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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]

Climate change and the current energy crisis are creating new challenges to agriculture and new technological solutions must be developed to increase agricultural machinery efficiency. Researchers and machinery manufacturers identified electrified powertrains as a possible solution to meet this demand. The development of field-effective electrified powertrains is challenging mostly due to the wide variability of operating conditions of agricultural tractors. While the automotive industry adopted reference driving cycles for the design and evaluation of hybrid powertrains, the tractor industry has not been able to easily record external load in real-world conditions as it requires dedicated systems that cannot be used under prolonged field usages. This study aims to provide a methodology for estimating a reference working cycle from a multi-year dataset using technologies available in current commercial tractors. Data were collected on a tractor used for 3 years of agricultural work. Data were first clustered into work states, then, for each state, signal features from on-tractor sensors were used to extract key factors to compute the reference work state. With an optimisation solver and a hidden Markov model, the reference working cycle that synthesised the real-world tractor use was calculated. This cycle was compared with established cycles for non-road mobile machinery. The new reference cycle better represented real-world tractor usage as it also complied with low engine operations, which are frequent in farming and mostly associated with machine setup. The new reference working cycle permits a reliable estimation of fuel consumption of real-world farming. • Reference working cycles are necessary for designing field-effective drivetrains. • A reference working cycle aiming to synthesise real-word usage was calculated. • The reference cycle makes the engine operates in its operating domain. • The cycle better reproduces real-world usage than established cycles for NRMM. [ABSTRACT FROM AUTHOR]

Despite continuous work on new power systems for vehicles, machines, and devices, the combustion engine is still the dominant system. The operation of the combustion engine is initiated during the starting process using starting devices. The most common starting system used is the electric starter. The starting process of an internal combustion engine depends on the following factors: the technical condition of the starting system, technical condition of the engine, battery charge level, lubricating properties, engine standstill time, engine and ambient temperature, type of fuel, etc. This article presents the results of laboratory tests of the electrical parameters of the starting process of a single-cylinder compression–ignition engine with variable fuel injection parameters and ambient temperature conditions. It was confirmed that for the increased fuel dose FD2, higher values of the measured electrical parameters (Imax, Pmax, and Pmed) were obtained compared to the series of tests with the nominal fuel dose. Knowledge of the values of the electrical parameters of the starting process is important not only for the user (vehicle driver, agricultural machinery operator, etc.), but above all for designers of modern starting systems for combustion engines and service personnel. The obtained results of testing the electrical parameters of the combustion engine during start-up may be helpful in designing new drive systems supported by a compression–ignition combustion engine. [ABSTRACT FROM AUTHOR]

The unmanned farm control platform is of great significance in promoting the supervision of farm production with less manpower or autonomous operation of farm machinery and the construction of farm informatization. Addressing the existing control platform for farm location information acquisition is time-consuming, labor-intensive, and lacks the whole process control of multiple types of farm machinery. In this paper, we propose an Internet of Things (IoT) control scheme for intelligent farm machinery operation of unmanned farms and design the access standards for multiple types of farm machinery, as well as realize the remote control of intelligent farm machinery operation by constructing a remote control model. A high-precision map construction method is designed to improve the DeepLabV3+ algorithm to identify fields and roads. The control models of path planning, remote task, remote control, and safety system are built to achieve the remote control of intelligent agricultural machinery operation. The proposed technology is implemented in the platform integration and application tests are carried out. The error of the constructed high-precision map is less than 3 cm, the completeness rate of the automatic boundary extraction rate is 96.71%, and the correctness rate is 95.63%, which can be used to obtain the boundary instead of manual labeling or on-site point picking. The use of the platform for the simultaneous control of three farm machinery operations reduces the number of people in operation and production and reduces the professional requirements of the personnel, which will promote the management of the entire farm by one person or even by no one in the future. [ABSTRACT FROM AUTHOR]

Currently, the multi-machine collaboration of agricultural machinery is one of the international frontiers and a topic of research interest in the field of agricultural equipment. However, the multi-machine cooperative operation of agricultural machinery is mostly limited to the research on task goal planning and cooperative path optimization of a single operation. To address the mentioned shortcomings, this study addresses the problem of multi-machine cooperative operation of fertilizer applicators in fields with different fertility and fertilizer cooperative distribution of fertilizer trucks. The research uses the task allocation method of a multi-machine cooperative operation of applying fertilizer-transporting fertilizer. First, the problems of fertilizer applicator operation and fertilizer truck fertilizer distribution are defined, and the operating time and the distribution distance are used as optimization objectives to construct functions to establish task allocation mathematical models. Second, a Chaos–Cauchy Fireworks Algorithm (CCFWA), which includes a discretized decoding method, a population initialization with a chaotic map, and a Cauchy mutation operation, is developed. Finally, the proposed algorithm is verified by tests in an actual scenario of fertilizer being applied in the test area of Jimo District, Qingdao City, Shandong Province. The results show that compared to the Fireworks Algorithm, Genetic Algorithm, and Particle Swarm Optimization, the proposed CCFWA can address the problem of falling into a local optimum while guaranteeing the convergence speed. Also, the variance of the CCFWA is reduced by more than 48% compared with the other three algorithms. The proposed method can realize multi-machine cooperative operation and precise distribution of seeds and fertilizers for multiple seeding-fertilizer applicators and fertilizer trucks. [ABSTRACT FROM AUTHOR]

This study investigates the optimization of VR simulation interfaces for agricultural machinery, emphasizing the critical role of skill development and targeted education in enhancing agricultural efficiency. By utilizing eye-tracking technology, the research evaluates user experience (UX) across two menu designs - panel and radial -in VR settings. Results highlight the significance of intuitive menu design in facilitating user navigation and information access, with the panel menu outperforming the radial menu in usability. Despite some preferences for the radial menu's features, the panel menu is favored for its user-friendly design and ease of access, particularly in agricultural simulations. The findings suggest that effective VR interface design, supported by focused training, can significantly improve operational efficiency in agriculture. [ABSTRACT FROM AUTHOR]

Field-road mode classification (FRMC) that identifies "in-field" and "on-road" categories for Global Navigation Satellite System (GNSS) trajectory points of agricultural machinery containing geographic information is essential for effective crop improvement. Most previous studies utilize local trajectory features (i.e., the relationships between a point and its neighboring points), but they ignore global trajectory features (i.e., the relationships between the point and all points of the trajectory), leading to difficulty in improving the overall classification performance. The global trajectory features are useful for FRMC because they contain rich trajectory information (e.g., mode switching and motion tendency). Therefore, a ConvTEBiLSTM network-based method is proposed to improve the overall performance. Firstly, nine statistical features (e.g., speed and direction) are extracted from the original data and fed into the ConvTEBiLSTM network. Then, the ConvTEBiLSTM network combining the Bidirectional Long Short-Term Memory network, 1D Convolution network, and Transformer-Encoder network is used to extract and fuse local and global trajectory features. Finally, a linear classifier is applied to identify the "field" and "road" categories of GNSS points based on the fused features. Experimental results show that compared with the baselines, our method achieves the best accuracy and F1-score of 97.38% and 92.74% on our Harvester dataset, respectively. [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]

In mechanized agricultural activities, fuel is particularly important for tillage operations. In this study, the impact of seven distinct parameters on fuel usage per unit of draft power was examined. The parameters are tractor power, soil texture index, plowing speed, plowing depth, width of implement, and both initial soil moisture content and soil bulk density. This study investigated the construction of an artificial neural network (ANN) model for tractor-specific fuel consumption predictions for two tillage implements: chisel and moldboard plows. The ANN model was created based on the collection of related data from previous research studies, and the validation was performed using actual field experiments in clay soil using a chisel plow. The developed ANN model (9-22-1) was confirmed by graphical assessment; additionally, the root-mean-square error (RMSE) was computed. Based on the RMSE, the results demonstrated a good agreement for specific fuel consumption per draft power between the observed and predicted values, with corresponding RMSE values of 0.08 L/kWh and 0.075 L/kWh for the training and testing datasets, respectively. The novelty of the work presented in this paper is that, for the first time, a farm machinery manager can optimize tractor fuel consumption per draft power by carefully controlling certain parameters, such as initial soil moisture content, tractor power, plowing speed, implement width, and depth of plowing. The results show that the input parameters make a significant contribution to the output over the used data with different percentages. Accordingly, the contribution analysis showed that the implement width had a high impact on tractor-specific fuel consumption for both plows at 30.13%; additionally, the chisel and moldboard plows contributed 4.19% and 4.25% in predicting tractor fuel consumption per draft power. This study concluded that practical useful advice for agricultural production can be achieved through optimizing fuel consumption rate by selecting the proper levels of affecting parameters to reduce fuel costs. Moreover, an ANN model could be used to develop future tractor fuel-planning schemes for tillage operations. [ABSTRACT FROM AUTHOR]

This study presents a machine vision-based variable weeding system for plant- protection unmanned ground vehicles (UGVs) to address the issues of pesticide waste and environmental pollution that are readily caused by traditional spraying agricultural machinery. The system utilizes fuzzy rules to achieve adaptive modification of the Kp, Ki, and Kd adjustment parameters of the PID control algorithm and combines them with an interleaved period PWM controller to reduce the impact of nonlinear variations in water pressure on the performance of the system, and to improve the stability and control accuracy of the system. After testing various image threshold segmentation and image graying algorithms, the normalized super green algorithm (2G-R-B) and the fast iterative threshold segmentation method were adopted as the best combination. This combination effectively distinguished between the vegetation and the background, and thus improved the accuracy of the pixel extraction algorithm for vegetation distribution. The results of orthogonal testing by selected four representative spraying duty cycles—25%, 50%, 75%, and 100%—showed that the pressure variation was less than 0.05 MPa, the average spraying error was less than 2%, and the highest error was less than 5% throughout the test. Finally, the performance of the system was comprehensively evaluated through field trials. The evaluation showed that the system was able to adjust the corresponding spraying volume in real time according to the vegetation distribution under the decision-making based on machine vision algorithms, which proved the low cost and effectiveness of the designed variable weed control system. [ABSTRACT FROM AUTHOR]

In response to the problems of low efficiency, high labor intensity, and low mechanization in manual tobacco harvesting, a comb-off tobacco picking device for southern hilly tobacco areas was designed following the agronomic requirements and the principle of manual picking of tobacco harvesting in southern China. The device was composed of the power chassis, picking mechanism, and storage mechanism. This study involved the theoretical analysis, structural design, and modeling of the key components, such as chassis structure, combing-type picking mechanism, and power synchronization mechanism. The results of the motion analysis and calculation of the picking process demonstrated that the adjustment range of the comb chain elevation angles was from 12.4° to 20.9°, the comb rod installation distance was 76.2 mm, and the synchronizing mechanism transmission ratio was 3:10. One-factor test and three-factor three-level orthogonal test was performed with the forward speed of the chassis, the distance between the picking device baffles and the elevation angle of the chain with the combing bar as test factors, and the rate of broken and missed tobacco picking as evaluation indicators. It was revealed that the optimal combination of the forward speed of the chassis, the distance between the baffles, and the chain elevation angle were 1.5 km/h, 75 mm, and 12.4°, respectively. Moreover, verification tests suggested that the breakage rate of tobacco leaves was 9.99%, and the probability of missed tobacco picking was 7.31%, both of which satisfy the agriculture requirements and the operational requirements in the agricultural machinery certification syllabus. [ABSTRACT FROM AUTHOR]

Weeds and crops engage in a relentless battle for the same resources, leading to potential reductions in crop yields and increased agricultural costs. Traditional methods of weed control, such as heavy herbicide use, come with the drawback of promoting weed resistance and environmental pollution. As the demand for pollution-free and organic agricultural products rises, there is a pressing need for innovative solutions. The emergence of smart agricultural equipment, including intelligent robots, unmanned aerial vehicles and satellite technology, proves to be pivotal in addressing weed-related challenges. The effectiveness of smart agricultural equipment, however, hinges on accurate detection, a task influenced by various factors, like growth stages, environmental conditions and shading. To achieve precise crop identification, it is essential to employ suitable sensors and optimized algorithms. Deep learning plays a crucial role in enhancing weed recognition accuracy. This advancement enables targeted actions such as minimal pesticide spraying or precise laser excision of weeds, effectively reducing the overall cost of agricultural production. This paper provides a thorough overview of the application of deep learning for crop and weed recognition in smart agricultural equipment. Starting with an overview of intelligent agricultural tools, sensors and identification algorithms, the discussion delves into instructive examples, showcasing the technology's prowess in distinguishing between weeds and crops. The narrative highlights recent breakthroughs in automated technologies for precision plant identification while acknowledging existing challenges and proposing prospects. By marrying cutting-edge technology with sustainable agricultural practices, the adoption of intelligent equipment presents a promising path toward efficient and eco-friendly weed management in modern agriculture. [ABSTRACT FROM AUTHOR]

The number of cameras utilised in smart city domains is increasingly prominent and notable for monitoring outdoor urban and rural areas such as farms and forests to deter thefts of farming machinery and livestock, as well as monitoring workers to guarantee their safety. However, anomaly detection tasks become much more challenging in environments with low-light conditions. Consequently, achieving efficient outcomes in recognising surrounding behaviours and events becomes difficult. Therefore, this research has developed a technique to enhance images captured in poor visibility. This enhancement aims to boost object detection accuracy and mitigate false positive detections. The proposed technique consists of several stages. In the first stage, features are extracted from input images. Subsequently, a classifier assigns a unique label to indicate the optimum model among multi-enhancement networks. In addition, it can distinguish scenes captured with sufficient light from low-light ones. Finally, a detection algorithm is applied to identify objects. Each task was implemented on a separate IoT-edge device, improving detection performance on the ExDark database with a nearly one-second response time across all stages. [ABSTRACT FROM AUTHOR]

Field applied liquid animal manure (slurry) is a significant source of ammonia (NH3) emission, which is harmful to the environment and human health. To evaluate mitigation options, reliable measurements of effects are needed. A new system of dynamic flux chambers (DFC) with high time resolution online measurements was developed. The system was investigated in silico with computational fluid dynamics and tested in three field trials, each trial assessing the variability after application with trailing hose at different scales: manual (handheld), 3-m experimental slurry boom, and 30-m farm-scale commercial slurry boom. For the experiments with machine application, parallel NH3 emission measurements were made using an inverse dispersion modelling method (backward Lagrangian stochastic modelling, bLS). The lowest coefficient of variation of replicate DFC measurements was obtained with manual application, followed by the 3-m slurry boom, and lastly the 30-m slurry boom. Conditions in DFCs resulted in a consistently higher NH3 flux than what was measured with the inverse dispersion technique but both methods showed a similar emission reduction by injection compared to trailing hose: 89% by DFC and 97% by bLS. The new measurement system facilitates NH3 emission measurement with replication after both manual and farm-scale slurry application with relatively high precision, with a coefficient of variation of 5% among replicates with manual slurry application and 20% for farm-scale slurry application. [ABSTRACT FROM AUTHOR]

The work is presented in three parts. The first one presents the use of the mechanization in Germany. In this case the form is presented in which is carried out the soil preparation; planting and it harvests using a great variety equipment (tractors and agricultural machine). In the second part the use of the mechanization is exposed in the Cuban case; emphasizing in the importance of introducing in Cuba some of these technologies of wide use in the developed world. The third part it carries out a discussion of the advantages and limitations that could be kept in mind to achieve a perroductive mechanization and a high quality, which could report an increase in the production and quality of the obtained products. [ABSTRACT FROM AUTHOR]

Mechanization is of great relevance in the development of the agricultural sector, as a tool that facilitates agricultural activities with quality and speed and a significant increase in the productivity and competitiveness of this sector, in the case of the province of Manabí in Ecuador this aspect becomes more relevant because this sector has a substantial weight in its economic and social life. The objective of the research was to carry out a diagnosis of agricultural mechanization competencies in the cantons of the central zone of Manabí. The methodology used consisted of several stages, which made it possible to evaluate the factors that characterize the competencies of agricultural mechanization in the area under study: human factor, machinery, operating conditions and infrastructure and financing. For the collection of information, surveys based on the factors under analysis were prepared and applied to agricultural producers and owners/entrepreneurs who provide mechanization services in the central zone of Manabí. The results of the diagnosis in the selected sample show that only 41% of the agricultural activities are being carried out with the use of agricultural machinery and that 20% of the producers have their own means to carry out agricultural activities, among other relevant aspects. As a whole, the results allowed concluding that the agricultural mechanization skills in the central zone of the province of Manabí present undesirable low levels that limit its productivity. [ABSTRACT FROM AUTHOR]

The importance of realistic financial reporting depends on the consideration of numerous factors by the decision maker. In this paper, the authors focused on a comprehensive analysis of agricultural machinery in use by individual farms and medium-sized agricultural enterprises. The main conclusion reached by the authors would be that there are significant differences regarding the use of agricultural machinery in relation to its age, value, fuel consumption and its maintenance (p<0.0005*) in relation to the two forms of organizing agricultural production. Medium-sized agricultural enterprises use younger, more expensive agricultural machinery, as well as the fact that the owner's satisfaction with it is somewhat lower with lower fuel consumption and lower maintenance costs of agricultural machinery. The value of agricultural mechanization can be predicted both for individual farms based on the mentioned factors (F=262.901, p<0.0005) and for medium-sized agricultural enterprises (F=161.229, p<0.0005). [ABSTRACT FROM AUTHOR]

Aiming at the adaptability and safety problems of agricultural machinery in hilly and mountainous areas, the remote driving control system of agricultural full hydraulic chassis is designed based on ARM-Linux platform. The whole remote driving system is composed of Web upper computer, server system and chassis drive system. According to the requirements of chassis operation, the STM32F407 is used as the lower computer to realize the running control and motion status monitoring of the chassis. Taking the I.MX6ULL as the hardware platform, the Linux as the software platform, and 4G communications as the Web Server, the remote driving of the chassis is realized through Web pages on the computer. It can be seen from the test results that the minimum RTT delay from the Web page driving to the lower computer is 170 ms; the maximum RTT delay is 1310 ms, and the average RTT delay is 222.75 ms. The real-time interactivity of the control system meets the needs of remote driving of the agricultural machinery. The research provides a theoretical basis and technical reference for the development of the remote driving system of the agricultural machinery. [ABSTRACT FROM AUTHOR]

Mini-tiller is an indispensable agricultural machinery in hilly and mountainous areas of China. Rotary blade is an important working part of mini-tiller, which directly affects the operation quality and power consumption of mini-tiller. In order to reduce the cutting resistance and power consumption of the rotary blade of mini-tiller, the cutting process of the rotary blade was analyzed by numerical simulation, and the tangential bending radius (R), bending angle (β) and edge thickness (c) of the rotary blade were selected as factors to optimize it. After comparing the cutting resistance and cutting power consumption of the rotary blade before and after optimization, the results show that the cutting force of the optimized rotary blade is smaller than that of the rotary blade before optimization. The cutting power consumption of the optimized rotary blade is 2.4% lower than that of the unoptimized rotary blade, which achieves the purpose of drag reduction and consumption reduction. [ABSTRACT FROM AUTHOR]

Detailed performance testing of agricultural machinery is very important in determining its value in use. These measurements cannot be limited to laboratory tests, such as braking the power take-off (PTO) shaft of a tractor or performing dynamic tests of implements in a soil bin. Field tests are the ultimate way to test the capabilities of agricultural machinery. However, during such field tests, there are many parameters that can interfere with and affect the test results, such as inhomogeneity of the soil and tyre characteristics. In order to minimise these effects as much as possible, Hungarian University of Agriculture and Life Sciences (MATE) Institute of Technology, Agriculture Engineering Labs. has developed a dynamometer vehicle with an electronic brake control system that is suitable for measuring the traction characteristics of agricultural tractors and other terrain vehicles. It is also capable of testing different track systems and tyre-soil interactions. This paper introduces this special test vehicle by presenting measurement results and also describes other interesting applications for the agricultural community. [ABSTRACT FROM AUTHOR]

Weeds have posed a serious impact on rice growth and yield in paddy fields. In this study, an inter-row weeding device was designed in the paddy field, including a pressing-weeds floating plate and a weeding roller. The weeding procedure was that the floating plate pushed over the weeds in the inter-row area, and then the weeding roller pressed the weeds into the soil. The probability that the weeding roller pressed the weeds into the soil was improved by 9.98% after the floating plate was pushed over the weeds. Furthermore, the pressing-weeds floating plate was in a closed box structure, which gradually pushed over the weeds, reduced the forward resistance and moved the rice for less damage to the stems and leaves. The weeding roller was composed of weeding discs and weeding cutter teeth. The weeds were pressed into the soil to isolate them from sunlight and air, in order to achieve the purpose of weeding. The two ends of the weeding roller were equipped with the chamfer, in order to reduce the damage to rice roots. The weeding width was expanded by 3%, compared with the regular weeding roller. Some parameters were determined, including the expanded weeding width, chamfer angle, soil depth, root crown root angle and weeding width of the weeding roller. The simulation test was implemented to clarify the interaction between the weeding device and soil. The quadratic orthogonal rotation combination test was carried out to analyze the effect of the weeding depth and weeding speed on the amount of heaped soil on the floating plate, the amount of soil disturbance, and the force of the floating plate and weeding roller in the horizontal and vertical directions. The interaction relationship between the factors and test indexes was determined by variance significance and response surface method (RSM). As such, the optimal weeding parameters were determined: the weeding depth was 35 mm, and the weeding speed was 0.8m/s. The field experiment was conducted to analyze the effects of different weeding modes on the plant height, yield, and roots of rice. Four treatments were set: non-weeding, chemical, artificial and mechanical weeding using this inter-row weeding device. Among them, three widths 150, 175, 200 mm and two types with/without chamfer were selected in the weeding rollers. A systematic investigation was made to determine the effect of different types of weeding rollers on the weeding rate, rice roots, rice growth and yield. The experimental results showed that the weeding rate of the device reached 87.51%, which fully met the requirements in the paddy field. The weeding device was also used to turn the soil and increase the permeability of the soil. The weeding rate increased gradually with the increase in the width of the weeding roller. There was an increase in the weeding rate of 7.3% by expanding the inter-row weeding area. There were also significant effects among different weeding modes on the plant height and yield of rice（P＜0.05）. Mechanical weeding can be expected to promote the growth of rice. The yield can also reach or even exceed the levels of chemical and artificial weeding. The weeding roller with different parameters has a significant impact on the weeding rate, plant height, yield and roots of rice. The weeding roller with chamfer at both ends when increasing the width of the weeding roller can effectively avoid or reduce damage to the roots of rice, for better growth of rice, yield and weeding performance（P＜0.05）. The inter-row weeding device can provide a strong reference to the design of weeding machinery and equipment in paddy fields. [ABSTRACT FROM AUTHOR]

Horizontal planting has been used for fresh sweet potatoes in recent years. A large number of sweet potatoes can be produced, even potato block sizes. It is necessary to place potato seedlings after trenching transversely on the potato ridges when using the horizontal transplanting manually. The labor-intensive and inefficient have severely constrained the development of the sweet potato industry. However, there is no horizontal transplanting machine for sweet potatoes. In this study, a horizontal transplanting machine was designed for sweet potatoes, according to the agronomic requirements. Two rows of sweet potatoes were realized in the rotary tillage, horizontal planting, soil covering and ridge repair, and laying drip irrigation belts in one operation. High transplanting quality and transplanting efficiency were achieved in the current process of sweet potato seedling transplantation. The transplanting motion of sweet potato seedlings was theoretically studied using the EDEM-RecurDyn coupling simulation. The main influencing factors on the transplanting quality of sweet potato seedlings were determined as the forward speed of the transplanting machine, chain speed, soil depth, and seedling claw height. A coupling model was constructed to simulate the seedling operation process for the planting device-flexible sweet potato seedling-sweet potato ridge. The simulation determined that the seedling trajectory was a short cycloid, and the seedling claw height was 50 mm. An analysis was made on the movement of sweet potato seedling posture and soil particles during transplantation. The final position and ridge shape of sweet potato seedlings were confirmed, according to the agronomic requirements for horizontal planting. The Box Behnken experimental design was used with the machine forward speed, chain forward speed, and soil depth as experimental factors, while the qualified rate of planting depth, planting spacing, and transplanting efficiency as evaluation indicators. The level was also evaluated for the influence of experimental influencing factors on various experimental indicators. A quadratic regression orthogonal experiment was conducted to determine the optimization model. The validation test results showed that the optimal combination of working parameters was the moving forward speed of 0.4 m/s in the machine, the moving forward speed of 0.2 m/s in the chain, and the soil depth at 46 mm. At this time, both qualified rates of planting depth and spacing were 92% at the transplanting efficiency of 263 plants/min. The relative error between the average value of the field experiment and the optimized value was less than 5%, indicating an accurate regression model. The number of sweet potatoes planted using a horizontal transplanting machine was 3-6, and the size of the sweet potato blocks was uniform, especially suitable for the commodity properties of fresh sweet potato blocks. The transplanting machine performed better planting, fully meeting the agronomic requirements for horizontal planting of sweet potatoes. The findings can provide a strong reference for the design and optimization of sweet potato transplanting machines. [ABSTRACT FROM AUTHOR]

Agricultural mechanization is crucial in enhancing production efficiency, alleviating labor demands, reducing costs, improving agricultural product quality, and promoting sustainable development. However, wear and tear are inevitable when using agricultural machinery. The failure of critical wear-resistant parts is responsible for over 50% of rural machinery breakdowns. For instance, a domestic combine harvester typically only operates trouble-free for 20 to 30 h, and the service life of a rotary plow knife is approximately 80 h. Investigating the wear performance of key farm machinery components reinforces machinery design and maintenance strategies, extends machinery lifespans, enhances agricultural production efficiency, and advances agrarian sustainability. This paper provides a comprehensive overview of the latest research on the wear resistance of crucial agricultural machinery components. It delves into the factors influencing the wear resistance of these components and explores current effective measures to address wear-related issues. Additionally, it also summarizes the challenges and opportunities in researching the wear performance of key components in agricultural machinery and future development directions. [ABSTRACT FROM AUTHOR]

A survey was conducted in this study to determine the general characteristics of the agricultural machinery manufacturing industry in the Konya region. To achieve this, 50 enterprises of various scales, considered representative of the sector, were selected and included in the study. When evaluating the enterprises based on size, it was found that 52% of them were small-scale enterprises. The average age of business owners is 53 years, with 35 years of industry experience, and 47% of them have primary school education. While a total of 1204 workers are employed in the enterprises participating in this study, there is an average of 24.5 workers per enterprise. Of the total personnel, 78.3% consisted of workers, followed by engineers with an average of 5.5%, accountants with 5.3%, marketers with 5% and technicians with 4%. Only 34% of enterprises cooperate with KOSGEB and 8% with TUBITAK in R&D and P&D activities. In addition, it was determined that 18% received consultancy from universities. Present findings shed light on the developments in the sector as well as understanding the situation of agricultural machinery manufacturing industry enterprises in the region. [ABSTRACT FROM AUTHOR]

[Objective] The present paper aimed to explore and design the platform architecture of agricultural machinery socialization service supply and demand docking, provide agricultural machinery socialization services scientifically and reasonably according to the needs of farmers, and coordinate the management of massive agricultural machinery socialization service data and information, so as to promote the development of agricultural informatization, so as to improve the management level of agricultural machinery and the quality and efficiency of agricultural machinery socialization services, and provide effective support for the transformation and upgrading of modem agriculture. [Method] Factor analysis was used to sort out the core requirements of users for the platform, divide the functional modules of the platform, and design the platform architecture based on this. The service blueprint theory was exploringly applied to the socialization of agricultural machinery services, which depicted the blueprint of the supply and demand docking platform of agricultural machinery socialization services, displayed various activities in the process of socialized agricultural machinery services, sorted out the service process, and showed the integrity of the platform architecture design in a visual form. [Result] The data variation explained by the four main factors was greater than 5%, and the cumulative variance contribution rate was 85. 32%, and the four main factors could be extracted, which were named as platform management optimization function requirements, agricultural machinery operation service function requirements, agricultural machinery information service function requirements and agricultural machinery supporting service function requirements to comprehensively express the functional requirements of the agricultural machinery socialized service supply and demand docking platform. Based on the results of factor analysis function division and the process of agricultural machinery socialized service described in the service blueprint, the architecture of the agricultural machinery socialized service supply and demand docking platform was designed. [Conclusion] With the adjustment of China's population structure, the shortage of labor in agricultural production, and the increasing demand of farmers for agricultural machinery socialization services, the construction of agricultural machinery socialization service platform is the general trend, and it is necessary to conduct in-depth research and gradual improvement in the future to promote the final construction and implementation of the platform. [ABSTRACT FROM AUTHOR]

Mulch cultivation has been widely used to regulate the growth cycle of crops for the high yields, due to the high ground temperature and moisture conservation for suppressing weeds. However, the main components of mulch film are polyethylene compounds extremely difficult to degrade. Once the mulch film failed to be recycled in a timely manner, the soil structure and fertility would be threatened, even by the serious pollution in sustainable cultivation. Among them, Xinjiang is the largest area of film cultivation in China. A great challenge is to recycle the ultra-thin film after a cotton operating season, due to the low film strength. However there are still some problems in the residual film recovery, such as the low adaptability to the unevenness of the ground, low recovery rate of residual film, and a large number of impurities in the recovered residual film. This study aims to develop an integrated machine with the clamping finger-chain type residual film recycling and straw crushing return to the cotton field. The machine was to concurrently realize the straw crushing and returning to the field, residual film recycling, as well as the clearing and baling operation. The structure and parameters of the existing clamping finger-chain type film collecting device were improved to design the disc film removing device and inclined belt impurity cleaning and feeding device. Mechanical analysis was conducted to determine the structural dimensions and arrangement of the film-removing device, as well as the impurity cleaning and feeding device. Three field tests were also carried out at an operating speed of 7 km/h. The test showed that the average lifting rate of residual film increased by 2.52 percentage pionts than before. The film-removing rate test showed that the highest film-removing rate of 99.79% was achieved when the speed of the film-removing disc was 189.47 r/min. The influencing factors on the residual film recovery rate were determined as the clamping finger-chain line speed ratio, the working length of the impurity cleaning belt, and the inclination of the impurity cleaning belt. The impurity rate of the residual film was dominated by the inclination of the impurity cleaning belt, the working length of the impurity cleaning belt, and the speed ratio of the impurity cleaning belt line. The working parameters were then optimized after the test. An optimal combination was obtained as follows: clamping finger-chain line speed ratio 0.8, clamping finger-chain belt inclination 50°, working length of impurity cleaning belt 608 mm. A better performance was achieved, where the evaluation indexes were 91.50% of residual film recovery rate, and 24.53% of impurity rate of residual film, respectively. The field test showed that the residual film recovery rate was 92.85%, and the residual film crushing and returning to the field rate was 26.05%, indicating a less difference from the predicted values. The integrated machine can be expected to fully meet the design requirements in the cotton field. [ABSTRACT FROM AUTHOR]

Management level and user benefits have greatly contributed to agricultural machinery in recent years. The operational efficiency of agricultural machinery was commonly used to evaluate the utilization rate, operator driving ability, and management efficiency of agricultural machinery. However, the current operational efficiency of agricultural machinery cannot fully represent the overall operational efficiency of agricultural machinery. For example, although the low-power agricultural machinery has low operational efficiency, the generated benefits are not lower than that of high-power agricultural machinery, if the operating time is saturated. In addition, the quality of agricultural machinery operation can seriously affect operational efficiency. Therefore, it is necessary to consider the key influencing factors on the efficiency of agricultural machinery operations. In this study, a comprehensive and comprehensive evaluation was conducted on agricultural machinery operations. The operational efficiency was then evaluated on each agricultural machine using influencing factors. The daily operational information of each machine was taken as a piece of data on that day. The operation status of operators and agricultural machinery were checked to identify the influencing factors on the efficiency of operations, in order to improve the management level and revenue of agricultural machinery. The data was collected from the 32000 deep loosening operations of agricultural machinery. The results show that the main influencing factors on the daily operation efficiency of agricultural machinery were directly obtained, including the daily operation area, fuel consumption, operation quality, repeated operation rate, missed operation rate, and the proportion of effective operation time. The BP_Adaboost neural network (NN) training model was used to evaluate the efficiency of agricultural machinery operation. Manually grading was replaced to avoid the large workload and extremely low efficiency from the subjective factors, inconsistent standards, and labeling errors, due to the large number of agricultural machinery and the large amount of homework data. A comparison was made on the training model and manual grading to predict the remaining data. Manual scoring standards were effectively used to establish the predictive models. A small number of samples were selected to predict the operational efficiency of agricultural machinery. The low accuracy was obtained in the training model if there were too few labeled samples. If the additional labeled samples were added, manual grading was less labor-saving. Semi-supervised BP_Adaboost was utilized to evaluate the efficiency of agricultural machinery operations, where manually scoring some data was marked the daily efficiency. One part was used as training samples, whereas, another part was used as testing samples. The BP_Adaboost was then used to reduce the manual labeling of training samples for the high accuracy of the training model, where the remaining unrated data was predicted after training the model. 1 000 samples were selected from 32 000 deep loosening operation data for labeling, of which 500 were used as training samples and 500 were used as testing samples. The highest prediction accuracy was achieved in the semisupervised method for the selected experimental data when the probability threshold was 97%. If the threshold was too large, there was only a limited increase in samples; If the sample was too small, misclassified samples led to low accuracy. Therefore, there was a significant impact on the sample selection and termination in semi-supervised methods. The prediction accuracies were achieved in 93.36% and 97.03%, respectively, using the BP_Adaboost, and semi-supervised BP_Adaboost with training samples. Statistical analysis was conducted on 32 000 agricultural machinery operation data from the experiment. The effectiveness of the improved model was obtained by combining the partial power agricultural machinery with different-width machines. The operation efficiency varied greatly in the power agricultural machinery when paired with different width machines. The optimal combination of agricultural machinery was recommended to enhance the operational capabilities, according to the operational efficiency. The accuracy of the improved model was higher than that of using the BP_Adaboost alone, depending largely on the selection of the probability threshold. The generalization and standards can be expected for the different datasets and the optimal thresholds. A more reasonable probability threshold can be selected to assign different weights to various indicators for the better performance of the improved model. [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]

Different share types of tine type inter-row cultivator are used to remove the weeds and loosen the soil surface between the rows during the first true leaf stage of cotton. The efficiency of these shares can be changed by soil properties and working parameters. Therefore, this study evaluated the effects of different share geometries for a tine inter-row cultivator on weed control and plant growth parameters at three different working depths (100, 150 and 200 mm) and a constant working speed (5.4 km. h-1) under cotton planted field conditions. Measurements included the weeding efficiency within row and between rows, the percentage of damaged plants, root dry weight, shoot dry weight, NDVI (Normalized difference vegetation index), SPAD (the relative content of chlorophyll) values and seed cotton yield. The results indicated that the inter-row cultivation at the first true leaf stage of cotton significantly increased the plant growth parameters (root dry weight, shoot dry weight, NDVI, SPAD) and seed cotton yield. The share types had a strong effect on the weeding efficiency and the percentage of damaged plants. The increased working depth increased the weeding efficiency, plant growth parameters and seed cotton yield, but also significantly increased the percentage of damaged plants. Overall, the results from this study suggest that the inter-row cultivation during the early stage of cotton will be an effective approach in improving the weed control and the plant growth in cotton production. These outcomes depend on the share type and working depth of the tine type inter-row cultivator. [ABSTRACT FROM AUTHOR]

This research was carried out with the aim of determining the deficiencies and determining the current situation by comparing the practices in the light of the Occupational Health and Safety Law No. 6331 and the relevant communiqués and regulations with the occupational health and safety practices carried out by some agricultural machinery manufacturers in Aydın. The material of the study consists of 19 enterprises that manufacture agricultural machinery registered in the Chamber of Industry and Söke Chamber of Commerce in Aydın province and its districts. A face-to-face survey method consisting of 68 questions was used as a data collection tool. The data obtained from the questionnaires were evaluated in computer environment by using the EXCEL program. In the research; ıt consists of demographic characteristics of the participants, business structures, production departments, information on occupational health and safety practices and data obtained within the framework of businesses for work accidents and occupational diseases. It was observed that the company responsible for the research lacked information about the occupational health and safety law, the level of implementation of the measures in the companies was not at a sufficient level, the employer and employee did not fully know their obligations, and controls and audits were not carried out effectively. [ABSTRACT FROM AUTHOR]

Agricultural machinery distribution programs are key components of the Philippine government to strengthen its economic productivity. However, concerns were reported that some of the distributed machines were under-utilized or unutilized in their respective farms. This study is focused on the development of a GIS-based model of determining suitable lowland rice areas for two-wheel and four-wheel tractors. A numerical rating system was designed that assigns a suitability score from three criteria, namely slope, road network proximity, and flood risk, based on established scales. Analytical Hierarchy Process was used as an approach to determine the relative influence in which results show that slope has the greatest weight (65%) followed by flood risk and road network proximity with 20% and 15%, respectively. The total suitability score (TSS) is then determined by getting the weighted average of the individual suitability scores. Land suitability mapping on the study area, the CALABARZON region, show that majority of the lowland rice areas are highly suitable for two-wheel and four-wheel tractors (81.39%) while some areas fall under marginal (15.03%) and moderate suitability (3.58%). Geotagged locations of the distributed agricultural tractors from 2015 to 2020 reveal that 78% of the distributed two-wheel tractors and 80% of four-wheel tractors in the region are situated in highly suitable areas. The GIS-based suitability model generated in this study can be utilized by the government to improve its machine distribution programs of two-wheel and four-wheel tractors in lowland rice farms. [ABSTRACT FROM AUTHOR]

Small arch sheds have been widely constructed in manual in China at present, particularly with the high labor intensity and low efficiency. The current commercial machinery of arch shed is the traction type in the form of shutdown insertion during construction. It is a high demand to improve the efficiency in the operation of shutdown insertion for the construction machinery. In this study, a continuous cuttage device was developed in the self-propelled shed machine for arch building. Specifically, the rear motor of the vehicle was used to drive forward, where the rear wheel drove the continuous insertion device to rotate via the transmission device, thereby driving the continuous insertion device to work. According to the agronomic requirements and overall structure, the key components of the continuous insertion device were determined to optimize the parameters of reverse transmission mechanism and bending components of the planetary gear train using simulation. The continuous and stable insertion operation was achieved to reduce the machine wear that caused by shutdown insertion for the high efficiency of arch construction. The reverse transmission mechanism and bending components of the planetary gear train were then designed to drive the bending components for the rotation and actions, such as bending and pressing poles. The soil resistance of shed pole was set as 51 N, when the maximum depth of insertion into the soil was 10 cm, according to the discrete element simulation of "Shed Pole-Soil". The stress simulation was conducted on the pressure pole arm of the shed pole and bending components, in order to ensure the successful insertion of the shed pole into the soil. The simulation results showed that the friction force between the pressure pole arm and the shed pole was 168 N, which was much greater than the soil resistance suffered by the shed pole. Moreover, the stress of shed pole was within the yield strength at the same time. The trajectory of bending pressure plate was analyzed in the bending components, according to the agronomic requirements of the depth and spacing of the small arch shed insertion. The optimal length of bending bracket was determined to be 27 cm, and the ratio of the speed of the central rotating shaft to the travel speed of vehicle was 0.85. The field trail results showed that the average insertion depth and spacing of shed pole were 7.04 and 74.11 cm, respectively, where the average error were 0.09 and 0.16 cm respectively. Therefore, the continuous insertion device of the self-propelled arch shed machine was developed to determine the optimal parameters of planetary gear train reverse transmission mechanism and bent parts using simulation. The continuous and stable insertion can be expected to reduce the wear of the machine that caused by the shutdown of the arch frame, particularly for the high construction efficiency of arch shed. [ABSTRACT FROM AUTHOR]

As the millet ears are dense, small in size, and serious occlusion in the complex grain field scene, the target detection model suitable for this environment requires high computing power, and it is difficult to deploy the real-time detection of millet ears on mobile devices. A lightweight real-time detection method for millet ears is based on YOLOv5. First, the YOLOv5s model is improved by replacing the YOLOv5s backbone feature extraction network with the MobilenetV3 lightweight model to reduce model size. Then, using the multi-feature fusion detection structure, the micro-scale detection layer is augmented to reduce high-level feature maps and low-level feature maps. The Merge-NMS technique is used in post-processing for target information loss to reduce the influence of boundary blur on the detection effect and increase the detection accuracy of small and obstructed targets. Finally, the models reconstructed by different improved methods are trained and tested on the self-built millet ear data set. The AP value of the improved model in this study reaches 97.78%, F1-score is 94.20%, and the model size is only 7.56 MB, which is 53.28% of the standard YoloV5s model size, and has a better detection speed. Compared with other classical target detection models, it shows strong robustness and generalization ability. The lightweight model performs better in the detection of pictures and videos in the Jetson Nano. The results show that the improved lightweight YOLOv5 millet detection model in this study can overcome the influence of complex environments, and significantly improve the detection effect of millet under dense distribution and occlusion conditions. The millet detection model is deployed on the Jetson Nano, and the millet detection system is implemented based on the PyQt5 framework. The detection accuracy and detection speed of the millet detection system can meet the actual needs of intelligent agricultural machinery equipment and has a good application prospect. [ABSTRACT FROM AUTHOR]

This study aims to reveal the effect of the soaking time of the lotus kernel on the quality of the plumule removal in the fresh lotus seeds. The physical and mechanical properties of the lotus kernel were investigated under different soaking times. The "Taikong 36" variety lotus seed was chosen as the research object. Firstly, a series of experiments were carried out to establish the relationship between soaking time and moisture content of the lotus kernel. The moisture contents of the lotus kernel at soaking times of 0-180 min were obtained as 60.75%, 62.06%, 62.54%, 62.85%, 63.08%, 63.23%, and 63.45%, respectively. Secondly, the geometric parameters of the lotus kernel and lotus plumules under different soaking times were measured using an vernier caliper. It was found that the maximum short diameter and length of the lotus kernel, and the length and the maximum width of the pointed fissure at the kernel tip increased with an increasing soaking time, as did the length, root diameter, maximum thickness, and maximum width of the lotus plumule. Thirdly, the hardness of the lotus kernel under different soaking times was measured using a Universal TA texture analyzer. The results showed that their hardness gradually decreased, as the soaking time of the lotus kernel increased. Once the soaking time increased from 0 to 180 min, the hardness of the lotus kernel decreased from 8.76 to 7.83 N. Mechanical properties tests of lotus kernel under different soaking times (including elastic modulus test, compressive strength test, and the force measurement for removing lotus plumule) were conducted using the UTS-4.5KN/T162 universal testing system, in order to obtain the stress-strain curve and load-displacement curve of the lotus kernel material. The relationship between physical and mechanical performance indicators of lotus kernels and their soaking time was established using regression analysis. It was found that the elastic modulus, compressive strength of the lotus kernel, and the force of removing lotus plumules decreased with the increase of soaking time. Once the soaking time increased from 0 to 180 min, the longitudinal compressive modulus of lotus kernel decreased from 5.44 to 5.01 MPa, while the compressive strength decreased from 5.15 to 4.75 MPa, the lateral compressive modulus of lotus kernel decreased from 4.48 to 3.74 MPa, and the compressive strength decreased from 4.07 to 3.54 MPa, the force of removing the lotus plumules using a solid punch needle decreased from 18.26 to 16.16 N, and the force of removing the lotus plumules using a hollow punch needle decreased from 14.54 to 12.31 N. Finally, the air extrusion plumule-removing machine of fresh lotus seed was developed to conduct the plumule-removing experiment of lotus kernel with different soaking times. It was found that the soaking time of the lotus kernel had a direct impact on the plumule complete removal rate, kernel breakage rate, and plumule intactness rate. When the soaking time for the lotus kernel was relatively short, there was also the smaller length and width of the fissure at the tip of the lotus kernel, indicating that the lotus plumules could not squeeze out of the compressed air. The lotus kernel presented the higher hardness, elasticity modulus, compressive strength, and the force of removing the plumule, which can easily cause the breakage of the lotus kernel and plumule. Therefore, the plumule complete removal rate and the plumule intactness rate of the lotus kernel were lower, resulting in a higher lotus kernel breakage rate. The length and width of the fissure at the tip of the lotus kernel also increased, as the soaking time increased. The hardness of the lotus kernel, elastic modulus, compressive strength, and the force of removing the plumule decrease with the increase in soaking time, making it easier for the lotus plumule and lotus kernel to completely separate. Furthermore, the lotus kernel breakage rate remained relatively low with the increase in the plumule complete removal rate and plumule intactness rate. If the soaking time was too long, there was an increase in the moisture content, the breakage rate, as well as the length and width of the fissure at the tip of the lotus kernel, as the soaking time increased. Although compressed air can easily extrude the lotus plumule for the higher plumule complete removal rate, the hardness, elastic modulus, compressive strength, and force of removing the lotus plumule continued to decrease, with the increase in soaking time. The breakage of the lotus kernel and plumule was easily caused by the cracking at the interface between the lotus kernel and embryo, thus increasing the lotus kernel breakage rate with the low intactness rate of the lotus plumule. The optimal removing plumule of lotus kernel can be achieved when the soaking time was 120 mins (the plumule complete removal rate was 94.67%, the plumule intactness rate was 84.00%, and the lotus kernel breakage rate was 3.33%). The finding can provide the basic data support to improve the lotus kernel quality in the efficient and low-damage removal processing of plumule in fresh lotus seeds. [ABSTRACT FROM AUTHOR]

Raw materials are usually stored in the form of particles in silos, such as the food, chemical, and pharmaceutical field. The motion of granular materials can vary greatly in the flow of gases and liquids, due to their discrete particle aggregates. It is difficult to accurately explain using traditional theories, such as solid or fluid mechanics, and condensed matter physics. Particularly, the silo can serve as one of the most important carriers to store the particulate matter. It is still lacking in a comprehensive unified theory for the silo subjected to complex forces. Among them, the irregularity of rice seeds has a significant impact on the unloading in the silo, due to the nature of loose particles. Therefore, it is of great significance to clarify the impact of rice seed discharge flow in the silo. Auxiliary devices can also be added to transform the central into the overall flow bin. Simple and effective fluid modification can be used to adjust the structure of silos for the better particle flow. This study aims to explore the impact mechanism of different fluid modifications on the flow of rice seed particles during discharge in the silo. The transformation of the population flow pattern was achieved from the central to the overall flow for better population flow. The discrete element method (DEM) was selected to construct the traditional silo, vertical disturbance, and horizontal disturbance silo models. Rice seed particle models were established for the discharge simulation. The flow pattern was compared with the actual discharge experiment in the silo. A series of experiments was also conducted to verify the accuracy of the discrete element model and numerical simulation. The mass flow index (MFI) and z-axis particle velocity indicated that the particle velocity in the central region of traditional and vertically disturbed silos decreased with the increase of particle stacking height, whereas, the particle velocity increased in the sidewall region. There was a decrease in the particle velocity in the sidewall area of the horizontally disturbed silo, as the particle stacking height increased, whereas, the particle velocity increased in the central area. Traditionally, the conversion heights of the flow pattern were 130, 118, and 130 mm, respectively, in the vertically and horizontally disturbed silos. There was a variation in the vertical, horizontal, and angular velocity in the different areas of the silo. Specifically, the vertical velocity of the population decreased by 34.82% and 83.46%, respectively, compared with the traditional flow area of the silo under the action of the vertical and horizontal fluid. The fluctuation of population horizontal velocity increased, as the height of particle accumulation decreased in the silo population. The standard deviations of particle horizontal velocity were 0.027 3, 0.018 7, and 0.010 3, respectively, in the traditional silos, vertical and horizontal disturbance silos. There were similar changes in the particle angular velocity in the center and sidewall areas of traditional and vertical disturbance silos. The peak angular velocity was smaller in the center area of vertical disturbance silos, compared with the traditional silos. The variation of particle angular velocity was similar to the traditional silo in the flow area of a horizontal disturbance. But there was a small variation of particle angular velocity in a horizontal disturbance silo. The finding can provide the theoretical reference for the fluid design standards, structural and positional parameters, particularly for the high available area of the silo. [ABSTRACT FROM AUTHOR]

Precision agriculture can play an important role in the development of intelligent agricultural machinery, due to fertilizer saving, low labor intensity, and high work efficiency. Among them, the amount of fertilizer discharge can directly dominate the crop yield. Nevertheless, the fertilizer discharge device was in a closed state during the live broadcast operation. Therefore, the detection of particle fertilizer discharge has been one of the development trends of intelligent and precise operation. Various approaches have been developed to replace granular fertilizers in recent years, such as the rotational speed, doppler effect, dynamic weighing, photoelectric, visual, and electrostatic ones. However, the low accuracy of detection has limited in the rapeseed mechanical direct seeding, due mainly to the large and disordered flow of fertilizer particles. There is a high demand for the real-time detection of high-throughput granular fertilizers during high-speed operations. In this study, the high-throughput particle flow dispersion and diversion serialization of "collision dispersion +sieve diversion +spiral tube constraint" were proposed to fully meet the agronomic requirements of fertilization and high-speed operation in rapeseed direct seeding operation. The high detection accuracy was also obtained under the large and disordered flow of fertilizer particles. A parallel detection device was designed for the diversion order of granular fertilizer using the discrete diversion order mechanism. The key parameters were then determined for the sensing detection structure, uniform fertilizer tube, sieve diversion structure, and spiral tube. A multi-channel signal synchronous acquisition system was also designed for the detection device of rapeseed live broadcast granular fertilizer, according to the multi-channel parallel detection and sensing. A test bench was constructed using a spiral disturbance cone centrifugal fertilizer feeder. The device performance tests were conducted to verify the effectiveness of discrete diversion serialization. The results showed that there was a gradual decrease in the coefficient of variation for each channel diversion of the detection device in an inclined state, as the speed increased when the speed of the fertilizer discharger was 100-130 r/min (fertilizer discharge frequency 361.80-631.60 Hz). The coefficient of variation exceeded 6.08% for each channel diversion under normal field operation with an inclination of 0°-5°. Once the discharge frequency of single-channel fertilizer was 30-80 Hz, the accuracy of the detection device with the spiral tube increased by 7.3 percentage points, compared with the straight tube. The detection accuracy was not less than 90.11% within the speed range of 100~130 r/min after displacement compensation, which was 9.3 percentage points higher than before. The experiment of vibration fertilizer discharge showed that the low-frequency vibration (0-30 Hz) significantly improved the discretization of granular fertilizer and detection accuracy. There was a stable detection accuracy of intermediate frequency vibration (30-110 Hz). High-frequency vibration (110-150 Hz) broke the serialization constraint of granular fertilizer for low detection accuracy. There was no significant impact of different vibration frequencies on the uniformity of the flow distribution in the detection device. The coefficient of variation exceeded 4.98% for each channel diversion. Field experiments showed that there was no significant impact of the light, vibration, and dust on the detection device under normal field operating speeds of 4.3-7.0 km/h. The detection accuracy of the device was not less than 90.05% when the speed of the fertilizer discharger was 100-130 r/min. The detection device can be expected to detect the fertilization operation of the equipment, in order to improve the quality of fertilization operation [ABSTRACT FROM AUTHOR]

Rape straw is characterized by high stubble, thick stalks and difficulty to decompose. In this study, the opposing double-screw burying device was designed to combine the crushing-rotary tillage-mulching machine for the rape straw returning. The coefficient of variation of straw mass distribution and the percentage of straw mass in different soil layers were taken as the evaluation standard of straw returning. A four-factors and four-level orthogonal test was then conducted to determine the influencing parameters, such as the helix angle of the opposing double-screw burying device, rotary speed, forward speed, and the length of the straw. The results show that the coefficient of variation of straw mass distribution in different soil layers slowly decreased and then sharply increased with the increase of the helix angle. The better uniformity was obtained for the rape straw returning when the helix angle was below 60°. Furthermore, the coefficient of variation of straw mass distribution in different soil layers decreased and then increased with the increase of the rotary speed. Specifically, the displacement of the straws increased, when the rotary speed was below 210 r/min. The reason was that the kinetic energy of the straws increased with the increase of the rotary speed. Once the rotary speed exceeded 210 r/min, the displacement of the straws increased with the increase of the straw kinetic energy, and then the straw was screened and aggregated from the soil. Different specific gravity thus caused the uneven distribution of the straw in the soil. There was a similar trend of decreasing and then increasing in the coefficient of variation of straw mass distribution in different soil layers, as the forward speed increased. The straw was separated from the soil under excessive disturbance at the low forward speed, where the machine stayed put. By contrast, the variation coefficient also increased at the high forward speed with the weak function of the opposing double-screw mulching device. There was a positive relationship between the variation coefficient and the straw crushing length, indicating the shorter the length was, the smaller the variation coefficient was. The significant degree in the coefficient of variation of straw mass distribution was ranked in the descending order of the straw length, helix angle, rotary speed, and forward speed. The highest proportion of straw mass was in the upper layer (0-50 mm). There was a gradual decrease with the deepening of the depth. The uniformity of rape straw returning was also achieved to increase the straw in the deep soil (＞100-150 mm). The percentage of straw mass varied in the different soil layers with the four factors between the upper layer (0-50 mm), indicating the opposite in the deep soil (＞100-150 mm). But there was a small change in the percentage of straw mass in the intermediate soil layer (＞50-100 mm). The uniformity of the mixed straw mulching was improved to reduce the length of straw crushing reducing, while improving the degree of mixing between the straw and the soil without excessive disturbance. In terms of the helix angle of 60°, the rotary speed of 210 r/min, the forward speed of 0.6 m/s, and the length of straw of 6 cm, the percentages of straw mass in the depth of 0-50, ＞50-100, and ＞100-150 mm were 43.97%, 33.28%, and 22.75%, respectively, where the coefficient of variation of straw mass distribution of straw mass was 26.43%. The percentage of straw mass in the upper layer was reduced by 2.36 percentage points, whereas, the percentage of straw mass in the deep depth increased by 7.18 percentage points, and the coefficient of variation of straw mass distribution was reduced by 12.6 percentage points, indicating the best uniformity of rape straw returning and the best quality of the seed bed, compared with the orthogonal experiment groups. The finding can provide a strong reference to improve the quality of rape straw returning. [ABSTRACT FROM AUTHOR]

Task allocation can dominate the energy consumption in agricultural equipment during operations. Particularly, energy efficiency can promote sustainable development in the context of carbon emissions peaking and carbon neutrality in modern agriculture. Among them, tasks can be programmed into integral parts of operations in multiple agricultural machinery. In the realm of collaborative multitasking, multiple agricultural machines can be utilized to execute the operation tasks within individual fields. The well-defined partitioning of their duties can substantially reduce the overlapping coverage areas. As such, this allocation can then translate into a more effective reduction in energy consumption. Furthermore, partial idle time can be offered for agricultural machinery, when the number of tasks exceeds the available number of machines. The task allocation can also have the potential to enable the simultaneous deployment of multiple agricultural machines within the same field. In this study, a tradeoff was provided for the operational pathway and the number of rows. The operational area was then established for each agricultural machine. The potential conflicts were also effectively resolved in the course of the multimachine collaboration. Taking the deep tillage operation model as a case study, both effective and energy-efficient collaborative operations were achieved within the agricultural machinery group. To this end, a systematic analysis was performed on the energy consumption during collaborative operations. Subsequently, a multi-objective optimization was proposed to minimize the energy consumption and the completion time of the agricultural machinery group, wherein the task volume was set as the optimization variable. INSGA-II was employed to optimize this model, including the initialization stage, logistic mapping and incorporating, as well as reverse learning. An improved heuristic method of population initialization was employed to enhance the population diversity. In addition, the barrier function was designed to prevent the solution in local optima. Moreover, the uniform crossover operator and simulated single-point mutation were combined to ensure the integrity of integer encoding. The efficacy and practicality of the improved model were systematically evaluated in real-world case studies using deep loosening operations. The results demonstrate that the improved model achieved a notable 4.35% reduction in machinery group energy consumption, and a 4.51% reduction in completion time, compared with the conventional NSGA-II. Furthermore, there was a remarkable 5.51% reduction in the machinery group energy consumption and an impressive 42.65% reduction in the completion time, compared with conventional operations. In essence, the optimization fully met the immediate needs of task allocation across various work scenarios during collaborative multi-machine operations in practical agricultural production. For instance, the allocation of operating rows can be expected to efficiently define the working areas in the seeding and harvesting machines with different working widths, compared with the conventional parallel operation. This innovation can also lead to more optimal solutions in group task allocation. [ABSTRACT FROM AUTHOR]

This study investigated adoption and determinants of adopting the bed planter developed by Bangladesh Agricultural Research Institute (BARI) and the impacts on productivity and farm income in the Rajshahi and Faridpur districts of Bangladesh. Primary data were collected during 2019 from 41 adopters and 80 non-adopters using a multi-stage random sampling technique. On average, the adoption rate of the BARI bed planter was 15%. Socio-economic characteristics such as farm size, farming experience, training, and extension contacts significantly differed between adopters and non-adopters. A probit model showed that farmer experience, extension contacts, and farmers' club membership were key variables influencing the likelihood of BARI bed planter adoption. Policy recommendations based on these results include modifying current extension approaches and increasing investment in farm machinery. [ABSTRACT FROM AUTHOR]

The paper evaluates the possibility of using dissimilar materials joined by welding technology in the construction of agricultural machinery. The desire to design larger and more efficient structures requires designers to combine materials with different mechanical and structural properties. In such a case, it is very important to properly select welding parameters so that, on the one hand, the quality of the joint meets the standard requirements, and on the other, the welding process is not too energy-intensive. In this paper, overlay joints connecting S355 steel with Strenx 700 steel were analyzed in terms of strength for three different values of welding parameters and different thicknesses. The starting point was the reference parameters recommended by the company's welding technologists, which were reduced by 10 and 20% according to the linear welding energy. The study compared the strength, ductility and macrostructure of the joints, as well as the energy intensity of the process. The proposed dissimilar joints achieved approximately a 10% increase in the strength limit of the components in comparison to the previously recommended welding parameters. Additionally, finite element analysis calculations of the improved designs showed significant weight reduction (up to 40%) for the relevant agricultural machinery components. [ABSTRACT FROM AUTHOR]

In the research, an agricultural machinery reliability analysis method based on fusion algorithm is proposed, a optimal radial basis function neural network and M-C statistical test method are mixed to obtain an agricultural machinery reliability. This mixed model is used to reliability design and calculation of a cotton picker, the simulation model of reliability control and calculation for a cotton picker based on the mixed algorithm is set up, and reliability of the level spindle of a cotton picker is computed through the mixed method, and the effect of important factors on the cotton picker is predicted. The level spindle is critical force-bearing parts of a cotton picker and breakdown occurs frequently, their reliability control and optimization are key problems that need to be solved urgently, this study builds an innovative approach for the reliability optimization and design of agricultural equipments. [ABSTRACT FROM AUTHOR]

Agricultural machinery distribution programs are key components of the Philippine government to strengthen its economic productivity. However, concerns were reported that some of the distributed machines were under-utilized or unutilized in their respective farms. This study is focused on the development of a GIS-based model of determining suitable lowland rice areas for two-wheel and four-wheel tractors. A numerical rating system was designed that assigns a suitability score from three criteria, namely slope, road network proximity, and flood risk, based on established scales. Analytical Hierarchy Process was used as an approach to determine the relative influence in which results show that slope has the greatest weight (65%) followed by flood risk and road network proximity with 20% and 15%, respectively. The total suitability score (TSS) is then determined by getting the weighted average of the individual suitability scores. Land suitability mapping on the study area, the CALABARZON region, show that majority of the lowland rice areas are highly suitable for two-wheel and four-wheel tractors (81.39%) while some areas fall under marginal (15.03%) and moderate suitability (3.58%). Geotagged locations of the distributed agricultural tractors from 2015 to 2020 reveal that 78% of the distributed two-wheel tractors and 80% of four-wheel tractors in the region are situated in highly suitable areas. The GIS-based suitability model generated in this study can be utilized by the government to improve its machine distribution programs of two-wheel and four-wheel tractors in lowland rice farms. [ABSTRACT FROM AUTHOR]

Digging resistance can dominate the energy consumption of potato-digging shovels in clayey black soil areas. In this study, a drag-reducing potato-digging shovel was designed using a bionic ripple structure. Among them, the rhizoma imperatae membranous sheath was taken as a bionic prototype. The optimal parameters were also determined for the drag reduction performance using the discrete element method (DEM) and soil trench test. The drag reduction and digging performance of the bionic digging shovel were then verified by the field test with the indexes of fuel consumption per unit time and drag force. The longitudinal arrangement was optimized for the better performance of the bionic digging shovel. Specifically, the optimal parameters of the bionic digging were A=2.5 mm, ω=0.5 in the soil trench test. The results show that the ripple shovel (y=2.5cos0.5x) achieved excellent properties of drag reduction at the soil moisture content under the condition of 35%, where the ordinary flat shovel drag reduction rate increased by 12.69%. In the soil moisture content of 65%, the spraying coating viscosity ripple shovel (y=2.5cos0.5x) still showed excellent properties of drag reduction, whereas the drag reduction rate of ordinary flat shovel increased by 18.27%. A comparison test was carried out between the ordinary flat and the bionic longitudinal ripple shovel. The drag-reduction rate of the bionic longitudinal corrugated shovel increased by 14.45%, and the fuel consumption rate was reduced by 17.15%. Bionic shovels presented better accumulation in the soil on the surface of the shovel rather than that in the shovel in the process of the mining operation. The bionic structure reduced the contact area and time between the soil on the surface of the shovel. The bionic shovel was performed on the short stagnation of the clod time under driving force in the same circumstances. The mining operation time of the shovel body was reduced to realize the energy)saving drag reduction in the same trip. The surface tension of the soil was also reduced using a bionic shovel surface with a low surface energy coating. The adhesion force of soil per unit area greatly contributed to the shovel of soil adhesion. There was a great decrease in the static friction coefficient between the shovel and the soil plane. Soil retention or accumulation was reduced for the soil conditions of movement and space on the surface of the shovel. Therefore, the bionic longitudinal ripple shovel performed better drag reduction, indicating the reasonable design of the bionic structure. The bionic structure of soil touching parts is of great significance in the application of potato harvesting and digging operations under clay and heavy black soil. The findings can lay a sound foundation for the energy saving and consumption reduction of the whole machine. [ABSTRACT FROM AUTHOR]