significantly due to reduced vibrations from subsoiler devices at greater depths, thereby minimizing vibration-related inaccuracies.ConclusionThe results indicate that the depth measurement technique based on the angles of the driving profiles of subsoiler shanks exhibits superior accuracy in determining the working depth of subsoilers mounted on tractors, particularly during sugarcane field operations. The laser distance meter technique ranked second in terms of accuracy, while the ultrasonic distance meter method demonstrated the least precision. Notably, as working depths increased, reduced vibrations during operation were observed, leading to enhanced accuracy in depth calculations across all techniques. This improvement is attributed to decreased mechanical disturbances at greater depths. Overall, measurements within deeper ranges achieved higher levels of accuracy compared to those at shallower surface ranges. This trend suggests that operational conditions and device stability play significant roles in optimizing measurement accuracy.

Research Article Agricultural systems engineering (greenhouse, fish farming, mushroom production)

Evaluation of the Development Level of Edible Mushroom Production Systems in Iran between 2016 and 2021

M. Zangeneh; E. Godini

Volume 15, Issue 2 , June 2025, Pages 211-228

https://doi.org/10.22067/jam.2024.88204.1252

Abstract

IntroductionIn recent years, the lack of adequate regional assessment and classification has led to unequal investments and policies, resulting in polarization and disparities in the development of agricultural units. However, since agricultural products are produced, distributed, and consumed nationwide, ... Read More IntroductionIn recent years, the lack of adequate regional assessment and classification has led to unequal investments and policies, resulting in polarization and disparities in the development of agricultural units. However, since agricultural products are produced, distributed, and consumed nationwide, analyzing production conditions across different agricultural systems can provide valuable insights for supply chain managers. A comprehensive evaluation of production system development across the country can enhance product quality, stabilize the supply chain, reduce costs, and improve overall efficiency and performance. These improvements are vital for advancing the agricultural sector and strengthening national competitiveness. In many regions, agriculture forms the backbone of the local economy, making regional equity and balanced development essential for sustainable agricultural growth.Materials and MethodsThis research was conducted with the aim of evaluating the development levels of different provinces of the country in the field of edible mushroom cultivation. The approach of this research is descriptive-analytical. The statistical population includes 31 provinces of Iran, and the required data are based on the results of the 2016 and 2021 censuses of the Statistical Center of Iran. Following the initial review, indicators that emphasize the aspects of human power, infrastructure, performance, waste, economy, and energy were collected. Weight estimation of indicators was done using Shannon's entropy method. The TOPSIS method was used to assess and rank the provinces based on their level of development within the mushroom cultivation industry. The ranking operation was done using eight different index groups: infrastructure, consumption of inputs, value of consumption inputs, types of products and waste, value of payment types, value of product categories, value of energy consumption, and the number of employees and payments to them.Results and DiscussionResults show that in 2016, the provinces were classified into three levels: relatively deprived of development, medium development, and relatively developed. Apart from Alborz province, which was placed at a relatively developed level, other provinces were placed at lower levels. By 2021, all provinces had made significant progress compared to 2016, elevating their development status so that none were classified as relatively deprived. Furthermore, the number of provinces categorized as relatively privileged surged from just one in 2016 to eight by 2021. The findings revealed that the smaller, non-industrialized provinces exhibited greater development compared to their larger, industrialized counterparts.ConclusionThe results showed that Alborz province had the highest level of development, and Semnan province had the lowest level of development of this industry in the country. The level of development and ranking of edible mushroom cultivation units in the provinces was obtained by using different categories of indicators and the TOPSIS multi-criteria decision-making method. To enhance the production and productivity of cultivated edible mushrooms, it is essential to advance cultivation techniques and technologies through the expansion of research initiatives, educational programs, and extension activities.

Research Article Bioenergy

Investigating Engine Performance and Emission Characteristics during Testing of Diesel-Biodiesel Mixed Fuels Obtained from Vegetable Oils and their Modeling

S. R. Mousavi Seyedi; M. Askari; S. M. R. Miri

Volume 15, Issue 2 , June 2025, Pages 229-245

https://doi.org/10.22067/jam.2024.88750.1263

Abstract

IntroductionIn Asia, two-wheeled agricultural tractors predominantly use single-cylinder two-stroke diesel engines, which are characterized by high fuel consumption and substantial air pollution. At the same time, the severe environmental impacts of energy production from diminishing fossil fuel reserves ... Read More IntroductionIn Asia, two-wheeled agricultural tractors predominantly use single-cylinder two-stroke diesel engines, which are characterized by high fuel consumption and substantial air pollution. At the same time, the severe environmental impacts of energy production from diminishing fossil fuel reserves are increasingly evident. Therefore, it is essential to develop sustainable and clean energy sources to meet these needs. Biodiesel is an alternative fuel that can be blended with conventional diesel to help reduce environmental pollution. In this study, diesel-biodiesel blends produced from rapeseed, soybean, and palm oil were evaluated for their effects on engine performance metrics, including power (P), torque (T), and specific fuel consumption (SFC). Furthermore, the emissions of pollutants (NOx, HC, CO, and CO₂) from these fuels were measured and modeled using linear and non-linear regression, as well as the adaptive neuro-fuzzy inference system (ANFIS).Materials and MethodsTo leverage the benefits of palm oil biodiesel, known for its high calorific value, along with the low kinematic viscosity of biodiesel derived from soybean and rapeseed oils, pure diesel was blended with 10% and 20% mixtures of rapeseed, soybean, and palm biodiesel, as well as 10% and 20% combinations of all three biodiesels. These nine fuel blends were tested at four engine speeds (1800, 2100, 2400, and 2700 rpm) under full load conditions. The diesel-biodiesel blends were produced at Sari Agricultural Sciences and Natural Resources University (SANRU) and transported to the engine laboratory at Tarbiat Modares University in Tehran, Iran, for detailed analysis. A total of 36 treatments were evaluated using a randomized complete block design (RCBD), incorporating four engine speeds and nine fuel types. The measured outputs included engine power, torque, specific fuel consumption, and pollutant emissions such as NOx, HC, CO, and CO₂. The collected data were used as input for modeling through both linear and non-linear regression in SPSS software, as well as ANFIS in MATLAB software.Results and DiscussionThis study evaluated nine diesel-biodiesel blends derived from palm, rapeseed, and soybean oils using a diesel engine in a controlled laboratory setting. Tests were carried out at four engine speeds—1800, 2100, 2400, and 2700 rpm—under full load conditions to assess engine performance and exhaust emissions. The results showed that for all tested fuel blends, power, specific fuel consumption, and pollutant emissions increased with engine speed, while torque decreased. Based on the findings, a blend containing 20% palm biodiesel can be used as an alternative fuel in diesel engines without requiring any modifications. The modeling results indicated that non-linear regression provided better accuracy than linear regression. However, ANFIS demonstrated a much higher correlation between actual and predicted values, with R² exceeding 0.98 for both performance parameters and emissions, compared to R² values below 0.47 for linear regression and below 0.92 for non-linear regression. The ANFIS model achieved its highest and lowest R² values at 0.99 for specific fuel consumption (SFC) and 0.98 for power (P), respectively; substantially higher than those from linear regression, which yielded 0.47 for torque (T) and 0.00 for power. Non-linear regression resulted in R² values of 0.92 for SFC and 0.60 for carbon monoxide (CO), still lower than those achieved by ANFIS. Overall, the highest R² value recorded was 0.7525 for torque, and the lowest was 0.6112 for power.ConclusionSingle-cylinder diesel engines, which have high fuel consumption and contribute to air pollution, are commonly used in two-wheel agricultural tractors across Asia. One approach to reducing the environmental impact of fossil fuels is to use biodiesel in these engines without requiring any modifications. The results of this study showed that a 20% blend of palm biodiesel can be an effective alternative fuel for diesel engines, with no need for engine modification. Furthermore, the modeling results indicated a significantly higher correlation (R² > 0.98) between actual and predicted values of performance variables and emissions using ANFIS, compared to linear regression (R² < 0.47) and non-linear regression (R² < 0.92). Therefore, ANFIS can be effectively used to accurately predict engine performance and emission parameters.

Research Article Modeling

Comparison of Energy Consumption Optimization in Sugar Factory Using Meta-Heuristic Algorithms

M. Boroun; M. Ghahderijani; A. A. Naseri; B. Beheshti

Volume 15, Issue 2 , June 2025, Pages 247-261

https://doi.org/10.22067/jam.2024.89450.1278

Abstract

IntroductionEnergy analysis offers significant benefits by establishing a foundation for resource conservation, quantifying the energy consumed at each stage of production, identifying processes that require minimal energy input, and supporting sustainable management practices. In sustainable agricultural ... Read More IntroductionEnergy analysis offers significant benefits by establishing a foundation for resource conservation, quantifying the energy consumed at each stage of production, identifying processes that require minimal energy input, and supporting sustainable management practices. In sustainable agricultural systems, maximizing the productivity of input energies is a key objective. This study aims to assess energy consumption patterns within the sugar industry and to compare the optimization of energy consumption indicators using two meta-heuristic algorithms, ultimately seeking to enhance resource efficiency and promote sustainable production methods.Materials and MethodsThis study evaluated energy efficiency and environmental impacts in sugarcane-based sugar production at Dehkhoda Sugarcane Agro-Industry Company (in Khuzestan Province, Iran), during the 2019-2020 agricultural cycle. Data collection integrated field questionnaires, expert interviews, operational records from the facility, and national agricultural databases (Ministry of Agriculture Jihad statistics and energy balance sheet). Energy flow were analyzed using MATLAB statistical software and the Equinonet database, with comparative optimization through genetic algorithms and imperialist competitive algorithms to identify efficiency improvements.Results and DiscussionThe results showed that, for the majority of indicators evaluated, the imperialist competitive algorithm outperformed the genetic algorithm in optimizing energy consumption. In addition to reducing the environmental impacts of this profitable industry in the country, it has a high potential for energy savings. The total energy input reduction with the genetic algorithm was 17.05%, while the imperialist competitive algorithm achieved a higher reduction of 26.40%. Natural gas consumption decreased by 3.82% using the genetic algorithm, and by 27.60% with the imperialist competitive algorithm. Direct energy savings were 16.97% for the genetic algorithm and 27.48% for the imperialist competitive algorithm. Soil acidification reduction was 23.03% with the imperialist competitive algorithm and 19.19% with the genetic algorithm, compared to conditions before optimization.ConclusionIn general, it can be concluded that, given the growing demand for sugar production and related industries, as well as the high efficiency of the sugar production sector, it is advisable to utilize expert knowledge and apply meta-heuristics methods to optimize energy consumption and available inputs with the aim of reducing harmful environmental impacts.

Research Article The relationship between machine and soil

Prediction of Rut Depth in Soil Caused by Wheels Using Artificial Neural Networks

N. Farhadi; A. Mardani; A. Hosainpour; B. Golanbari

Volume 15, Issue 2 , June 2025, Pages 263-274

https://doi.org/10.22067/jam.2024.90273.1295

Abstract

Introduction The formation of ruts induced by vehicle traffic poses a significant challenge for agricultural soils due to soil compaction both at the surface and deeper layers. This phenomenon compromises vehicle performance increases energy consumption, and leads to long-term environmental degradation, ... Read More Introduction The formation of ruts induced by vehicle traffic poses a significant challenge for agricultural soils due to soil compaction both at the surface and deeper layers. This phenomenon compromises vehicle performance increases energy consumption, and leads to long-term environmental degradation, such as soil erosion and fertility reduction. To enhance vehicle performance and reduce soil damage, it is crucial to accurately predict how factors such as vehicle speed, vertical load, and the number of passes impact rut depth. The findings of this study hold significant practical implications, facilitating the development for the creation of more efficient agricultural practices, while simultaneously minimizing environmental impact. The complexity of these interactions necessitates using machine learning models, especially artificial neural networks (ANNs), to predict rut depth based on input parameters. In this study, two machine learning models, namely the multilayer perceptron (MLP) and the radial basis function (RBF) networks, were employed to predict rut depth.Materials and MethodsExperiments were conducted using a soil bin that allows for precise control of independent parameters, measuring 24 meters in length, 2 meters in width, and 0.8 meters in depth. The soil used was agricultural soil, comprising 35% sand, 22% silt, and 43% clay, with a moisture content of 8%. The tests included three independent parameters: vertical load (2, 3, and 4 kN), forward speed (1, 2, and 3 km h-1), and number of wheel passes (up to 15). Two types of traction devices, including a rubber wheel and a track wheel, were tested. A caliper was used to measure the rut depth after each pass with an accuracy of 0.02 mm. The data collected from soil bin tests were used to train neural network models in MATLAB 2021-b software. The MLP model had a topology with two hidden layers and included three inputs and one output. In the RBF model, the network topology had a single hidden layer. The trial-and-error method was used to adjust the hyperparameters of the neural networks, including the number of neurons in the hidden layers, the learning rate, and momentum for the MLP network, as well as the spread rate and regularization rate for the RBF network.Results and DiscussionExperimental data confirmed that increasing the vertical load and the number of passes resulted in deeper ruts. Conversely, an increase in speed led to a reduction in rut depth, particularly during the initial pass. Both artificial neural network (ANN) models accurately predicted rut depth, with the multilayer perceptron (MLP) neural network outperforming the radial basis function (RBF) neural network. Specifically, the root mean square error (RMSE) for the optimal MLP model, which utilized a learning rate of 0.001 and a momentum of 0.67, was 0.10. In contrast, the optimal RBF model, with an expansion rate of 0.23456, yielded an RMSE of 0.12. The findings indicate that the MLP artificial neural network model surpasses the RBF neural network model in terms of accuracy and overall performance. However, the RBF neural network exhibits a faster response time, making it particularly suitable for real-time applications.ConclusionThis study demonstrates the efficacy of machine learning techniques, particularly artificial neural networks (ANNs), in predicting rut depth caused by off-road vehicle traffic. Both multilayer perceptron (MLP) and radial basis function (RBF) neural networks exhibited robust predictive capabilities, with the MLP model providing slightly superior accuracy and the RBF model offering better computational efficiency. These findings highlight the potential of machine learning in modeling complex interactions between soil and vehicles, which can enhance vehicle performance, mitigate soil erosion, and guide the design of off-road vehicles. Future research directions could include investigating additional soil parameters, various vehicle configurations, and the real-world implementation of autonomous off-road vehicles to promote more environmentally sustainable operations.

Effect of turbo charger system on engine fuel consumption and tractor power and traction (ITM475, ITM485 and ITM800)

Volume 5, Issue 2 , 2015, , Pages 313-324

https://doi.org/10.22067/jam.v5i2.28515

Abstract

Introduction: Tractors are considered as the main power generators in mechanized agriculture. Hence, the experts and engineers in tractor manufacturing of the country, are required to focus on developing and designing new features in tractor manufacturing. This must be, of course, paralleled with the ... Read More Introduction: Tractors are considered as the main power generators in mechanized agriculture. Hence, the experts and engineers in tractor manufacturing of the country, are required to focus on developing and designing new features in tractor manufacturing. This must be, of course, paralleled with the economic aspects. Achieving this goal, Iran Tractor Manufactories Co., (ITMCO) has designed and developed tractors equipped with turbochargers. This has been performed on ITM800 & ITM485 models, according to world standards. The turbocharger system, with harnessing of lost energy in engine output fumes, compresses the air entering the engine and more air enters the cylinder. This will cause the engine to burn fuel more efficiently and thus produce more power. Materials and Methods: This study has been carried out on ITM485 & ITM800 tractors (with turbocharger system) and ITM285 & ITM475 tractors (without turbocharger system) to assure the improvement of engine performance and compare them employing OECD world standards. Experiments were performed in the concrete runway of Tabriz Tractor Manufacturing Company. For experiments, a dynamometer was used to measure the traction force between two tractors, a measuring unit for fuel, a thermometer unit and a timer to measure the quantities of fuel consumption, drawbar force and power. For drawbar traction test, each of the tested tractors pulled the rear tractor in different gears and the dynamometer between these 2 tractors recorded the tractors traction force by data loggers. To measure tractors fuel consumption, a measuring unit of fuel (VDO - EDM 1404) was used that calculated the flow rate in the path of fuel from the fuel tank to the engine and the return path from the engine to the fuel tank and showed the quantity of fuel consumption in liters per hour digitally. Results and Discussion: In comparison of traction power and force of tractors with turbochargers and without turbochargers in different gears, the results of variance analysis showed that the effect of tractor was significant. Traction power and force at tractors with turbochargers ITM485 and ITM800 and without turbocharger ITM475 have a significant difference in the level of one percent. Tukey post hoc test results also indicate that traction power and force in tractors with turbochargers ITM485 and ITM800 are significantly more than the tractor without turbocharger ITM475. The gear effect is also significant. Traction power and force in different gears have significant difference at the probability of one percent. Tukey post hoc test results indicate that power quantity is highest in the gears: (1+H, 2*H, 1*H, 3+L) and minimum in the gears: (1*L, 1+L, 2*L), (* Turtle and + Rabbit). But Tukey post hoc test results indicate that traction force quantity is highest in the gears: (1*L, 2*L, 1+L) and minimum in the gears: (2*H, 1+H). In the comparison of specific fuel consumption of tractors with turbochargers and without turbochargers in different gears, the results of variance analysis showed that the effect of tractor was significant. The amount of specific fuel consumption at tractors with turbochargers ITM485 and ITM800 and without turbocharger ITM475 has a significant difference in the level of one percent. Tukey post hoc test results also indicate that specific fuel consumption quantity in tractors with turbochargers ITM485 and ITM800 in the level of one percent is significantly less than the tractor without turbocharger ITM475. The gear effect is also significant. The specific fuel consumption quantity in different gears has significant difference at the probability of one percent. Tukey post hoc test results indicate that specific fuel consumption quantity is highest in the gears: (1*L, 1+L, 2*L) and minimum in the gears: (1+H, 2*H, 1*H). Conclusions: The tests were performed on tractor drawbar traction. Results of variance analysis in this experiment on a concrete surface, indicated that the calculated traction power and force of ITM485 and ITM800 tractors (with turbocharger system) were higher than the ITM475 & ITM285 tractors (without turbocharger) and this difference was significant at the one percent level of probability. Meanwhile specific fuel consumption in the ITM485 and ITM800 tractors (with turbocharger system) was lower than that of the ITM475 & ITM285 tractors (without turbocharger) and this difference was significant at the one percent level of probability. This will lead to significant savings in fuel consumption.

Evaluation and Modeling of Camel Thorn (Alhagi Maurorum) Weed Cutting by Water Jet

Volume 4, Issue 1 , 2014, , Pages 125-132

https://doi.org/10.22067/jam.v4i1.33176

Abstract

Due to the importance of weed control and the limitations of mechanical methods in some places, in this research the water jet cutting for weed control was investigated. The cutting tests were performed on camel thorn weed in Shahid Bahonar university of Kerman. The water jet pressure of 90 bars was ... Read More

The Effect of Compression Ratio and Alternative Fuels on the Performance of Turbocharged Diesel Engine by GT-POWER Software

Volume 11, Issue 2 , 2021, , Pages 199-212

https://doi.org/10.22067/jam.v11i2.71613

Abstract

Introduction Today, maximizing the efficiency of fuels and increasing the output power of diesel engines is considered inevitable due to the increasing need for energy resources, the reduction of fossil fuel resources, the need to maintain the environment, reduce air pollution, and limit the electricity ... Read More Introduction Today, maximizing the efficiency of fuels and increasing the output power of diesel engines is considered inevitable due to the increasing need for energy resources, the reduction of fossil fuel resources, the need to maintain the environment, reduce air pollution, and limit the electricity supply and fuel supply. In the large cities of Iran, the problem of vehicle pollution is one of the main problems. The lack of proper fuel, soot filters, and absence of requirement for a technical inspection of diesel vehicles have led to an increase in mortality and the growth of lung cancer due to pollution. All of studies indicate that fossil fuels, despite the low cost of production, will increase the cost of both living and environment. A solution for this crisis is to reduce the sources of pollutant-producing sources from the source of these pollutants. In the internal combustion engines, the compression ratio and alternative fuels are two important factors affecting engine performance and exhaust emission. Materials and Methods In this research, a one-dimensional computational fluid dynamics solution with GT-Power software was used to simulate a six-cylinder diesel engine to study the performance and exhaust emissions with different compression ratios and alternative fuels. The compression ratio was chosen to be 15:1 to 19:1 with an interval at unity. Alternative fuels such as (as base diesel), methanol, ethanol, diesel and ethanol, biodiesel and decane were selected. To modeling engine, first, all parts of the engine were introduced as a real six-cylinder engine, and then the required data were entered according to the actual engine conditions at the atmospheric pressure of one atmosphere. Before this investigation was carried out, a validation model for evaluation was done by experimental and simulation data. The validation results showed that software model error is acceptable and the model has a good capability of fitting and predicting. Results and Discussion The engine performance was evaluated in terms of engine power, engine torque, and specific fuel consumption at different engine compression ratio and fuel. The results showed that with increasing the compression ratio, brake power and brake torque increased. Among the fuels used in this engine, the maximum brake power and brake torque in the compression ratio of 19 with the decane fuel were 3.86% higher than that the base fuel and the lowest value was awarded in the compression ratio of 15, with methanol fuel and it was equal with 56.04%. The results indicated that by increasing compression ratio, the brake specific fuel consumption was reduced due to more power than the fuel consumed in the engine. A fuel with lower heating value should be injected more mass to the engine. This will increase the brake specific fuel consumption. In this research, the decane fuel with a compression ratio of 19 with a reduction of 3.72% had the lowest brake specific fuel consumption among other fuels. The CO emission from the engine largely depended on the fuel's properties, the availability of oxygen, the fuel mix with air, temperature, and turbulence inside the combustion chamber. The results highlighted that by increasing compression ratio, CO emission increased and CO emission in biodiesel fuel, with a compression ratio of 15, was decreased by 82.37% compared to the base. CO2 emissions are not too harmful to humans, but they increase the potential for ozone depletion and global warming. With increasing compression ratio, CO2 and HC emissions increased for all fuels, CO2 emissions have risen up the base. The fuel heating mechanism, combustion temperature, oxygen content, and gas fuel availability are the most important factors in the formation of NOx. With increasing the compression ratio, the amount of NOX increases, which is due to the high temperature in the cylinder at a higher compression ratio. The viscosity and density of fuels have an effect on NOX emission, and because of the larger droplets of the fuel, it released NOX. The highest NOx emissions from biodiesel fuel are due to the high oxygen content of this fuel and the lowest NOx emissions from decane fuel, due to the low density of the fuel compared to other fuels. Conclusion The results of this study showed that the decane fuel with a compression ratio of 19 in total had the best functional and pollutant characteristics among the six fuel used in this study. Therefore, this fuel can be the best alternative for diesel fuel.

Comparison of Rice Direct Seeding Methods (Mechanical and Manual) with Transplanting Method

Volume 4, Issue 1 , 2014, , Pages 108-115

https://doi.org/10.22067/jam.v4i1.33172

Abstract

The main method of rice planting in Iran is transplanting. Due to poor mechanization of rice production, this method is laborious and costly. The other method is direct seeding in wet lands which is performed in the one third of rice cultivation area of the world. The most important problem in this method ... Read More

Design and Construction of a High-voltage System to Kill Weeds with a Feedback Mechanism

Volume 13, Issue 2 , June 2023, , Pages 117-133

https://doi.org/10.22067/jam.2021.70524.1051

Abstract

IntroductionVarious methods have been performed to control weeds in the world and the use of herbicides is one of them, but public concerns about human health have changed interest in alternative methods. Thermal methods based on flame-weeder, hot air, steam, and hot water have the potential to control ... Read More IntroductionVarious methods have been performed to control weeds in the world and the use of herbicides is one of them, but public concerns about human health have changed interest in alternative methods. Thermal methods based on flame-weeder, hot air, steam, and hot water have the potential to control weeds, but due to the high cost are not economical. Electromagnetic waves transfer energy into weeds and finally destroy them. The effect of radiation on plant mutation, high consumption of energy, and human health are problems for this approach. Unlike other methods, electrical energy is an ideal and non-chemical method for weeds. This method applies high voltage to weeds, their roots, and soil so that electric currents pass through them, and the vaporization of the liquid content of weeds kills the weeds. To increase the severity of damage to weeds, the development of a feedback mechanism is required. The ultrasonic sensor measuring physical parameters like plant height is a simple method. Some complex sensing systems include optical sensors such as infrared, and machine vision that require high-speed processors and expensive equipment. In this project, as a simple method, the monitoring of the electrical current passing through weeds was used for developing the feedback mechanism and increasing electric damage to weeds.Materials and MethodsIn this study, the system consisted of a high-voltage device that generated a 15 kV AC voltage to kill weeds, as well as a feedback mechanism that included a sensor to measure the electric current on the input of the weed killer and identify the presence of weeds and their annihilation. All parts were installed on a robotic platform, and an application on a laptop was connected to it via an access point for navigation and data reception. The system was tested in a greenhouse lab with various weeds. Initially, a test was performed to investigate the effect of high voltage on the weeds and establish relationships between the electric currents passing through weeds and their presence (before and after annihilation). During the test, the system was guided along a path and applied high voltage to kill the weeds. The feedback mechanism was then calibrated based on the extracted data on electric current relations. This allowed the system to detect weeds and their annihilation, enabling it to move to the next target once a weed had been eliminated. After calibration, a comparative test was conducted to evaluate the weed-killing efficiency of the two methods (with and without the feedback mechanism), and the results were analyzed using a t-test with p ≤ 0.01.Results and DiscussionThe observations indicated that the input electric current on the weed killer was dependent on the electric current passing through weeds. When the high-voltage electrode touched a weed, the electric current passed through it increased, and simultaneously, the high electrical energy destroyed the weed. After the removal of the weed, the electric current rapidly decreased. The average energy consumption per weed plant was estimated to be 250 joules, which can be compared with other methods. The final test comparing the use and non-use of the feedback mechanism revealed significant differences (P < 0.01) between the results obtained with and without the mechanism, demonstrating that the feedback mechanism increased the efficiency of weed annihilation. The sensing system used in the developed feedback mechanism is a simple method that is affected by the electrical resistivity of weeds. As such, it did not mistakenly detect other objects as weeds, unlike an ultrasonic mechanism. Based on these results, monitoring the electrical current passing through weeds proved to be a suitable method for developing a feedback mechanism for the weed killer to identify the presence of weeds and their annihilation.ConclusionThe use of high voltage as a non-chemical and alternative method for weed control has shown promising results. The study revealed that measuring the electric current applied to the weed killer was an effective and straightforward approach to developing a feedback mechanism. This mechanism aids in identifying the presence of weeds and ensuring their elimination by intensifying the damage inflicted on them through the application of high electrical energy. To further enhance the efficiency and speed of weed control, future research should consider integrating an automatic guidance mechanism with the weed killer.

Research Article-en

Investigating the Potential of the Innovative YOLOv8s Model for Detecting Bloomed Damask Roses in Open Fields

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 ... Read More

Research Article-en

Impact of Field Characteristics on Pneumatic Seed Drill Performance: A Case Study in Eritrea

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. ... Read More

Research Article-en

Effect of Magnetic Field on Seeds of Parsley (Petroselinum crispum): Modeling and Optimization by Response Surface Methodology

M. Rafiei; F. Khoshnam; M. Namjoo

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 ... Read More

Research Article-en

Detection and Classification of Some Diseases of Tomato Crops Using Transfer Learning

I. Ahmadi

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 ... Read More

Research Article-en

Sustainability of Traditional Paddy Rice Processing Techniques Among Smallholder Rice Farmers in Southeast Nigeria

C. N. Onwusiribe; J. Mbanasor; P. O. Nto; M. C. Ndukwu

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. ... Read More

Research Article-en

Evaluating the Effect of Soil Deformation Rate on the Estimation of the Energy Consumption in Soil-Tire Interactions Using the Pressure-Sinkage Equation

H. Asadollahi; B. Mohammadi-Alasti; A. Mardani; M. Abbasgholipour

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 ... Read More

Research Article-en

Sweet Pepper Detection Using Fast Point Features Histogram and Unsupervised Learning

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 ... Read More

Research Article-en

Energy, Environmental, and Economic Evaluation of a Novel Building Integrated Green System: Insights from Residents and Social Perspectives

M. M. Naserian; R. Khodabakhshian

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 ... Read More

Review Article-en

Prospects of Mechanization in Direct Seeded Rice: A Comprehensive Review

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 ... Read More

Review Article-en

Developing a Methodological Framework for Agricultural Cooperatives Studies: A PRISMA Systematic Review

M. Bamdad; M. Zangeneh; S. H. Peyman

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 ... Read More

Review Article-en

Potential and Pitfalls of Using Drone Technology in Sustainable Agriculture: An Overview

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 ... Read More

Research Article

Performance Analysis of a Walnut Peeler with a Rotating Cutting Plate

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 ... Read More 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

Investigating the Performance of Agricultural Mechanization Service Cooperatives in Gilan Province Using a Combined Delphi-AHP-SWOT Method

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, ... Read More 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

Real-Time Measurement of In-Field Soil Surface Roughness Using Laser and Infrared Sensors

N. Salehi Babamiri; H. Haji Agha Alizadeh; M. Dowlati

Articles in Press, Accepted Manuscript, Available Online from 03 June 2025

https://doi.org/10.22067/jam.2024.90374.1300

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 ... Read More 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

Feasibility and Site Selection for Wind-Powered Road Lighting in Kermanshah Province

B. Dosti; A. Asakereh

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 ... Read More 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

Field and Economic Evaluation of Spraying Drones Versus Boom Sprayers for Weed and Yellow Rust control in Wheat fields

M. Safaeinezhd; M. Ghasemi-Nejad Raeini; M. Taki

Articles in Press, Accepted Manuscript, Available Online from 28 April 2025

https://doi.org/10.22067/jam.2025.91236.1322

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 ... Read More 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

Manufacturing and Evaluation of a Dry land Rice Transplanter

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, ... Read More 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

Evaluation of Mechanical Properties of Polylactic Acid (PLA) Films Over One and Ten Months of Aging

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 ... Read More

Short Article- en

The Impact of Water and Climate Changes on Food Security in Middle-Low-Income Countries: A Case Study of Ghana and Vietnam

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 ... Read More

Research Article-en

Optimization of Hot-Air Drying Assisted with Incandescent Lamp of Red Seaweed (Chondracanthus chamissoi) Using Response Surface Methodology

E. Elena Vivanco-Cuba; D. Vivanco-Pezantes

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 ... Read More

Research Article-en

Evaluation and Optimization of Costs for Agricultural Machinery Management System in Arjo Diddessa Sugar Factory

S. K. Busse; T. K. Hurisa; E. A. Esleman

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 ... Read More

Research Article-en

Energetic and Economic Evaluation of Olive Production Systems: A Comparative Assessment of Chemical, Mechanical, and Integrated Weed Management Strategies

B. Mohammadi; A. R. Yousefi; M. Namdari; M. Heydari

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 ... Read More

Research Article-en

Investigating the Rates, Severity and Affecting Factors of Accidents Related to Agricultural Tractors and Grain Combine Harvesters in Ilam Province of Iran

J. Allahnouri; A. Marzban; M. Ghasemi-Nejad Raeini; M. Rahnama; M. Savari

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, ... Read More

Research Article-en

Modification and Analysis of Integrated Enset (Ensete ventricosum) Processing Machine Components

B. Adugna; K. Purushottam Kolhe; M. Gutu

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, ... Read More

Research Article-en

Optimization of the Canola Harvester Blade Based on Energy Reduction Approach and Life Cycle Assessment

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 ... Read More

Research Article-en

Assessing the Influence of Copper Oxide Nanoparticles Combined with Distilled Water on PVT System Performance

M. Ghaderi; P. Salami; H. Samimi-Akhijahani; S. Zareei; M. Safvati

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 ... Read More

Research Article-en

Investigation of the Structural and Physicomechanical Properties of Edible Sodium Carboxymethyl Cellulose Based Bilayer and Composite Films Containing Walnut Oil Emulsion Stabilized with Chia Seed Gum

A. Nahalkar; A. Rajaei; H. Mirzaee Moghaddam

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 ... Read More

Research Article-en

An Assessment of the Potential of Multispectral Sentinel-2 Satellite Imagery for Detecting Dubas Bug Infestations in Date Palm Cultivation Regions

H. Karimi; M. J. Assari; F. Ranjbar-Varandi

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, ... Read More 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

Prediction of SPAD Values Using Dominant Wavelength in Mung Bean Microgreens

R. Külcü; A. Süslü

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 ... Read More

Research Article-en

Using the Response Surface Methodology to Predict the Effect of Different Moisture Levels on the Bulk Density and Penetration Resistance of Soil Under Different Operating Conditions

M. ALmoosa; S. Al-Atab; S. Almaliki

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 ... Read More 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.

Research Article-en

Non-destructive Internal Quality Evaluation of Apple Fruit Using X-ray CT

R. Khodabakhshian; R. Baghbani

Articles in Press, Accepted Manuscript, Available Online from 14 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.2025.90983.1317

Abstract

In this study, X-ray computed tomography (CT) as a non-destructive method for internal quality evaluation of apple fruit was investigated. For this purpose, three local apple fruit cultivars including: Red Delicious, Golden Delicious, and Golab were used. The CT number of the images, which indicates ... Read More

Research Article

Investigating the Effect of the Magnetic Field Generated by the Helmholtz Coil on Water Evaporation Rate in a Hot Air Convection Dryer

H. Mohammadinezhad; M. H. Aghkhani; H. Sadrnia

https://doi.org/10.22067/jam.2025.91869.1337

Abstract

IntroductionWater is a very important component of many food products and determines their physical properties, texture, sensory quality, and rate of chemical and microbiological reactions. Magnetic fields, as an emerging technological tool, have recently received increasing attention in the food industry ... Read More IntroductionWater is a very important component of many food products and determines their physical properties, texture, sensory quality, and rate of chemical and microbiological reactions. Magnetic fields, as an emerging technological tool, have recently received increasing attention in the food industry due to their strong permeability and non-contact nature. Studies have shown that magnetic fields weaken hydrogen bonds. Researchers reported that when the magnetic field strength increases, the refractive index of water increases by approximately 0.1%. Magnetic fields can also weaken the van der Waals bonds between water molecules. A similar type of magnet was used in another study for a magnetic field of 6 Tesla. They did not evaluate the evaporation rate, but rather some other properties using the air flow contact angle, and suggested that the magnetization of pure water requires air and the relative motion of the water against the magnetic flux. Previous experiments were conducted at room temperature. The effects of magnetic fields on water samples have been studied from various aspects and are still of interest to researchers in this field. The direction of air flow relative to the magnetic field gradient also affects the evaporation rate. However, some experiments are not well-defined, and their repetition will not be easily feasible. Therefore, a review of the literature on the effects of magnetic fields on water properties shows that there is still no coherent view on the mechanism of the effects of such fields. In this study, we focused on studying the effect of a static electromagnetic field with predefined intensities on the water evaporation rate, fields from 30 to 130 mT and a temperature range between 30, 50, and 70 °C with forced air movement at a uniform speed, and the continuous presence of samples in the electromagnetic field, which, to our knowledge, has not been reported before. To this end, the objectives of this study include: (1) quantitative determination of the evaporation rate as a function of the applied magnetic field; (2) finding the energy contribution to the evaporation rate in the presence of a magnetic field.Materials and MethodsTo create a magnetic field, two copper coils with a wire gauge of 1.25 mm, a core diameter of 110 mm, and 2500 turns were used. To measure the level of magnetism, the PHYWE Tesla meter with an accuracy of 10 microteslas and measurement range of 20 to 2000 mT, made in Germany, was used. To measure the weight of the samples at the desired intervals, the AND digital scale model GF6000 with a weighing capacity of 6000 grams and an accuracy of 0.01 grams, made in Japan, was used. For each of the tests, 40 milliliters of Type II distilled water were used in accordance with ASTM D1193 and ISO 3696 standards, with a conductivity of 0.1 μS.cm-1. Initially, to ensure uniform testing conditions, the device was operated for 15 minutes, after which the samples were placed in petri dishes with a diameter of 90 millimeters and a height of 11 millimeters at a constant temperature of 20 degrees Celsius and prepared for testing. After preparing the samples and the device, the prepared samples were placed inside the device and removed at 15-minute intervals for a duration of 120 minutes, then weighed using a scale with an accuracy of 0.01 grams. This process was carried out separately for each treatment, and the data were collected. The evaporation rate of the sample per unit time was calculated using the unit of milligrams per minute and the trend line equation. The slope of the obtained lines indicated the evaporation rate values. All the trend lines obtained had a coefficient of determination (i.e., linear correlation degree) equal to or greater than 0.99. We chose the magnetic field range of 30 to 130 mT because the working range of the magnetic field generator in the device fell within this range. The experiments were conducted using a factorial test based on a completely randomized design with two replications. The first factor was the intensity of the electromagnetic field at four levels: 0, 30, 60, and 130 mT; the second factor was temperature at three levels: 30, 50, and 70 degrees Celsius; and the third factor was time at eight levels: 15 to 120 minutes. The means were compared at the 5% significance level using Duncan's test. For this purpose, SAS software version 9.2 was used, and Excel 2016 was used for plotting the graphs.Results and DiscussionsThe samples were placed in the field generated by the Helmholtz coil, and the results confirmed the effect of the magnetic field on the water evaporation rate. It was demonstrated in a study that, although increasing temperature and decreasing humidity are the dominant factors affecting the rate of water evaporation, a stationary magnetic field with decreasing temperature has an increasing effect on the evaporation rate. This finding contradicts the results of the present study, where the experimental data indicate an increased impact of the magnetic field with rising temperature levels. Considering the results of the analysis of variance, all factors along with their two-way and three-way interactions were significant at the one percent level.Based on Duncan's multiple range test, for duration, magnetic intensity, and temperature, with the increase in each factor level, the weighted evaporation values of the samples significantly decreased compared to the previous factor level. All the trend lines obtained had a coefficient of determination (i.e., linear correlation degree) equal to or greater than 0.99. The slope of the line equation between weight and time is equal to the evaporation rate (R). From the evaporation rates obtained from experimental data, it is clear that the correlation with temperature is not linear, but rather an exponential function as:The above model can behave like a linear model. The parameter estimates of the model were obtained using the SPSS software as:The final model can be expressed in the following form:At a temperature of 30 degrees Celsius, the energy consumption decreased by 11.4 kJ with the increase of magnetic levels. At temperatures of 50 and 70 degrees Celsius, the reduction in energy consumption with the application of a magnetic field was observed to be 48.3 and 45.2 kJ per gram, respectively. These results demonstrate the effect of magnetism on optimizing energy consumption at different temperature levels, with 50 degrees Celsius and a magnetic field intensity of 130 mT being the optimal conditions in terms of energy consumption.ConclusionIn this study, a statistical approach was used to investigate the rate of water evaporation under different magnetic fields and temperatures over a specified period. The results indicated that the magnetic field, like temperature, affects water evaporation, and as the field increased, the rate of water evaporation also rose. Specifically, the evaporation rates in the treatments at 30, 50, and 70 degrees Celsius after 120 minutes without applying the magnetic field were 43.7%, 53.3%, and 66.5% of the initial weight of the sample, respectively. After applying the magnetic field from 0 to 130 mT, the evaporation rates were reported as 59.6%, 82.8%, and 94.7% of the initial sample weight, respectively, indicating an increase in the evaporation rate with the application of the magnetic field. Finally, a model was proposed that accurately predicts this trend and can be utilized. The analysis of the energy consumption results for each treatment also showed that the magnetic field can influence the total energy consumption for water evaporation and optimize energy use, with reductions of 14.6% at 30 degrees Celsius, 26.55% at 50 degrees Celsius, and 22.5% at 70 degrees Celsius.AcknowledgmentsThe present study pertains to research project number 60993 approved by Ferdowsi University of Mashhad, and it acknowledges the efforts of Dr. Mohammad Farkhari (Associate Professor of Plant Breeding at the University of Agricultural Sciences and Natural Resources of Khuzestan) and Dr. Omid Doosti Irani, alumnus of the Biosystems Engineering Department at Ferdowsi University of Mashhad.

Research Article

Detection of Cucumber Fruit on Plant in a Greenhouse Environment Using the YOLOv8 Object Detection Algorithm

A. Soleimanipour

https://doi.org/10.22067/jam.2025.92068.1339

Abstract

IntroductionThe increasing demand for automation in agriculture, particularly for repetitive and labor-intensive tasks, has driven the development of robotic harvesting systems. Recent advances in computer vision, deep learning, and the availability of large image datasets have made it possible to create ... Read More IntroductionThe increasing demand for automation in agriculture, particularly for repetitive and labor-intensive tasks, has driven the development of robotic harvesting systems. Recent advances in computer vision, deep learning, and the availability of large image datasets have made it possible to create robust object detection models for agricultural applications. Traditional harvesting methods, such as bulk harvesting, often lead to fruit damage and loss owing to non-selective picking. Selective harvesting, particularly with the use of robotic systems, offers a promising alternative by combining the precision of human labor with the efficiency of automation. This study presents a deep learning-based model for detecting cucumber fruits on plants in a real greenhouse environment, which is an essential step towards developing autonomous harvesting robots that selectively pick ripe cucumbers.Materials and MethodsA dedicated image dataset was curated in a commercial greenhouse, comprising 300 images of cucumber plants captured under various lighting conditions (morning, noon, and evening), to ensure robustness against real-world variability. Images were manually labeled to identify the cucumber fruits and their pedicels. To enhance the model training and prevent overfitting, data augmentation techniques were applied to the training set. Several architectures of the YOLO (You Only Look Once) object detection algorithm were evaluated, including the nano-scale versions YOLOv5n and YOLOv8n, and the small-scale YOLOv8s, in addition to the RT-DETR model.The YOLOv8 algorithm is known as one of the state-of-the-art algorithms in computer vision because of its high speed, detection accuracy, and adaptability. The YOLOv8 architecture consists of three main parts: backbone, neck, and head, which are responsible for extracting image features, combining and enriching features, and predicting bounding boxes and object classes, respectively.These models were trained, and their performances were compared based on the detection accuracy and inference time metrics. Training and evaluation were conducted using a suitable computational platform.Results and DiscussionThe performances of different YOLO models and RT-DETR were rigorously evaluated. The results demonstrated that the YOLOv8n model achieved the highest detection accuracy of 87.5%, surpassing the performances of the other tested models. Importantly, the YOLOv8n model also exhibited a favorable balance between the accuracy and inference time, making it suitable for real-time applications. The analysis considered the trade-off between the number of parameters and detection speed, highlighting the efficiency of YOLOv8n.The YOLOv8n model demonstrated superior performance in terms of pedicel detection accuracy compared to YOLOv5n, achieving a fitness score of 91.08% (calculated as a weighted average of mAP@50 and mAP@50-95). While exhibiting strong performance in fruit and pedicel detection (Figure 6), the sensitivity of the model for pedicel detection (88.0%) was comparatively lower than that for fruit detection (96.1%). The highest F1 score (0.89) was observed at a confidence level of 39.5%, indicating the effectiveness of the model in balancing the precision and recall for pedicel detection. Overall, YOLOv8n outperformed the other tested models in identifying the class and location of the fruit pedicel. The superior performance of YOLOv8n can be attributed to its architectural advancements and optimized training processes.ConclusionThis study successfully developed a deep learning-based model for accurate and efficient cucumber fruit detection in a greenhouse environment. The YOLOv8n model demonstrated superior performance compared with the other evaluated architectures, achieving a detection accuracy of 87.5% while maintaining a good processing speed. These findings suggest that the YOLOv8n model has significant potential for integration into autonomous vegetable harvesting robots, contributing to the automation of agricultural processes and increased efficiency in greenhouse operations. Future works should explore further optimization and testing under diverse environmental conditions.

Research Article

Multivariate Optimization of Moldboard Plow Tillage Quality Using Response Surface Methodology

M. Akbari; I. Hazbawi; M. Jafarian

https://doi.org/10.22067/jam.2025.92680.1357

Abstract

IntroductionTillage of rainfed lands is performed using moldboard plows to a depth of 30 cm. Due to the influence of soil surface roughness and crop residues on moisture absorption and erosion reduction, investigation of the relationship between tillage implements’ performance and the aforementioned ... Read More IntroductionTillage of rainfed lands is performed using moldboard plows to a depth of 30 cm. Due to the influence of soil surface roughness and crop residues on moisture absorption and erosion reduction, investigation of the relationship between tillage implements’ performance and the aforementioned factors is essential. Therefore, considering the importance of preserving precipitation and preventing soil erosion, this study was conducted to investigate and optimize the effects of forward speed and tillage depth on soil surface roughness and the percentage of buried crop residue using response surface methodology.Materials and MethodsThis research was conducted in the Khomeyn region, Iran during the 2023-2024 growing season, utilizing a moldboard plow and an MF399 tractor. The objective was to investigate the effects of plowing depth and speed on soil surface roughness and the burial of plant residues. Soil surface roughness was measured using a pin meter, while the percentage of burial of plant residues was determined using image processing techniques and ImageJ software. Wheat straw residue with an initial moisture content of 8-9% was uniformly distributed at a rate of 100 g m-2 along the designated paths. Images were captured before and after the tillage operation for subsequent processing and analysis.To optimize the process, a central composite design (CCD) with three levels of speed (5, 7.5, and 10 km h-1) and three levels of tillage depth (17.5, 22.5, and 27.5 cm) was employed. The objective was to determine the optimal factor levels for maximizing surface roughness and minimizing residue burial. Data were analyzed using a second-order model and Design Expert V11 software. The best model was selected based on statistical criteria.Results and DiscussionModeling soil surface roughness and crop residue incorporation revealed that the second-order regression model, with high coefficients of determination (R2 = 0.983 and 0.96), was capable of accurately predicting these indices. The interaction effects of tillage speed and depth were significant (P < 0.01). In this study, the effect of tillage depth on soil surface roughness was greater than that of tractor speed. The regression model indicated that tillage depth plays a primary role in the amount of crop residue incorporation. Moldboard plowing demonstrated that increasing depth, particularly at high speeds, leads to increased roughness and residue incorporation, whereas increasing speed, especially at shallow depths, reduces roughness and increases incorporation. The maximum roughness was observed at the deepest tillage depth and lowest speed, while the shallowest depth and highest speed resulted in the minimum roughness.Tillage depth and speed influence soil surface roughness and bulk density. Higher speeds decrease furrow depth and ridge height; thus, lower speeds are recommended for creating greater roughness. The highest residue incorporation (85%) was achieved at a depth of 27.5 cm and speeds of 5 and 10 km h-1, while the lowest (70%) occurred at a depth of 17.5 cm and a speed of 5 km h-1. Depth was more influential than speed, and nonlinear models are necessary for more accurate modeling. The developed model, with a desirability of 81%, provides the maximum roughness (10.96 cm) and minimum residue incorporation (69.34%) for a moldboard plow at a speed of 5 km h-1 and a tillage depth of 17.5 cm.ConclusionThis study investigated the effects of conventional tillage methods in dry land areas on soil surface roughness and the extent of crop residue burial. The results indicate that increasing tillage depth leads to an increase in both indices, while reducing tractor speed increases roughness and decreases residue burial. The optimization model revealed that at a speed of 5 km h-1 and a depth of 17.5 cm, minimum roughness and maximum residue incorporation can be achieved. To improve regional tillage practices, it is advised to conduct further research into the long-term effects of different tillage systems. This effort will ensure a well-informed selection and implementation of the most effective methods.AcknowledgmentThe authors gratefully acknowledge the financial support provided by the University of Lorestan.

Research Article-en

The Evaluation of Lime Juice Adulteration by Comparing Cyclic Voltammetry and Electronic Tongue Methods

Gh. Bahrami; M. H. Aghkhani; M. R. Golzarian; B. Deiminiat

https://doi.org/10.22067/jam.2023.83040.1173

Abstract

The present study investigated the use of the cyclic voltammetric electrochemical method and the electronic tongue (e-tongue) method for detecting adulteration in lime juice. Since the measurement of citric acid content in lime juice is an accepted indicator of lime juice adulteration in laboratories, ... Read More

Research Article

Evaluating the Effects of Grape Harvest Time and Vacuum Drying on the Physicochemical Properties of White Seedless Quchan Raisin Cultivar

F. Kiumarsi Darbandi; Y. Selahvarzi; B. Abedy; M. Kamali; H. Sadrnia

https://doi.org/10.22067/jam.2024.87715.1241

Abstract

IntroductionVarious methods have been used to dry grapes. The main purpose is to increase shelf life, produce high-quality dried grapes, and also produce raisins to reduce post-harvest losses. Different methods can be used to dry grapes. Sun drying is the method traditionally used to dry commercial raisins. ... Read More IntroductionVarious methods have been used to dry grapes. The main purpose is to increase shelf life, produce high-quality dried grapes, and also produce raisins to reduce post-harvest losses. Different methods can be used to dry grapes. Sun drying is the method traditionally used to dry commercial raisins. However, this process is very slow and depends mainly on weather conditions, which can cause microbial and insect contamination in dried fruits and hence, reduce their quality. Recently, advanced vacuum drying techniques have been used in order to increase the amount of water removal and ensure better quality of raisins. Vacuum drying (VD) is a process in which wet materials are dried under subatmospheric pressure. Vacuum pressure reduction increases the mass of water between the fruit and its surroundings, thereby reducing the heat needed for rapid drying. Therefore, vacuum drying is a promising technology for drying grapes and has been used in current works. Preserving the quality of raisins and maintaining their essential nutritional indicators is a vital aspect of effective management strategies aimed at enhancing product quality. This improvement boosts demand for raisins in both domestic and international markets. Finding new methods of drying while maintaining the desired quality and preventing contamination are other factors that determine the quality of raisins. On the other hand, it is very important to determine the right time to harvest grapes according to the climatic conditions of each region and its effect on the quality of raisins. For this purpose, in this study, some quantitative, qualitative, and nutritional indicators related to raisins were compared between the sun-dried and vacuum drying methods for the white Quchan cultivar, evaluating the potential of each method in this field.Materials and MethodsThis research was conducted in 2021-2023 in one of the vineyards of the Quchan region in Iran. Quchan city is located within the geographical coordinates of 36 to 37 degrees north latitude and 58 degrees 10 minutes to 58 degrees 58 minutes east longitude. The relative humidity of this city is 40% in summer, 65% in spring, and 60% in autumn. Based on 10-year statistics, the average annual rainfall in this area is 274 mm. This research project was done in the form of a split plot, based on a randomized complete block design with four replications. Experimental factors include three harvesting times (August 27th, September 6th, and 16th) and four modes of drying (sun drying, and vacuum drying at 60, 70, and 80 °C). Fruits were harvested at three different stages, with time intervals of 10 days from August 27 to September 16, based on the sugar content in the pods and the ratio of total soluble solids (TSS) to titratable acidity (TA). At each harvest time, the grapes were dried in four different ways. In the first method, the grapes were dried traditionally in the open environment and in front of the sunlight. In the second method, the grapes were dried using a vacuum system at three different temperatures of 60, 70, and 80 °C.Results and DiscussionIn general, the interaction of harvesting time and drying method had a significant effect on most of the studied traits. The grape drying methods employed in this research significantly influenced the levels of phenolic compounds, flavonoids, and the antioxidant capacity of the resulting white seedless raisins. The amount of these compounds in sun-dried raisins was lower than the raisins produced using the vacuum drying method. The interaction effect of harvesting time and drying method on the production raisin yield was significant at the 1% probability level. The highest yield was related to the third harvest under the vacuum dryer at 60 °C (305.52 g kg-1), and the lowest yield was related to the first and second harvests with an average of 270.29 g kg-1 in the sun-dried method. In general, the highest amount of TSS was related to the treatments of the third harvest, which was observed in vacuum drying at 60 °C. After that, no significant difference was observed in temperatures of 70 and 80 °C. The amount of antioxidant, phenol, flavonoid, and total sugar content in the vacuum drying treatment was higher than the sun drying method. The total soluble sugars in sun-dried raisins were, on average, 22.68% lower compared to those dried using the vacuum method. In terms of total microbial count, the highest microbial load (126.51 Cfu g-1) was related to sun-dried raisins. The treatments under vacuum drying at all three temperatures of 60, 70, and 80 °C showed the lowest amount of microbial load (almost zero). The low level of microbial contamination in raisins produced by the vacuum method in this research can be attributed to the short drying time and also the lack of contact with the surrounding environment.ConclusionVacuum drying is a new technology that has been developed in recent years, employing a lower pressure in the chamber to increase the moisture transfer during the drying process. In this method, due to the lack of oxygen in the environment, some undesirable biochemical reactions such as browning, oxidation, and degradation reactions are reduced. In addition, the periodic pressure change can create fissured and porous structures in the skin of the sample, thereby increasing the mass transfer through the pores. Overall, the results of this research showed that the raisins produced in the third harvest and using vacuum drying at 60 °C had better quality than other treatments in terms of biochemical and sensory characteristics, including flavor, texture, and color. It can also be concluded that the vacuum drying method is a good alternative to traditional drying methods.

Publication start year	2011
Number of Volumes	15
Number of Issues	36
Number of Authors	901
Number of submissions	1,306
Number of Reject Articles	715
Number of Accept Articles	548
Number of Reviewers	423

Volume 15 (2025)

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Volume 6 (2016)

Volume 5 (2015)

Volume 4 (2014)

Volume 3 (2013)

Volume 2 (2012)

Volume 1 (2011)

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