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Purpose: Agricultural extension services in poor countries often identify opinion leaders based on criteria such as wealth and social status. We explore the effectiveness of this top-down approach by analysing the role of so-called model and nodal farmers in the diffusion of malt barley in a highland community in Ethiopia. Research approach: We use a retrospective case study design where we combine quantitative network analysis with qualitative data. Findings: Nodal farmers played a more central role in knowledge diffusion of the technology than model farmers. While model farmers were wealthier and better connected to the local authorities, nodal farmers were socio-economically more similar to their fellow farmers. Nodal and model farmers, as well as farmers closely connected to them, had a significantly higher adoption index than the rest. Practical implications: The diffusion of knowledge is an important condition for the adoption of modern agricultural technologies, but it is not enough, particularly when access to external inputs is limited. Moreover, relying on assumed opinion leaders has its limitations and may even reinforce existing inequalities. Theoretical implications: This paper has shown the complementarity of network approaches. We propose network approaches such as social network analysis to identify community brokers who emerge from bottom-up or clan-based, political, knowledge networks that mediate access to agricultural technologies. Originality: Our combined research approach differs from the mainstream of studies in this field that employ either ethnographic fieldwork or (spatial-)econometric methods. We aim to create a bridge between the often separated worlds of (technical) agronomic research, (qualitative) rural sociology, and (quantitative) econometric analysis.

This paper describes an innovative method to provide a micro-electric tractor which has been developed as part of an initiative that aims to provide socially inclusive and affordable green energy solutions to smallholders in sub-Saharan Africa. It utilizes a 15.0-kW solar array and battery system to power micro-electric tractors for an agricultural practice called deep bed farming in Malawi. Deep bed farming increases smallholder crop yield by about two and half times, which increases revenue by up to 12 times. The extra revenue can then be used to perpetually purchase domestic energy from the solar array, creating a self-sustaining model for decentralized energy access. However, the requirement for land preparation is onerous, and mechanization is needed to help overcome barriers to entry. This paper describes the technical requirements of a solar base station and micro-tractor for use with the deep bed farming technique. The paper covers the 5.9 kWp modular solar design and a 10.0-kWh rated micro-tractor. Testing was undertaken at an isolated grid in Loughborough as a precursor for large-scale testing in Malawi. [ABSTRACT FROM AUTHOR]

Agricultural mechanics is an important component of a well-rounded school-based agricultural education (SBAE) program. Within agricultural mechanics courses lies a plethora of topics and skills to be covered. Adequate tools and equipment are vital in preparing students to fill an expanding, 21st century workforce. The issue of inadequate teaching materials has been well documented throughout the entire educational system, and such inadequacies may leave gaps in students' ability to become proficient within agricultural mechanics. A paper-based questionnaire was distributed to all teachers in attendance at the Iowa teachers' conference. This descriptive study sought to identify teacher-perceived adequacy of available tools and equipment to teach agricultural mechanics in Iowa. The researchers found that many agricultural education teachers in Iowa are ill-equipped to teach many concepts within agricultural mechanics due to a reported lack of adequate tools and equipment. Agricultural education teachers in SBAE programs should ensure adequate tools and equipment to meet curricular and industry standards. It is recommended to examine purchasing decisions of tools for inclusion in the agricultural mechanics laboratory as well.

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering 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.)

With the rapid advancement of agricultural mechanization, intelligent header technology has emerged as a pivotal element in optimizing the efficiency and quality of grain combine harvesters. This paper offers a comprehensive analysis of the current state of intelligent header technology, with a particular emphasis on the structure, working principles, contour-following mechanisms, and height control technologies. By integrating cutting-edge sensor technologies, advanced control algorithms, and optimized mechanical designs, intelligent headers can achieve precise control over height and posture, thereby significantly reducing crop losses and enhancing both harvesting efficiency and quality. Despite substantial progress, challenges remain in areas such as response speed, real-time performance, height measurement accuracy, and control algorithm effectiveness. Future research will likely concentrate on improving control system performance, refining component and system designs, and incorporating emerging technologies to better accommodate diverse crops and complex terrains. This paper also provides a critical evaluation of current limitations in intelligent header research and projects future trends, offering valuable theoretical and practical insights for optimizing header structures, minimizing losses, and enhancing intelligent functionalities. The ultimate aim is to drive continuous innovation and advancement in header technology for grain combine harvesters. [ABSTRACT FROM AUTHOR]

Effective succession planning is a critical aspect of leadership continuity and organizational success. This article delves into the succession planning strategies of two prominent agricultural machinery companies, John Deere and Titan Machinery, providing insights into their distinctive approaches during leadership transitions. John Deere, a renowned global leader in agriculture and related services, employed a strategy that centred around continuous improvement and the development of leaders capable of transmitting their knowledge to others. Their introduction of the “teachable point of view” (TPOV) and the organization of Leadership EDGE events exemplify their commitment to nurturing a culture of leadership development. In contrast, Titan Machinery adopted a strategy that emphasized experience and continuity. With Bryan Knutson, a seasoned executive within the organization, taking over as CEO, the company focuses on operational excellence, expansion, and an unwavering commitment to customer service. The outcomes of these strategies include seamless leadership transitions, a focus on leadership development, the preservation of organizational culture, a commitment to operational excellence, and the introduction of fresh strategic visions for future growth. The focus is on examining the strategies, approaches, and outcomes of their succession plans, with an emphasis on commonalities and differences between the two companies. The paper aims to provide insights into effective succession planning practices within the context of these organizations. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering 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.)

Plastic film mulching technology can effectively enhance crop yield and quality, and the use of mulch has been increasing in recent years; however, the problem of mulch residue is worsening due to the large amount of recycling work and slow natural degradation. In this study, a potato seedling killing and residual film recycling machine is designed to provide good working conditions for potato harvesters before harvesting in response to the problems of difficult separation of film tangles, the low net rate of recycling due to the mixing of residual film with soil, and the high soil content in residual film recycling operations in northwest China. The machine is based on the potato monoculture and double row planting mode in Gansu area. This paper puts forward the overall design scheme and carries out the theoretical analysis and parameter determination of the key components, such as the seedling killing device, the film surface cleaning device, the film unloading device, and so on. Using EDEM software to carry out the virtual simulation test and Design-Expert13 to analyze the test results, we determined the optimal working scheme for the machine, with a forward speed of 0.8 m/s, a film gap of 125 mm, and a spiral stirrer speed of 600 r/min. Based on a field test for verification, the test results show that the machine's residual film recovery rate was 83.3%, the impurity rate was 3.8%, and the rate of injury to the potatoes was 1.4%. The machine meets the requirements of national and industry standards, and it can simultaneously realize straw crushing, film surface cleaning, residual film recycling, and hydraulic film unloading operations, with better operating results and while reaching the expected results. It can also provide a reference for the design and testing of a seeding and residual film recycling machine. [ABSTRACT FROM AUTHOR]

To address the lack of specialized machinery for the mechanical weeding of SCSCP in the Huang Huai Hai region, this study designs a mechanized inter-row weeding machine for SCSCP. The machine features a reciprocating weeding shovel and an adaptive contouring mechanism for cultivation and soil loosening. This paper details the machine's principles by analyzing the geometric relationship and mechanical model between the corresponding profiling quantities, which determine the relevant parameters for adaptive contouring to ensure stable operation on undulating ground. Furthermore, by optimizing the design of the weeding shovel's reciprocating motion mechanism, combining EDEM simulation with the weeding shovel–soil interaction, it has been determined that, at various PTO shaft speeds, the optimal weeding efficacy is achieved with a blade-type weeding shovel structure when operating at a forward speed of 3.5 km/h. Field experiments were conducted with different PTO shaft speeds and weeding depths, using weeding and seedling injury rates as performance indicators. The results showed that, based on the optimal speed, the PTO shaft speed is 760 r/min, the operating depth is 3–5 cm, and the average row weeding rate is 90.4%. The average soybean and corn seedling injury rate is 3.4% and 4.2%, meeting the technical requirements for mechanical weeding. [ABSTRACT FROM AUTHOR]

Agricultural tractors are an essential agricultural power source. Therefore, the scientific literature tests have described agricultural tractors' evolution over time and determined future trends. This paper uses bibliometric tools to assess the agricultural evolution of tractor testing from 1969 to 2022 to ascertain the publication's scientific perspective on operational, ergonomic, and energy performance. We searched for relevant research in the Scopus and Web of Science (WOS) databases. The data were processed in RStudio software version 4.4.1, and we used elaborated bibliometric maps to research evolution, major journals, studies, countries, and keywords. The first research mainly concerned the development of new wheelsets, more efficient engines, and fuel consumption prediction models. After the 2000s, environmental protocols contributed to increasing publications on biofuels and renewable energies. Recently, an intense process of robotization in autonomous vehicles has improved to allow the replacement of combustion engines. Ergonomics and safety have been less recurrent topics in recent years, indicating a stable level in the actual research. New machine control models involving artificial intelligence are currently applied to obtain test results without using the machine in the field. These virtual models reduce costs and optimize resources. The most common terms were "tractor" and "agricultural machinery". The terms "Electric tractor", "agricultural robots", and "Matlab" indicate solid trends for future research. [ABSTRACT FROM AUTHOR]

This paper presents a path tracking algorithm based on a fuzzy control pure tracking model for autonomous navigation of 4WS agricultural machines. The aim of this research is to implement path tracking for unmanned 4WS agricultural machinery and to solve the problem of difficult determination of forward-looking distances in pure tracking algorithms. By using the pure tracking algorithm model and a fuzzy controller, this paper converts the heading deviation and lateral deviation in one control cycle into the sum of lateral deviation as the first input to the fuzzy controller and the vehicle travel speed as the second input to the fuzzy controller, thus outputting the actual forward-looking distance. In order to verify the practicality, accuracy, and path tracking precision of the proposed path tracking algorithm, a straight-line path tracking test under variable speed conditions and a turning path tracking test under non-fixed forward-looking distance conditions were carried out using a test platform after simulation on MATLAB/Simulink in this paper. The test results show that: in the straight-line path tracking process, the maximum overshoot is 0.123 m, and after stable driving, the maximum lateral deviation of the straight-line tracking part is 0.058 m and the steady-state deviation is 0.039 m; in the bow-turn path tracking process, the absolute value of the maximum lateral deviation of the actual driving trajectory of the farm machine from the desired path is 0.139 m, and the average tracking deviation is 0.041 m. It can be seen that the path tracking control algorithm proposed in this paper has good tracking accuracy as well as convergence, and can meet the demand for the autonomous navigation function of 4WS agricultural machinery, which has a certain application value. [ABSTRACT FROM AUTHOR]

To address the inefficient crushing of fertilizer during the mechanized spreading process caused by the caking of high-humidity organic fertilizer, a fertilizer spreader with a combined rotor and lining plate crushing mechanism was proposed in this paper. With the introduction of the basic structure and working principle of the spreader, a particle group model for an organic fertilizer consisting of both caked and bulk fertilizer was built, based on the Hertz–Mindlin model with bonding and the Hertz–Mindlin model with JKR contact, in EDEM to construct an organic fertilizer-crushing-and-spreading model. With the rotor speed, the axial distance of the hammer, and the number of circumferential hammer groups as the experimental factors and the maximum broken bond rate of the caked organic fertilizer and the minimum coefficient of variation of spreading uniformity as the experimental indices, the Box–Behnken test method was employed to establish regression equations for response surface analysis and multi-objective optimization of the test results. The results indicated that, when the rotor speed was 6.47 Hz, the axial distance of the hammer was 90.30 mm, the number of circumferential hammer groups was five, the broken bond rate reached 90.86%, and the coefficient of variation was 21.45%. Verification tests under these conditions showed a broken bond rate of 90.03% and a coefficient of variation of 22.12%, which were consistent with the optimization results. Therefore, our research provides a reference for the structural design of an organic fertilizer spreader and the optimization of its working parameters. [ABSTRACT FROM AUTHOR]

Maintaining agricultural machinery is crucial for efficient mechanized farming. Specifically, diagnosing faults in rolling bearings, which are essential rotating components, is of significant importance. Domain-adaptive technology often addresses the challenge of limited labeled data from a single source domain. However, information transfer can sometimes fall short in providing adequate relevant details for supporting target diagnosis tasks, leading to poor recognition performance. This paper introduces a novel fault diagnosis model based on a multi-source locally adaptive graph convolution network to diagnose rolling bearing faults in agricultural machinery. The model initially employs an overlapping sampling method to enhance sample data. Recognizing that two-dimensional time–frequency signals possess richer spatial characteristics in neural networks, wavelet transform is used to convert time series samples into time–frequency graph samples before feeding them into the feature network. This approach constructs a sample data pair from both source and target domains. Furthermore, a feature extraction network is developed by integrating the strengths of deep residual networks and graph convolutional networks, enabling the model to better learn invariant features across domains. The locally adaptive method aids the model in more effectively aligning features from the source and target domains. The model incorporates a Softmax layer as the bearing state classifier, which is set up after the graph convolutional network layer, and outputs bearing state recognition results upon reaching a set number of iterations. The proposed method's effectiveness was validated using a bearing dataset from Jiangnan University. For three different groups of bearing fault diagnosis tasks under varying working conditions, the proposed method achieved recognition accuracies above 99%, with an improvement of 0.30%-4.33% compared to single-source domain diagnosis models. Comparative results indicate that the proposed method can effectively identify bearing states even without target domain labels, showcasing its practical engineering application value. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering 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.)

This paper presents the design of an intra-row obstacle avoidance shovel-type weeding machine. Theoretical analysis of intra-row weeding components guided the determination of the structures and parameters for key parts, including the signal acquisition mechanism, automatic obstacle avoidance mechanism, and weeding shovel. Furthermore, a hydraulic system was designed to support these functions. The design aims to optimize intra-row weeding operations, reduce labor costs, enhance weed control effectiveness, and prevent collisions between weeding equipment and grapevines. Through the construction of a mathematical model, the analysis determined the necessary minimum return speed of the hydraulic cylinder for the intra-row weeding shovel to avoid grapevines. We also established a reasonable range for the extension speed of the hydraulic cylinder to minimize areas missed during weeding. Further analysis showed that using the minimum return speed of the hydraulic cylinder effectively reduced missed weeding areas. A virtual prototype model of the weeding machine was created in ADAMS. Using the coverage rate of weeding operation as the evaluation index, single-factor simulation tests determined that the extension speed of the piston rod in the obstacle avoidance hydraulic cylinder and the forward speed of the weeding machine are the main influencing factors. The preset threshold of the control system, which triggered the automatic obstacle avoidance mechanism when the obstacle avoidance rod reached a specific angle (the "Angle Threshold"), was identified as a secondary influencing factor. Other factors were considered irrelevant. Hydraulic cylinder extension speed, weeding machine forward speed, and angle threshold were chosen as the influencing factors. Following the principles of a Box–Behnken experimental design, a quadratic regression combination experiment was designed using a three-factor, three-level response surface analysis method. The evaluation criterion focused on the coverage rate of weeding operation. A regression model was developed to determine the coverage rate of the weeding operation, identifying the optimal parameters as follows: obstacle avoidance hydraulic cylinder extension speed of 120 mm/s, forward speed of the weeding machine at 0.6 m/s, and an angle threshold of 18°. The optimized coverage rate of the weeding operation achieved 86.1%. This study serves as a reference for further optimization of intra-row weeding machines in vineyards and for other crops. [ABSTRACT FROM AUTHOR]

To address the problems of low bright rates and high rates of potato injuries, a left and right-hand rotation combination of potato–soil separation devices was developed. Its overall structure and working principle were introduced. A Texture Analyzer and pressure sensor were used to measure the force threshold of different varieties of potatoes. A discrete element model of separation rollers and potatoes was established. The collision characteristics of potatoes were analyzed using the device inclination angle, rotational speed, and the center distance of the separation rollers as test factors. A field trial was carried out to optimize the best combination of factors by taking the rate of injured potatoes, bright potatoes, and skin-breaking rate as the test indexes. The force threshold for skin-breaking injury in potatoes was found to be 190–195 N. When the inclination angle of the device was 6°, the rotation speed of the separation roller was 100 r/min, and the distance between the centers of the separation rollers was 79 mm. The rate of injury was 1.25%, the rate of bright potatoes was 99.01%, and the rate of skin-breaking was 1.58%. When the inclination angle of the device was 8°, the rotational speed of the separating roller was 80 r/min, and the center distance of the separating roller was 79 mm, the rate of injured potato was 1.43%, the rate of bright potato was 98.64%, and the rate of broken skin was 1.77%. This paper offers an optimized reference for the effectual removal of sticky soil. [ABSTRACT FROM AUTHOR]

Soil compaction is generally viewed as one of the most serious soil degradation problems and a determining factor in crop productivity worldwide. It is imperative to understand the processes involved in soil compaction to meet the future global challenges of food security. In this work, we used co‐occurring keyword analysis to summarize 3491 papers on soil compaction over the past 40 years, elaborating on the main research focuses such as the causes, influencing factors, and effects of soil compaction on crops, and the mitigation and prevention of soil compaction. This review provides a comprehensive discussion of the effects of soil compaction, including altering soil structure, increasing bulk density (BD) and penetration resistance (PR), and reducing porosity and soil hydraulic properties. Notably, based on the 387 data points of 11 papers about BD, our results demonstrated soil compaction on average, increased BD by 7.6%, 6.9%, and 3.2% in the medium‐, coarse‐, and fine‐textured soils, respectively. Based on the 264 data points of 18 papers, in the 0–30 cm soil layer, compaction increased penetration resistance (by 91% in the coarse‐textured, 84.2% in the medium‐textured, and 8.8% in the fine‐textured soils). Compacted soil limits the access of crop roots to water and nutrients, leading to poor root development and reduced crop productivity. There was a difference in soil compaction sensitivity between the different crops, but crop growth and yield showed an overall worsening trend with increasing degrees of compaction. This review collected data points on 142 crop yields and found that wheat, barley, corn, and soybean yields decreased by an average of 4.1%, 15.1%, 37.7%, and 22.7%, respectively, in the BD range of 1.1–1.8 Mg/cm3 after compaction. Additionally, the effectiveness of different compaction mitigation measures, including natural, tillage, and biological, is systematically discussed. Compared with soil compaction mitigation measures, prevention should be the top priority although there is still a lack of practical prevention methods. Soil conditions and agricultural machinery type are the main factors affecting the risk of soil compaction in the process of soil compaction. Therefore, it is particularly important to optimize the soil working conditions in the field and the type of farm machinery used to reduce the risk of soil compaction. This initiative is pivotal for ensuring sustainable systems for food production and recovering crop productivity from compacted soil. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering 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.)

In order to further exploit the production advantages of rice throwing, this paper proposes a systematically designed throwing device suitable for integration with unmanned aerial vehicles (UAVs). The device primarily comprises a seedling carrying and connection system, a seedling pushing mechanism, and a seedling guiding device. The operational principles and workflow of the device are initially elucidated. Subsequently, an analysis of factors influencing rice throwing effectiveness is conducted, with throwing height, working speed, and the bottom diameter of the seedling guide tube identified as key factors. Seedling spacing uniformity and seedling uprightness are designated as performance indicators. A three-factor, three-level response surface experiment is conducted, yielding regression models for the experimental indicators. Through an analysis of the response surface, the optimal parameter combination is determined to be a throwing height of 142.79 cm, a working speed of 55.38 r/min, and a bottom diameter of the seedling guide tube of 43.51 mm. At these parameters, the model predicts a seedling spacing uniformity of 88.43% and a seedling uprightness of 88.12%. Field experiments validate the accuracy of the optimized model results. Experimental data indicate that under the optimal operational parameters calculated by the regression model, the seedling spacing uniformity is 86.7%, and the seedling uprightness is 84.2%. The experimental results meet the design requirements, providing valuable insights for UAV rice-throwing operations. [ABSTRACT FROM AUTHOR]

To realize monitoring of trenching depth, this paper built an online monitoring system and measured depth at three levels of 25 cm, 30 cm, and 35 cm. The test results show that the measured data have large fluctuations and low precision and are smaller than the actual value. For the above problems, this paper proposes a comprehensive noise reduction filtering algorithm based on wavelet noise reduction and Kalman filtering, in which the output of the preprocessing part of the wavelet noise reduction is used as the input of the postprocessing part of the Kalman filter. This article first selects the optimal combination of wavelet threshold denoising parameters such as wavelet function, decomposition level, and threshold denoising rule. Then the optimal Q/R value and the combination of Q and R parameters for the Kalman filter reprocessing part are explored. Finally, the comprehensive filtering correction algorithm and Kalman filtering algorithm are used to process the above-measured data. By comparing the results of the two algorithms, we found that for the local data, the variance decreased by 0.0207, 0.0398, and 0.0609, and the mean square deviation decreased by 0.0609, 0.0854, and 0.0457. The mean values of the two algorithms are very close. Similarly, for the global data, the variance decreased by 0.0182, 0.0549, 0.0428, and the mean square deviation decreased by 0.0359, 0.041, 0.0323. There is no significant difference in means between the two algorithms. The results show that the comprehensive algorithm improves the quality of trenching depth data and has certain significance for precision agriculture. [ABSTRACT FROM AUTHOR]