Research Article-en Post-harvest technologies

Artificial Neural Network (ANN) Modeling of Plasma and Ultrasound-assisted Air Drying of Cumin Seeds

M. Namjoo; M. Moradi; M. A. Nematollahi; H. Golbakhshi

Volume 15, Issue 1 , March 2025, Pages 1-22

https://doi.org/10.22067/jam.2024.85744.1209

Abstract

In this study, the air drying of cumin seeds was boosted by cold plasma pre-treatment (CPt) followed by high-power ultrasound waves (USp). To examine the impact of included effects, different CP exposure times (0, 15, and 30 s), sonication powers (0, 60, 120, and 180 W), and drying air temperatures (30, ... Read More

Research Article-en Bioenergy

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life Cycle Assessment Modification of Corn Production in Lorestan Province, Iran

M. Soleymani; A. Asakereh; M. Safaeinejad

Volume 15, Issue 1 , March 2025, Pages 23-46

https://doi.org/10.22067/jam.2024.86234.1221

Abstract

Optimal use of resources, including energy, is one of the most important principles in modern and sustainable agricultural systems. Exergy analysis and life cycle assessment were used to study the efficient use of inputs, energy consumption reduction, and various environmental effects in the corn production ... Read More

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

IoT Stingless Bee Colony Monitoring System

R. J. Arendela; R. A. Ebora; E. Arboleda; J. L. M. Ramos; M. Bono; D. Dimero

Volume 15, Issue 1 , March 2025, Pages 47-63

https://doi.org/10.22067/jam.2024.86261.1222

Abstract

The IoT monitoring system for stingless bee colonies aims to provide real-time information about temperature, humidity, and hive weight in response to the issue of colony collapse disorder (CCD) caused by human intervention in beekeeping. It also aims to improve the current monitoring methods for the ... Read More

Research Article-en Image Processing

Diagnosis and Classification of Two Common Potato Leaf Diseases (Early Blight and Late Blight) Using Image Processing and Machine Learning

H. Koroshi Talab; D. Mohammad Zamani; M. Gholami Parashkoohi

Volume 15, Issue 1 , March 2025, Pages 65-79

https://doi.org/10.22067/jam.2024.86571.1226

Abstract

Diagnosing plant diseases is an important part of crop management and can significantly affect the quantity and quality of production. Traditional methods of visual assessment by human observers are time-consuming, costly, and error-prone, making accurate diagnosis and differentiation between various ... Read More

Research Article-en Design and Construction

Evaluations of Cereal Combine Harvester Head Attachment for Harvesting of Sunflower and Comparison with Conventional Harvesting Methods

M. Safari; P. Ghiasi; A. Rohani

Volume 15, Issue 1 , March 2025, Pages 81-93

https://doi.org/10.22067/jam.2024.86827.1229

Abstract

In Iran, more than 50,000 hectares of sunflowers (oil and nuts) are cultivated annually. Conventional grain combine harvesters are not compatible with the unique characteristics of sunflowers, leading to significant grain losses during harvesting. Therefore, it is currently being harvested manually. ... Read More

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

Developing a Service Management Framework in the Agricultural Supply Chain with Fuzzy Weighted Average

M. Zangeneh

Volume 15, Issue 1 , March 2025, Pages 95-113

https://doi.org/10.22067/jam.2024.87618.1239

Abstract

The main objective of this research is to create a comprehensive and adaptable framework for assessing performance in agricultural supply chains and develop two improving approaches. The most relevant performance measures are selected to assess the current status of services in agricultural supply chains ... Read More

Research Article-en Post-harvest technologies

Qualitative Analysis of Apple Fruit during Storage using Magnetic Resonance Imaging

R. Khodabakhshian; R. Baghbani

Volume 15, Issue 1 , March 2025, Pages 115-127

https://doi.org/10.22067/jam.2024.87861.1243

Abstract

Magnetic resonance imaging (MRI) is a non-destructive technique for determining the quality of fruits which, with different protocols, shows the density and structure of hydrogen atoms in the fruit in which it is placed. This study compared MRI images of healthy and bruised apple flesh tissues, both ... Read More

Research Article-en Image Processing

Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method

H. Bagherpour; F. Fatehi; A. Shojaeian; R. Bagherpour

Volume 15, Issue 1 , March 2025, Pages 129-144

https://doi.org/10.22067/jam.2024.87830.1244

Abstract

In some countries, people commonly consume hazelnuts in their shells to extend shelf life or due to technological limitations. Therefore, open-shell hazelnuts are more marketable. At the semi-industrial scale, open-shell and closed-shell hazelnuts are currently separated from each other through visual ... Read More

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

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

Articles in Press, Corrected Proof, Available Online from 02 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.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

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

Articles in Press, Corrected Proof, Available Online from 26 February 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.2023.81221.1150

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

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

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

Articles in Press, Corrected Proof, Available Online from 05 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.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, Construction, and Evaluation of a Spatial Depth Measurement System for Subsoiler in Sugarcane Fields

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

Articles in Press, Corrected Proof, Available Online from 23 February 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.2024.87809.1242

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

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

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

Articles in Press, Corrected Proof, Available Online from 24 February 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.2024.90273.1295

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.

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

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

Introduction Planting 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 Introduction Planting 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 Methods Conventional 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 Discussion The 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. Conclusion Given 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.

View Article

Publication start year	2011
Number of Volumes	15
Number of Issues	35
Number of Authors	830
Number of submissions	1,250
Number of Reject Articles	679
Number of Accept Articles	524
Number of Reviewers	410

Volume 15 (2025)

Volume 14 (2024)

Volume 13 (2023)

Volume 12 (2022)

Volume 11 (2021)

Volume 10 (2020)

Volume 9 (2019)

Volume 8 (2018)

Volume 7 (2017)

Volume 6 (2016)

Volume 5 (2015)

Volume 4 (2014)

Volume 3 (2013)

Volume 2 (2012)

Volume 1 (2011)

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Indexing and Abstracting

Keywords Cloud

Related Journals