Search Results (73)

This paper presents a bionic extended Kalman filter (EKF) state estimation algorithm for agricultural planters, inspired by the bionic mechanism of migratory birds navigating in complex environments, where migratory birds achieve precise localization behaviors by fusing multi-sensory information (e.g., geomagnetic field, visual landmarks, and somatosensory balance). The algorithm mimics the migratory bird’s ability to integrate multimodal information by fusing laser SLAM, inertial measurement unit (IMU), and GPS data to estimate the position, velocity, and attitude of the planter in real time. Adopting a nonlinear processing approach, the EKF effectively handles nonlinear dynamic characteristics in complex terrain, similar to the adaptive response of a biological nervous system to environmental perturbations. The algorithm demonstrates bio-inspired robustness through the derivation of the nonlinear dynamic teaching model and measurement model and is able to provide high-precision state estimation in complex environments such as mountainous or hilly terrain. Simulation results show that the algorithm significantly improves the navigation accuracy of the planter in unstructured environments. A new method of bio-inspired adaptive state estimation is provided. Full article

The rural border areas of Serbia have been undergoing significant demographic shifts and transformations in land use. Between 2002 and 2022, these regions experienced a continuous population decline, an increase in the average age, and a growing share of single-person households. Simultaneously, there has been a reduction in agricultural land and a noticeable expansion of forested and grassland areas, particularly in hilly and mountainous terrain. This paper aims to explore the interrelationship between demographic indicators and land cover changes in these areas. Pearson’s correlation analysis was applied to data from the national population censuses and the CORINE Land Cover datasets for 1990 and 2018. The strongest positive correlation was found between the decline in the number of households and the reduction in agricultural land. Conversely, the expansion of forested areas showed a negative correlation with most demographic indicators. The findings reflect trends similar to those observed in other Eastern European countries but also reveal specific patterns of spatial marginalization unique to Serbia. In the study, the conclusion leads to the idea that depopulated border areas are in transition between past and future functions that will be influenced by their resource base. Full article

Aiming at key issues in harvesting film-covered potatoes in hilly and mountainous areas—incomplete residual film collection, poor potato–soil separation, and high damage from potato-collecting devices—this study developed a crawler self-propelled potato harvester suitable for these regions. This study first expounds the overall structure and working principle of the potato harvester and then conducts principal analysis and structural design for key components (film-collecting device, digging device, primary conveying and separating device, secondary conveying and separating device, and intelligent potato-collecting device) from the perspectives of material force and movement. Finally, field performance tests were carried out in Huangzhong County, Xining City, Qinghai Province. The test results show that the machine can achieve an operation effect with a potato harvest loss rate of 2.4%, a potato damage rate of 1.4%, an impurity content rate of 2.8%, a skin-breaking rate of 2.7%, and a residual film cleaning rate of 89.6%, meeting the potato harvesting needs of this region. The lightweight self-propelled crawler potato harvester designed in this paper can realize functions such as residual film collection, potato–soil vibration separation, manual auxiliary sorting, and intelligent potato boxing, providing technical and equipment references for the harvesting of film-covered potatoes in complex terrain areas. Full article

This study investigates the dynamic performance of mountainous crawler tractors during small-radius slope steering, providing theoretical support for power machinery design in hilly and mountainous regions. Addressing the mechanization demands in complex terrains and existing research gaps, a steering dynamics model is established. The model incorporates an amplitude-varied multi-peak cosine ground pressure distribution, employs position vectors and rotation matrices to characterize 3D pose variations in the tractor’s center of mass, and integrates slope angle, soil parameters, vehicle geometry, center-of-mass shift, bulldozing resistance, and sinkage resistance via d’Alembert’s principle. Numerical simulations using Maple 2024 analyzed variations in longitudinal offset of the instantaneous steering center, bilateral track traction forces, and bulldozing resistance with slope, speed, and acceleration. Variable-gradient steering tests on the “Soil-Machine-Crop” Comprehensive Experimental Platform demonstrated model accuracy, with <8% mean error and <12% maximum relative error between predicted and measured track forces. This research establishes a theoretical foundation for predicting, evaluating, and controlling the steering performance/stability of crawler tractors in complex slope conditions. Full article

Accurate surface wind speed data are vital for atmospheric science, climatology, and energy applications. European Centre for Medium-Range Weather Forecasts Reanalysis v.5 (ERA5), as one of the most widely used global reanalysis datasets, has insufficient assessment of its applicability across diverse landform types. Using the gridded observational dataset over China (CN05.1) and the Global Basic Landform Units dataset, this study evaluated the surface wind speed data from ERA5 over various altitudinal zones and undulating terrains in China via root-mean-square differences (RMSD) and mean absolute percentage error (MAPE) against CN05.1 observations. Results reveal significant regional variations, with ERA5 effectively capturing the spatial distribution of mean wind speeds but systematically underestimating magnitudes, particularly in plateau and mountainous regions. ERA5 reanalysis fails to reproduce the observed altitudinal increase in surface wind speed. Elevation-dependent biases are prominent, with RMSD and MAPE increasing from low-altitude to high-altitude areas. Terrain complexity exacerbates errors, showing maximum deviations in high-relief mountains and minimum deviations in hilly regions. These biases evolve seasonally, peaking in spring and reaching minima in winter. In summary, discrepancies between observations and ERA5 vary with altitude, topographic relief, and season. The most significant deviations occur for spring surface winds in high-altitude, high-relief mountains, with mean RMSD reaching 3.3 m/s and MAPE 553%. The findings highlight the limitations of ERA5 reanalysis data in scientific and operational contexts over complex terrains. Full article

To address the limitations of conventional single-track rail systems in challenging hilly and mountainous terrains, which are ill-suited for transporting heavy agricultural machinery, there is a critical need to develop a specialized the double-track rail transportation system optimized for orchard equipment. Recognizing this requirement, our research team designed and implemented a double-track rail transportation system. In this innovative system, the rail functions as the pivotal component, with its structural properties significantly impacting the machine’s overall stability and operational performance. In this study, resistance strain gauges were employed to analyze the stress–strain distribution of the track under a full load of 750 kg, a critical factor in the system’s design. To further investigate the structural performance of the double-track rail, the impact hammer method was utilized in conjunction with triaxial acceleration sensors to conduct experimental modal analysis (EMA) under actual support conditions. By integrating the Eigensystem Realization Algorithm (ERA), the first 20 natural modes and their corresponding parameters were successfully identified with high precision. A comparative analysis between finite element simulation results and experimental measurements was performed, revealing the double-track rail’s inherent vibration characteristics under constrained modal conditions versus actual boundary constraints. These valuable findings serve as a theoretical foundation for the dynamic optimization of rail structures and the mitigation of resonance issues. The advancement of hilly and mountainous rail transportation systems holds significant promise for enhancing productivity and transportation efficiency in agricultural operations. Full article

This review examines water pressure regulation technologies in irrigation systems tailored for hilly and mountainous terrains. In such areas, effective water management is crucial due to the terrain’s complexity and variability, which can greatly affect water distribution and resource efficiency. This text analyzes various types of pressure-regulating devices, including direct-acting and pilot-operated regulators, delving into their working principles, performance characteristics, and practical advantages and disadvantages. This summary also addresses the current research trends in these technologies, focusing on design optimization and performance enhancements. By summarizing existing studies and highlighting areas for future research, this review aims to provide a solid foundation for technological advancements in agricultural irrigation systems suited to challenging landscapes. Full article

The scenario adaptability of agricultural machinery chassis in hilly and mountainous regions has become a key area of innovation in modern agricultural equipment development in China. Due to the fragmented nature of farmland, steep terrain (often exceeding 15°), complex topography, and limited suitability for mechanization, traditional agricultural machinery experiences significantly reduced operational efficiency—typically by 30% to 50%—along with poor mobility. These limitations impose serious constraints on grain yield stability and the advancement of agricultural modernization. Therefore, enhancing the scenario-adaptive performance of chassis systems (e.g., slope adaptability ≥ 25°, lateral tilt stability > 30°) is a major research priority for China’s agricultural equipment industry. This paper presents a systematic review of the global development status of agricultural machinery chassis tailored for hilly and mountainous environments. It focuses on three core subsystems—power systems, traveling systems, and leveling systems—and analyzes their technical characteristics, working principles, and scenario-specific adaptability. In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. By establishing these performance benchmarks and focusing on critical technical priorities—including terrain-adaptive mechanism upgrades, energy-drive coordination, and precision leveling—this study provides a clear roadmap for the development of modular and intelligent chassis systems specifically designed for China’s hilly and mountainous regions, thereby addressing current bottlenecks in agricultural mechanization. Full article

Quinoa is renowned for its high nutritional value, which not only meets the nutritional needs of the human body but also makes it a suitable option for individuals with diabetes and celiac disease due to its low sugar and gluten-free characteristics. In China, the primary cultivation regions of quinoa are the Tibetan Plateau, the Yunnan–Guizhou Plateau, and Northwest China, which are predominantly characterized by hilly and mountainous terrain, resulting in the gradual development of mechanized harvesting processes. The efficacy of the mechanized harvesting process in these regions is suboptimal, exhibiting poor clearance and efficiency. In this paper, the design and MBD-EDEM coupling analysis of the quinoa combine harvester’s cleaning and screening mechanism is carried out to simulate the cleaning process of quinoa threshing materials. The results show that the vibrating screen can complete the forward sliding and dispersed throwing up of the materials and effectively avoid the accumulation of the threshing materials. The coupling results of the permeability of each material in the cleaning and screening mechanism, as well as the vibrating screen movement condition, indicate that when the herringbone screen opening degree is set in the range of 15° to 30°, the cleaning and screening device can achieve a high cleaning efficiency while maintaining a low impurity rate. Field trial data further confirm that within this opening range, the cleaning effect and efficiency both exhibit significant advantages. Full article

Understanding a catchment’s geomorphological and erosion processes is essential for sustainable land management and soil conservation. This study investigates the Xynias drained lake catchment in Central Greece using a twofold geospatial modelling approach that combines morphometric analysis with the Revised Universal Soil Loss Equation (RUSLE) to evaluate the area’s landscape evolution, surface drainage features, and soil erosion processes. The catchment exhibits a sixth-order drainage network with a dendritic and imperfect pattern, shaped by historical lacustrine conditions and the carbonate formations. The basin has an elongated shape with steep slopes, high total relief, and a mean hypsometric integral value of 26.3%, indicating the area is at an advanced stage of geomorphic maturity. The drainage density and frequency are medium to high, reflecting the influence of the catchment’s relatively flat terrain and carbonate formations. RUSLE simulations also revealed mean annual soil loss to be 1.16 t ha⁻¹ y⁻¹ from 2002 to 2022, along with increased erosion susceptibility in hilly and mountainous areas dominated by natural vegetation. In comparison to these areas, agricultural regions displayed less erosion risk. These findings demonstrate the effectiveness of combining GIS with remote sensing for detecting erosion-prone areas, informing conservation initiatives. Along with the previously stated results, more substantial conservation efforts and active land management are required to meet the Sustainable Development Goals (SDGs) while considering the monitored land use changes and climate parameters for future catchment management. Full article

In mountainous citrus orchards, the application of conventional ground sprayers for the control of citrus red mite (Panonychus citri) is often constrained by complex terrain and low operational efficiency. The Unmanned Aerial Spraying System (UASS), due to its low-altitude, low-volume, and high-maneuverability characteristics, has emerged as a promising alternative for pest management in such challenging environments. To evaluate the spray performance and field efficacy of different UASS types in controlling P. citri, five representative UASS models (JX25, DP, T1000, E-A2021, and T20), four mainstream pesticide formulations, and four novel tank-mix adjuvants were systematically assessed in a field experiment conducted in a typical hilly citrus orchard. The results showed that T20 delivered the best overall spray deposition, with upper canopy coverage reaching 10.63%, a deposition of 3.01 μg/cm², and the highest pesticide utilization (43.2%). E-A2021, equipped with a centrifugal nozzle, produced the finest droplets and highest droplet density (120.3–151.4 deposits/cm²), but its deposition and coverage were lowest due to drift. Nonetheless, it exhibited superior penetration (dIPR 72.3%, dDPR 73.5%), facilitating internal canopy coverage. T1000, operating at higher flight parameters, had the weakest deposition. Formulation type had a limited impact, with microemulsions (MEs) outperforming emulsifiable concentrates (ECs) and suspension concentrates (SCs). All adjuvants improved spray metrics, especially Yimanchu and Silwet, which enhanced pesticide utilization to 46.8% and 46.4% for E-A2021 and DP, respectively. Adjuvant use increased utilization by 4.6–11.9%, but also raised ground losses by 1.5–4.2%, except for Yimanchu, which reduced ground loss by 2.3%. In terms of control effect, the rapid efficacy (1–7 days after application, DAA) of UASS spraying was slightly lower than that of ground sprayers—electric spray gun (ESG), while its residual efficacy (14–25 DAA) was slightly higher. The addition of adjuvants improved both rapid and residual efficacy, making it comparable to or even better than ESG. E-A2021 with 5% abamectin·etoxazole ME (5A·E) and Yimanchu achieved 97.4% efficacy at 25 DAA. Among UASSs, T20 showed the rapid control, while E-A2021 outperformed JX25 and T1000 due to finer droplets effectively targeting P. citri. In residual control (14–25 DAA), JX25 with 45% bifenazate·etoxazole SC (45B·E) was most effective, followed by T20. 5A·E and 45B·E showed better residual efficacy than abamectin-based formulations, which declined more rapidly. Adjuvants significantly extended control duration, with Yimanchu performing best. This study demonstrates that with optimized spraying parameters, nozzle types, and adjuvants, UASSs can match or surpass ground spraying in P. citri control in hilly citrus orchards, providing valuable guidance for precision pesticide application in complex terrain. Full article

The operation of electric rice reaper binders in hilly and mountainous areas currently faces the challenges of poor conveying efficiency and high harvest losses caused by the large dispersion of rice stem posture angles. In this study, we propose a multiparameter collaborative optimization method for improving header structure in an effort to address these challenges. First, key parameters influencing lifting performance and their operational ranges were determined based on a theoretical analysis of the stem-lifting mechanism’s kinematic characteristics. A dynamic model simulating the header’s lifting process was developed by using the ADAMS multibody dynamics platform. Subsequently, we designed a quadratic regression orthogonal rotation combination experiment with three factors, i.e., the stem-lifting speed ratio coefficient, the cutter installation position, and the header tilt angle, using the stem-lifting angle as the evaluation metric. The variance in the experimental data was analyzed with Design-Expert 13.0, and response surface methodology (RSM) was applied to elucidate the parameter interaction effects. The optimal parameter combination was identified as a speed ratio coefficient of 2.14, a cutter installation position of 258.79 mm, and a header tilt angle of 62.63°, yielding a theoretical stem-lifting angle of 2.36°. Field validation tests demonstrated an actual stem-lifting angle of 2.44° (relative error: 3.39%) and a header loss rate of 0.59%, representing a 49.6% reduction compared with the pre-optimized design. These results confirm that the optimized header satisfies operational requirements for hilly terrain rice harvesting, providing both theoretical guidance and technical advancements for the design of low-loss harvesting machinery. Full article

The terrain in hilly and mountainous areas is complex, and the level of agricultural mechanization is low. This article systematically reviews the research progress of key technologies for agricultural machinery power chassis in hilly and mountainous areas, and conducts an analysis of five aspects: the power system, walking system, steering system, leveling system, and automatic navigation and path tracking control system. In this manuscript, (1) in terms of the power system, the technical characteristics and application scenarios of mechanical, hydraulic, and electric drive systems were compared. (2) In terms of the walking system, the performance differences between wheeled, crawler, legged, and composite walking devices and the application of suspension systems in agricultural machinery chassis were discussed. (3) In terms of the steering system, the steering characteristics of wheeled chassis and crawler chassis were analyzed, respectively. (4) In terms of the leveling system, the research progress on hydraulic and electric leveling mechanisms, as well as intelligent leveling control algorithms, was summarized. (5) The technology of automatic navigation and path tracking for agricultural machinery chassis was discussed, focusing on multi-sensor fusion and advanced control algorithms. In the future, agricultural machinery chassis will develop towards the directions of intelligence, automation, greening, being lightweight, and being multi-functionality. Full article

Single-track electric agricultural chassis plays a vital role in autonomous navigation and driving operations in hilly and mountainous regions, where its path tracking performance directly affects the operational accuracy and stability. However, in complex farmland environments, traditional methods often suffer from frequent turning and large tracking errors due to variable path curvature, uneven terrain, and track slippage. To address these issues, this paper proposes a path tracking algorithm combining a segmented preview model with variable universe fuzzy control, enabling dynamic adjustment of the preview distance for better curvature adaptation. Additionally, a heading deviation prediction model based on Support Vector Regression (SVR) optimized by Particle Swarm Optimization (PSO) is introduced, and a steering angle compensation controller is designed to improve the turning accuracy. Simulation and field experiments show that, compared with fixed preview distance and fixed-universe fuzzy control methods, the proposed algorithm reduces the average number of turns per control cycle by 30.19% and 18.23% and decreases the average lateral error by 34.29% and 46.96%, respectively. These results confirm that the proposed method significantly enhances path tracking stability and accuracy in complex terrains, providing an effective solution for autonomous navigation of agricultural machinery. Full article

Benggangs, a type of soil erosion widely distributed in the hilly and mountainous regions of South China, pose significant challenges to land management and ecological conservation. Accurate identification and assessment of their location and scale are essential for effective Benggang control. With advancements in technology, deep learning has emerged as a critical tool for Benggang classification. However, selecting suitable feature extraction and fusion methods for multi-source image data remains a significant challenge. This study proposes a Benggang classification method based on multiscale features and a two-stream fusion network (MS-TSFN). Key features of targeted Benggang areas, such as slope, aspect, curvature, hill shade, and edge, were extracted from Digital Orthophotography Map (DOM) and Digital Surface Model (DSM) data collected by drones. The two-stream fusion network, with ResNeSt as the backbone, extracted multiscale features from multi-source images and an attention-based feature fusion block was developed to explore complementary associations among features and achieve deep fusion of information across data types. A decision fusion block was employed for global prediction to classify areas as Benggang or non-Benggang. Experimental comparisons of different data inputs and network models revealed that the proposed method outperformed current state-of-the-art approaches in extracting spatial features and textures of Benggangs. The best results were obtained using a combination of DOM data, Canny edge detection, and DSM features in multi-source images. Specifically, the proposed model achieved an accuracy of 92.76%, a precision of 85.00%, a recall of 77.27%, and an F1-score of 0.8059, demonstrating its adaptability and high identification accuracy under complex terrain conditions. Full article