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Selecting the appropriate tractor for small-scale farms is a complex process due to the multitude of technical, environmental, and economic criteria that must be evaluated. This study addresses this challenge by integrating the Analytic Hierarchy Process (AHP) with machine learning (ML) to reduce the number of criteria and simplify the decision-making process. The research aims to determine the most relevant criteria aligned with sustainable development goals for selecting the right tractor, focusing on small farms in the Egyptian Delta. Four tractors, with horsepower ranging from 55 to 95, were evaluated based on inputs from forty-two governmental service providers in the study area. Initially, nine criteria were identified, encompassing key technical, environmental, and economic factors. These criteria were reduced to three—price, power, and maintenance costs by weights 0.142, 0.334, and 0.525, respectively—using Hierarchical Agglomerative Clustering with Euclidean distance. This reduction streamlined the selection process, making it more practical for farmers. Results show that the second tractor (T2), with a priority score of 0.326 and a normalized value of 33.4%, emerged as the optimal choice for small-scale farmers, outperforming the first tractor (T1) (28.7%) and third tractor (T3) (21%). Integrating AHP and ML simplifies tractor selection, ensuring sustainability, cost-efficiency, and operational effectiveness. [ABSTRACT FROM AUTHOR]

Coverage path planning is a central task in agricultural field operations such as tillage, planting, cultivation, and harvesting. In future visions, manual operation will be replaced by fleets of autonomous agricultural vehicles that perform the tasks autonomously. A step towards this transition is to enable simultaneous and safe cooperation of autonomous vehicles on the field. In this article a novel approach is presented for coverage path planning (CPP) for two autonomous tractors that perform sequentially dependent tasks simultaneously on the same area. The approach is based on the idea of computing the coverage solutions for each task by dividing them into short paths that consist of a swath and a turn. The approach ensures collision avoidance by examining that the simultaneous short paths, operated by different tractors, do not collide geometrically, and then schedules them to be operated simultaneously in real-time. The approach was demonstrated successfully in a real-world test environment with two autonomous tractors. The tractor that performed the first task was equipped with a disc cultivator and the second tractor was equipped with a seed drill. A test area of 0.8 ha was used for the demonstration drive, during which the tractors drove 22 swaths simultaneously. Both tractors completed their respective tasks. • We present the problem of sequentially dependent coverage path planning. • Sequentially dependent coverage tasks are performed simultaneously on the same area. • A novel algorithm for solving this problem for two autonomous tractors. • The algorithm solves and schedules non-conflicting paths in real-time online. • Successful collision-free completion of autonomous operation in a field test. [ABSTRACT FROM AUTHOR]

To enhance the precision and efficiency of the tractor-failure-rate and equipment-quality inspection, the present study introduces a wireless rapid detection method for assessing tractor quality. For this study, which was based on the symmetrical structural characteristics of tractors, we designed a magnetic suction accelerometer. The test system was composed of a wireless router, a magnetic suction accelerometer sensor, a data-acquisition terminal, and other components. This test system aimed to test the equipment quality of the tractor at idle speed before leaving the factory. The experiment found that the vibration characteristics of the tractor had a symmetrical pattern on the left and right sides of the front and rear axle at idle. When the idle speed of the tractor was 800 r/min and 1000 r/min, the predominant vibration direction of both sides of the front axle of the tractor was the Y direction, while the predominant vibration direction of the rear axle was the Z direction. The experimental results showed that the proposed wireless rapid detection method of tractor quality and the designed acceleration sensor had good testing accuracy. The present study could provide a novel rapid detection method for the failure detection of power machinery in the agricultural field and for inspection before leaving the factory. The implementation of the method could improve the detection efficiency, and reduce the detection cost and the incidence of failure during actual use. [ABSTRACT FROM AUTHOR]

Tractor condition recognition has important research value in helping to understand the operating status of tractors and the trend of tillage depth changes in the field. Therefore, this article presents a method for recognizing tractor conditions, providing the basis for establishing the relationship between tractor conditions and the tillage depth of the attached agricultural machinery. This study designed a tractor condition recognition method based on neural networks. Using real-world vehicle data to establish a data set, K-means clustering analysis was used to label the data set based on four conditions: "accelerated start", "constant speed", "decelerated stop" and "turning". The learning vector quantization (LVQ) neural network and the VGG-16 model of a CNN were selected for use recognizing the tractor conditions. The results showed that both the neural networks had good recognition effects. The average accuracy rates of the VGG-16 model of CNN and LVQ neural network were 90.25% and 79.7%, respectively, indicating that these models could be applied to tractor condition recognition and provide theoretical support for the correction of angle detection errors. [ABSTRACT FROM AUTHOR]

Productivity is one of the most important measures used to determine the growth and development level of countries or sectors. A wide variety of projects have been planned and implemented to increase agricultural productivity. The productivity to be obtained in agriculture; Soil conditions, climate, seeds, fertilizer, pesticides, labor and agricultural mechanization directly affect it. Agricultural mechanization is the realization of agricultural activities by using energy together with agricultural tools and machines. Agricultural mechanization; It is an important agricultural production technology that helps increase agricultural productivity. Due to the inadequate maintenance planning of agricultural machinery, agricultural machinery cannot be utilized at the desired level in agricultural production. Most agricultural equipment is subject to frequent changes in speed and direction of movement while operating. Damage that can be seen on a single machine; It also causes other machines to malfunction. During the year, especially in the months when agricultural activity is high, excessive working tempo can cause tractors to malfunction. The breakdown of tractors causes disruptions in agricultural activities. In addition, the breakdown of tractors increases the repair costs. Since there is no tractor maintenance planning, farmers face interruptions in agricultural activities due to tractor malfunction. However, tractor malfunctions may cause cost and economic losses. For these reasons, there is a need for appropriate maintenance planning of agricultural machinery in order to continue agricultural activities without disruption. Maintenance planning; It consists of a set of preventive activities to improve the reliability and availability of any system. The main purpose of this study is to determine and rank the importance level weights of the criteria that are important for agricultural machinery maintenance planning using the fuzzy AHP method. Fuzzy AHP method, which provides ease of application, was preferred in determining the Criterion Weights. The research proposes a framework to determine the weights of appropriate criteria for care planning selection through a combined approach of fuzzy multi-criteria decision making involving relevant stakeholders. On the basis of the prioritization of criteria of tractor maintenance planning (TMP), it was found from the ranking that checking for all fluid levels (TMP1) ranked first. This respectively is followed by checking for general conditions (TMP4), checking for tires and wheels (TMP2) and checking for batteries (TMP3). With the results of the study, a guide was created for farmers and other stakeholders, as well as decision makers, to help plan the maintenance of machines in better working conditions. It is also thought that this study will be encouraging for other studies. [ABSTRACT FROM AUTHOR]

Optimizing the design and operational parameters for tillage tools is crucial for improved performance. Recently, artificial intelligence approaches, like ANN with learning capabilities, have gained attention for cost-effective and timely problem solving. Soil-bin experiments were conducted and data were used to develop ANN and regression models using gang angle, velocity ratio, soil CI, and depth as input parameters, while tractor equivalent PTO (PTOeq) power was used as an output. Both models were trained with a randomly selected 90% of the data, reserving 10% for testing purposes. In regression, models were iteratively fitted using nonlinear least-squares optimization. The ANN model utilized a multilayer feed-forward network with a backpropagation algorithm. The comparative performance of both models was evaluated in terms of R2 and mean square error (MSE). The ANN model outperformed the regression model in the training, testing, and validation phases. A well-trained ANN model was integrated with the particle-swarm optimization (PSO) technique for optimization of the operational parameters. The optimized configuration featured a 36.6° gang angle, 0.50 MPa CI, 100 mm depth, and 3.90 velocity ratio for a predicted tractor PTOeq power of 3.36 kW against an actual value of 3.45 kW. ANN–PSO predicted the optimal parameters with a variation between the predicted and the actual tractor PTOeq power within ±6.85%. [ABSTRACT FROM AUTHOR]

This project combined systems engineers, farm safety researchers, work health and safety inspectorate and policymakers with the aim of designing a way in which to reduce fatal farm injury caused by run-overs and roll-overs by tractors and side-by-side vehicles. The team made comparisons between farm machinery and powered mobile plant that is used in the industrial manufacturing, warehousing and logistics, mining, and construction sectors. Current and emerging safety technologies and engineering solutions were collated. Safety standards, legislated engineering controls, retrofit designs, and known ways in which farmers' workaround safety features were considered. These elements were used as criteria to propose a way to resolve which safety technologies or engineering controls should be recommended for aftermarket retrofitting or incorporated at the original equipment manufacturer design stage. The concept of measuring safety effectiveness to prevent fatal farm injury emerged. This developed into a score sheet and a corresponding matrix to highlight engineering strength and industry acceptance. The project resulted in the conceptual design of the agricultural safety effectiveness score (ASES). The next phase is a multi-stakeholder validation process and a protocol for the scoring system. It requires a hypothesis to test the theory that when safety technologies and engineering solutions are mature in other industries or if they are associated with agricultural productivity gains, their adoption into the agricultural sector is more likely, which in turn will reduce the incidence of tractor and side-by-side run-overs and roll-overs on farms. [ABSTRACT FROM AUTHOR]

Accident is an unexpected event with negative consequences occurring unintentionally causes due to ignorance, lack of training and knowledge and unsuited design of implements. Ergonomics prioritizes design of safer machinery and tools for accident avoidance. To investigate about agricultural accidents surveys were conducted during the periods 2005-2007 and 2012-2014 throughout West Bengal to assess the magnitude, causes and severity of agricultural accidents through direct interviews of the victims and their related ones in case of fatal accidents with the help of developed questionnaire. Different ergonomic interventions were introduced to the agricultural workers to minimize the accidents. The total population in the periods 2005-2007 and 2012-2014 of the selected districts was recorded as 189940 including 53.6% male and 46.3% female and 297347 with 52.4% male and 47.6% female, respectively with total growth of 36.1% since 2007. Highly accident prone agricultural machinery includes thresher, power tiller, rotavator, chaff cutter, tractor etc. Accidents due to agricultural machinery, hand tools and other sources like snake bite, thunder were found to be 14.8%, 54.8% and 30.4%, respectively in 2005-2007 and 44.1%, 27.5% and 28.4%, respectively. The accident incidence rates due to hand tools was found to be decreased from 1.51 to 0.127 per 1000 hand tools due to increase of awareness about use of hand tools. But in the contrary, the accident incidence rates due to agricultural machinery was found to be increased over two mentioned periods from 1.28 to 2.62 per 1000 farm machines due to increased mechanization over the years. More awareness about the safe operation of agricultural machinery will decrease the accident incidence rate. [ABSTRACT FROM AUTHOR]

One of the leading causes of death in the word is the injury in the field of agriculture. Agricultural machinery, in fact, is very dangerous for workers and rollover accidents are due to several reasons. First, it must be considered that these machines operate on nonlinear land and on extremely steep slopes, so the causes are due to operational, tractor, and soil characteristics. Furthermore, recent studies have shown that in 33% of the rollovers that are analyzed, passive safety devices, such as seat belt, are not used by workers (who got thrown out of the safety zone). Another cause of fatal accidents is that, until now, the mechanical design of tractors has not provided for occupant protection. In fact, there are no standard tests that assess the safety of the occupant. This study aims to conduct an explicit finite element (FE) analysis of a rollover test of a generic T5 category tractor to assess the structural characteristics and the biomechanical performance of the occupant. [ABSTRACT FROM AUTHOR]

Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Operator fatigue during work with agricultural machinery is a significant factor contributing to fatal accidents in Greece. Workers operating agricultural machinery, especially those working with tractors and off-road machines, constitute one of the most hazard-prone groups due to mechanical vibrations transmitted from the ground to the operators' seats. Operators of tractors and off-road machines are exposed to intense mechanical vibrations, underscoring the importance of cumulatively calculating permitted working hours. This work presents a study that was conducted at the Laboratory of Safety and Ergonomics of Agricultural Machinery, Department of Agriculture - Agrotechnology, Faculty of Agricultural Sciences, University of Thessaly, in order to evaluate the vibrations generated when operators work with agricultural tractors and off-road machinery. The results of the study showed that the highest levels of vibration occurred during disc harrowing operation, particularly when the disc harrow moved vertically or at an angle of 30° to the ploughing direction. For seed bed preparation, it is recommended to use tractors equipped with a suspension system for the operator's cabin and a seat with an adjustable range of perceived vibration. Additionally, to prevent fatigue or health problems for tractor operators, it is advisable to limit permitted working hours to fewer than 8 hours per day. [ABSTRACT FROM AUTHOR]

Traditional tractors can only achieve steering through mechanical structures such as steering knuckles and steering trapezoids. Among them, the mechanical structure is more complex, and various parts are easily damaged, making the tractor malfunction. The four-wheel independent drive differential steering mode differs from the traditional Ackermann steering mode, which realizes steering by controlling the inner and outer wheel torque, which can accurately steer the working state of high-end agricultural machinery equipment and improve the operating efficiency of agricultural machinery equipment. Aiming at the dynamic control problem in the steering of electric tractor four-wheel independent drive, a layered control strategy based on the sliding mode control of yaw torque at the upper level and the optimal torque distribution level based on the mean load rate of vehicle tires at the lower was proposed. By analyzing the differential steering mechanism of a four-wheel independent drive, a dynamic model of differential steering of the electric tractor is established, and a dynamic controller of a four-wheel independent drive is designed according to the layered control strategy. The upper controller tracks and controls the expected yaw speed on the basis of the sliding mode control to track the driver's intention, and the lower controller realizes the optimal torque distribution based on the principle of the optimal average load rate of the vehicle tire to ensure the steering stability of the electric tractor. The effect of the controller was simulated and analyzed under typical conditions of double line shift, serpentine, and step. The results showed that the sliding mode controller is better than the PID controller in driver intention tracking. Compared with the average allocation strategy, the average maximum load rate of the vehicle tire under the three working conditions is reduced by 16.9%, 13.8%, and 17.3%, respectively, which proves the effectiveness of the layered control strategy. In the real car test, the sliding mode controller is better than the PID controller in the driver intention tracking. This study has important guiding significance for improving the maneuverability and stability of electric tractors. [ABSTRACT FROM AUTHOR]

Objective: the objective of the study was to know the current state of the national fleet of agricultural machinery. Design/Methodology/Approach: an estimate of the tractor fleet was made by adding the number of tractors with one year of lag, plus the number of tractors from national sales, minus the number of tractors leaving the fleet due to the end of their useful life, the period from 2007 to 2027. Results: there is a downward trend in the tractor fleet in the period 2007 to 2027. If the downward trend continues, the tractor fleet will have decreased by 114 thousand units in 2027, compared to the 238 thousand existing in 2007. This means a drop of 52%, compared to the initial year, which would leave the fleet of tractors with 124 thousand units. Limitations/Implications of the study: the main limitation is the non-existence of official data after 2007. Therefore, in order to know the current state of the national fleet of tractors in Mexico, estimates such as the one carried out in this investigation are required. Findings/Conclusions: The estimate of the tractor industrial fleet in Mexico indicates that annually the number of tractors that are added is less than the number of obsolete tractors that leave the fleet, which indicates that the rate of mechanization will decrease in the future. To avoid such a trend, the Government is required to support investments in agricultural machinery. [ABSTRACT FROM AUTHOR]

A procedure is proposed for the appraisal of alloy components used in tractors, agricultural equipment, and roadbuilding machines. By this method, the grade of aluminum, iron, and copper alloy parts may be established. [ABSTRACT FROM AUTHOR]

Farmers in Catamayo Canton, Loja Province, who do not have agricultural machinery for soil preparation, hire mechanization services locally. The general objective of this research was to diagnose the use of agricultural machinery by mechanization-service providers in the parishes of San Pedro de la Bendita, Catamayo and El Tambo, through interviews and surveys of 9 mechanization-service providers and 12 farmers. The research was field-based, cross-sectional and descriptive. The mechanization-service providers are small farmers who maintain their tractors and implements personally and consider that the use of machinery is due to the predominant soil texture in the canton. The mechanization indexes determined indicate the existence of a very diverse crop pattern and soil aeration is necessary for better yields: clay texture and the presence of stone is predominant in the area. The most used implements in the soil preparation are disk plow, furrower and harrow and tractors have an average power of 95 hp, of varied brand and year of manufacture 1987-2019. The group of mechanization-service providers served 610 producers corresponding to an equal number of production units in 2019 with a range of 20-500 ha. There is a ratio of 142.09 ha/tractor, as well as seven tractors/100 ha, the area harvested with machinery is 0% and the power used per area is 0.42 kW/ha. [ABSTRACT FROM AUTHOR]

Agricultural mechanization plays a major role in food production. Its proper implementation requires knowing the indicators that affect its performance. The aim of the present investigation was to evaluate the main mechanization indices of Aldeia Nova Farm in Cela Municipalty. For this, the execution of the study consisted of a non-experimental descriptive investigation, which was divided into two parts. The first consisted of collecting personal data for the operation of the machine and tractor park, maintenance and repair, as well as production. Subsequentle, the mechanization indicators were determined by following methodological recommendations established by various authors. Within the results, the ratio values of tractors per hectare (0,008 tract ha-1), the ratio of average power per tractor (108,86 kW tract-1), the machines per tractor ratio (2,05), the ratio of arable hectares per tractor (126,5 ha tract-1) and the ratio of arable hectares per combine (631,25 ha col-1) were magnitudes studied that behaved outside the established. Finally, the level of mechanization of Aldeia Nova Farm was evaluated using the indices established for this purpose, and it was shown that it is low, since although the value of the available power per hectare (0,86 kW ha-1) is higher than the 0,75 kW ha-1 established in the specialized literature, the rest of the indicators register unfavorable magnitudes, except technical assistance indicators. [ABSTRACT FROM AUTHOR]

Identifying available farmland suitable for agricultural machinery is the most promising way of optimizing agricultural production and increasing agricultural mechanization. Farmland consolidation suitable for agricultural machinery (FCAM) is implemented as an effective tool for increasing sustainable production and mechanized agriculture. By using the machine learning approach, this study assesses the suitability of farmland for agricultural machinery in land consolidation schemes based on four parameters, i.e., natural resource endowment, accessibility of agricultural machinery, socioeconomic level, and ecological limitations. And based on “suitability” and “potential improvement in farmland productivity”, we classified land into four zones: the priority consolidation zone, the moderate consolidation zone, the comprehensive consolidation zone, and the reserve consolidation zone. The results showed that most of the farmland (76.41%) was either basically or moderately suitable for FCAM. Although slope was often an indicator that land was suitable for agricultural machinery, other factors, such as the inferior accessibility of tractor roads, continuous depopulation, and ecological fragility, contributed greatly to reducing the overall suitability of land for FCAM. Moreover, it was estimated that the potential productivity of farmland would be increased by 720.8 kg/ha if FCAM were implemented. Four zones constituted a useful basis for determining the implementation sequence and differentiating strategies for FCAM schemes. Consequently, this zoning has been an effective solution for implementing FCAM schemes. However, the successful implementation of FCAM schemes, and the achievement a modern and sustainable agriculture system, will require some additional strategies, such as strengthening farmland ecosystem protection and promoting R&D into agricultural machinery suitable for hilly terrain, as well as more financial support. [ABSTRACT FROM AUTHOR]

Dynamic muscular workload assessments of tractor operators are rarely studied or documented, which is critical to improving their performance efficiency and safety. A study was conducted to assess and model dynamic load on muscles, physiological variations, and discomfort of the tractor operators arriving from the repeated clutch and brake operations using wearable non-invasive ergonomic transducers and data-run techniques. Nineteen licensed tractor operators operated three different tractor types of varying power ranges at three operating speeds (4–5 km/h), and on two common operating surfaces (tarmacadam and farm roads). During these operations, ergonomic transducers were utilized to capture the load on foot muscles (gastrocnemius right [GR] and soleus right [SR] for brake operation and gastrocnemius left [GL], and soleus left [SL] for clutch operation) using electromyography (EMG). Forces exerted by the feet during brake and clutch operations were measured using a custom-developed foot transducer. During the process, heart rate (HR) and oxygen consumption rates (OCR) were also measured using HR monitor and K4b2 systems, and energy expenditure rate (EER) was determined using empirical equation. Post-tractor operation cycle, an overall discomfort rating (ODR) for that operation was manually recorded on a 10-point psychophysical scale. EMG-based maximum volumetric contraction (%MVC) measurements revealed higher strain on GR (%MVC = 43%), GL (%MVC = 38%), and SR (%MVC = 41%) muscles which in normal conditions should be below 30%. The clutch and brake actuation forces were recorded in the ranges of 90–312 N and 105–332 N, respectively and were significantly affected by the operating speed, tractor type, and operating surface (p < 0.05). EERs of the operators were measured in the moderate-heavy to heavy ranges (9–24 kJ/min) during the course of trials, suggesting the need to refine existing clutch and brake system designs. Average operator ODR responses indicated 7.8% operations in light, 48.5% in light-moderate, 25.2% in moderate, 10.7% in moderate-high, and 4.9% operations in high discomfort categories. When evaluated for the possibility of minimizing the number of transducers for physical workload assessment, EER showed moderate-high correlations with the EMG signals (rGR = 0.78, rGL = 0.75, rSR = 0.68, rSL = 0.66). Similarly, actuation forces had higher correlations with EMG signals for all the selected muscles (r = 0.70–0.87), suggesting the use of simpler transducers for effective operator workload assessment. As a means to minimize subjectivity in ODR responses, machine learning algorithms, including K-nearest neighbor (KNN), random forest classifier (RFC), and support vector machine (SVM), predicted the ODR using body mass index (BMI), HR, EER, and EMG at high accuracies of 87–97%, with RFC being the most accurate. Such high-throughput and data-run ergonomic evaluations can be instrumental in reconsidering workplace designs and better fits for end-users in terms of agricultural tractors and machinery systems. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Effective indoor testing on a four-poster rig of agricultural machinery should mimic the real-world environment while the machinery is in farming and transportation. The emerging load spectrum extrapolation and compilation are capable of speeding up the use of the indoor vibration testing of tractors. However, most ground load spectrum studies consider a particular type of ground rather than all the rough farmland conditions that tractors experience daily. Such a problem inevitably raises doubts about validating the load spectrum-based fatigue durability and reliability testing of tractors. For a remedy, this article proposes a CEEMDAN-POT (Peak Over Threshold) model to comprehensively build a full life-cycle ground load spectrum of tractor vibration with six ground conditions and different field operations. The study acquires the real four vertical acceleration signals from the front and rear axles of the tractor to collect representative vibration load data. Furthermore, the study refines the measured load data by proposing a CEEMDAN-Wavelet threshold method, which is proved to be effective for the load signal decomposition and denoising. Lastly, the study presents a time domain extrapolation method, integrating the sample principle of the POT model, the proper parameter estimation with the Generalized Pareto Distribution (GPD) function, and the POT super-threshold model. The statistical analysis implies that the produced load spectrum fully preserves the statistical features observed in the original one. After extrapolation, the overall distribution of the rainflow matrix becomes more consistent while the mean and amplitude of the spectrum data increase. This study unifies a load spectrum of tractors operating and transporting on various farm ground conditions, providing the real load data of the indoor four-poster rig test. [ABSTRACT FROM AUTHOR]

Hilly and mountainous areas are weak places for the development of agricultural mechanization in China. The way to improve the utilization rate of small agricultural machinery widely used in hilly and mountainous areas is of positive significance for optimizing resource allocation efficiency of agricultural production and ensuring food security supply. Taking microtillers as a representative tool, this study systematically analyzed the main factors affecting the utilization rate of small agricultural machines and its influencing mechanism. Then, based on the survey data of 4905 farmers in 100 counties in 10 hilly and mountainous provinces of China, empirical analysis was carried out by some econometric models, such as censored regression and the mediating effect model. Results show the following.: (1) Among farmers in hilly and mountainous areas, the average use time of each microtiller is 218.41 h per year. (2) Age, social identity, terrain conditions, crop types, land area, the number of microtillers, the number of large tractors, and the machinery purchase subsidy policy are the significant factors affecting the utilization rate of microtillers. (3) The increase of cultivated land area not only directly improves the utilization rate of microtillers, but also indirectly improves the utilization rate of microtillers due to the increase in quantity. [ABSTRACT FROM AUTHOR]

With the application of new energy technology, hybrid agricultural machinery has been developed. This article designs a hybrid tractor energy management method to solve the problem of high energy consumption caused by significant load fluctuation of the tractor in field operation. This article first analyzes the characteristics of the hydrogen fuel cell, power battery, and ultracapacitor and designs a hybrid energy system for the tractor. Second, the energy management strategy (EMS) of multi-layer decoupling control based on the Haar wavelet and logic rule is designed to realize the multi-layer decoupling of high-frequency, low-frequency, and steady-state signals of load demand power. Then, the EMS redistributes the decoupled power signals to each energy source. Finally, a hardware-in-loop simulation experiment was carried out through the model. The results show that, compared with single-layer control strategies such as fuzzy control and power-following control, the multi-layer control strategy can allocate the demand power more reasonably, and the efficiency of the hydrogen fuel cell is the highest. The average efficiency of the hydrogen fuel cell was increased by 2.87% and 1.2%, respectively. Furthermore, the equivalent hydrogen consumption of the tractor was reduced by 17.06% and 5.41%, respectively, within the experimental cycle. It is shown that the multi-layer control strategy considering power fluctuation can improve the vehicle economy based on meeting the power demanded by the whole vehicle load. [ABSTRACT FROM AUTHOR]

Protecting the soil, which serves as the basis for crop production, is a major challenge in view of the increasing weight of agricultural machinery. In the context of soil compaction, track depth is an important measure. As part of the ARDopt research project, the suitability of various ultrasonic sensors and photogrammetric methods for measuring the track depth was investigated. In addition, the influence of the parameters tire pressure, driving speed and soil moisture on the track depth was investigated. The continuous measurement of the track depth with commercially available ultrasonic sensors and the calculation of the track depth from digital surface models show a close correlation with the reference measurements. The tire pressure had the strongest influence on the measured track depth. Likewise, as expected, the influence of soil moisture on the track depth could be observed. [ABSTRACT FROM AUTHOR]

The current control accuracy of automatic navigation curve tracking in tractors cannot fully meet the production needs in modern agriculture. In this study, a tracking control system of variable curvature path was presented as the front wheel angle feedforward compensation. Firstly, a comprehensive evaluation was made on the influence of agricultural machinery operating speed and reference path curvature on the foresight distance. The lookahead area was then altered to compute the preview point, in order to realize the dynamic adjustment of the lookahead distance and the feedforward amount of the front wheel angle. Furthermore, the lookahead distance posed a significant effect on the speed of the vehicle. Specifically, the vehicle often traveled at a lower speed on the rugged and curved reference path, when the tractor was working on the field mechanized road or irregular fields. However, the lookahead distance was typically expressed as a linear function that related to the speed of the vehicle. The inaccurate tracking of the reference path was normally obtained due to the weak coupling, if only the speed of the vehicle without considering the curvature of the driving road on the lookahead distance. Therefore, the varying lookahead distance was proposed to depend on the curvature of the path. Meanwhile, the varying curve length of the preview point in the lookahead area was relative to the starting point of the lookahead area depending on the curvature of the reference path. Secondly, the steady-state error was often observed in the driving process of the agricultural machinery, because the pure pursuit algorithm failed to consider the deviation between the current pose and the reference path of the agricultural machinery, when tracking the preview point. An improved controller with the fuzzy control algorithm was designed to realize the compensation of the front wheel angle of agricultural machinery. Specifically, the lateral error and heading error of the agricultural machinery were used as the inputs of the fuzzy controller, and the compensation amount of the front wheel angle was used as the output. The sum of the feedforward and compensation amount of the front wheel angle were used as the control amount of the front wheel angle of the vehicle. This control amount considered the lateral error and heading error of the current position of the vehicle, together with the influence of the forward reference path on the steering of the agricultural machinery. The tracking accuracy was then greatly improved in the agricultural machinery. Taking the DF2204 continuously variable transmission tractor as the test platform, an automatic navigation system was developed to verify the practicability of the path tracking algorithm. 21 sets of variable curvature path tracking experiments were carried out in Beijing Miyun Experimental Field. The results indicate that the average absolute errors were 2.7, 2.7, 3.3, and 4.0 cm, and the average root errors were 3.4, 3.7, 4.6, and 5.0 cm, respectively, when the tractor moved at 1.0, 1.5, 2.0, and 3.0 m/s. The tracking control approach of variable curvature path in the autonomous navigation can be expected to effectively increase the tracking accuracy of agricultural machinery curve paths and the utilization rate of farmland. [ABSTRACT FROM AUTHOR]

A tractor electro-hydraulic hitch system is considered one of the most important systems that play a strategic role in the power transmission and operation depth control of a tractor's field operation. Its performance directly affects the operation quality of the whole work unit of the tractor. Furthermore, a tractor electro-hydraulic hitch system has gained the interest of many in the agricultural machinery sector because of its stable performance, high production efficiency, good operation quality and its low energy consumption. To fully benefit from the potential of the tractor electro-hydraulic hitch system, it is significant to understand and address the problems and challenges associated with it. This study, therefore, aims to contribute to the development of the tractor electro-hydraulic hitch system by investigating the research methods, technical characteristics and emerging trends in three key aspects that include the tillage depth adjustment method, the tillage depth control algorithm and the core components of the electro-hydraulic hitch system. The characteristics and applicable conditions of the different tillage depth adjustment methods of the electro-hydraulic hitch system were summarized. The realization methods and the control characteristics of the different algorithms were elaborated and discussed for both the PID control algorithm and the intelligent control algorithm. The working characteristics of the core components of the electro-hydraulic hitch system were analyzed based on the hydraulic control valves and sensing elements. The results have shown that the multi-parameter tillage depth adjustment method met the operation quality standard while taking the engine load stability and traction efficiency into account, and it has a greater research significance and value. The working quality can be improved effectively by introducing the intelligent algorithm. In addition, the study of smart valves with built-in sensing elements and how to improve the anti-interference ability of sensing elements, are the aspects that requires further consideration. Aiming to improve the working quality and reduce energy consumption, further research into the tractor electro-hydraulic hitch system is necessary. The results of this comprehensive review provide a reference for the intelligent operation of tractors under the precision agriculture. [ABSTRACT FROM AUTHOR]

The growing human population is a driver for higher food demands with a need to scale agricultural production and maintain security of the food supply chain. Thus, there is a need to increase the adoption and improvement of mechanized systems in agriculture, especially where needed labor is also drifting into nonagricultural production sectors. With this view, the relationship or link between population and employment in nonagricultural sector in Ghana (West Africa) to agricultural mechanization was tested to ascertain any such validity. This formed the primary basis for this study and furthered on to establish the current level of agricultural mechanization within the country through measuring effect of available farm energy sources on farm sizes under cultivation. The methods employed included a structured questionnaire administered to farmers and other agricultural stakeholders to determine the level of mechanization, readiness to adopt/accept mechanization technology, level of usage of mechanization technologies, and ownership of machinery. The Statistical Package for the Social Sciences (SPSS version 20) software was used to model and analyze data obtained including a multiple regression method for the relationship between parameters. The overall level of agricultural mechanization in Ghana was found to be very low with 77.6% of the farm operations being performed manually. The level of the tractor power availability in Ghana was found to have increased from 0.0207 kW/ha in the year 2004 to 0.0588 kW/ha in the year 2020 and is expected to increase to 0.0752 kW/ha in the year 2025. The power availability valued in this study was also found to be low compared with that in other developing countries. Statistically, both employment in the service sector and population growth were significant determinants (Adjusted − R 2 = 0.9172) in the variations in the level of mechanization of agriculture in Ghana and policymakers will have to make adjustments in policies to take note of these indicators most often underplayed. Advocacy for higher levels of mechanization of agricultural operations must increase as it is critical to the overall cost of production in agriculture as this study also found out that mechanized operations were between 21.3% and 53.8% cheaper than manual operations. [ABSTRACT FROM AUTHOR]

Although the trade effects of public and private standards—particularly for food safety and environmental quality—in agricultural markets have been well documented, much less is known about standards harmonization and international trade in tractors, a crucial input to agricultural production in most countries. We analyze the trade impacts of the long‐lived OECD Tractor Codes—an integrated system of standardized tractor tests for performance and safety, certification, and mutual recognition agreements established in 1959. We hypothesize that this system increases tractor trade between members and possibly among members and nonmembers because it: (1) reduces duplication of tests across import markets, (2) lowers transaction costs of tractor trade disputes, (3) enhances manufacturers' risk management, and (4) boosts farmer demand through greater trust resulting from intergovernmental organization certification. Using bilateral COMTRADE data for 1962–2018, we estimate a structural gravity equation using Poisson pseudo‐maximum likelihood methods to account for zero trade. After controlling for economic integration agreements and OECD membership, our benchmark analysis suggests trade is roughly one‐third larger if both partners are members, a finding that is robust to considerations of gradual adjustment costs and reverse causality. We further find that this effect varies by countries' timing of accession and, to a lesser extent, level of economic development, though trade creation effects are inconclusive. A counterfactual analysis indicates that manufacturers and farmers in nonmember countries, including several middle‐income and low‐income countries, would benefit from membership. Our results have important implications for standards harmonization and international trade in agricultural machinery. [ABSTRACT FROM AUTHOR]