Due to the significant lateral undulation of sloped farmland, existing strip tillage machinery exhibits poor lateral profiling capabilities, severely affecting the effectiveness of cross-slope strip tillage operations. Based on the straw distribution and soil characteristics of sloped farmland in Northeast-China, this study conducted soil angle of repose tests and basic inclined plane experiments using a 2D LiDAR to determine the contact parameters between straw and soil components. A soil-straw composite model is established under different slopes. Using MBD-DEM coupled simulations, the performance of a straw strip clearing device (SSCD) was analysed under varying front tilt angles (FTAs), side tilt angles (STAs), working speeds (WSs), and working depths (WDs). The optimal operating parameters for the SSCD were determined to be 30 degrees, 20 degrees, 3 ms-1, and 150 mm, respectively. By analysing the trajectories of straw of four different lengths on the sowing strip above and the sowing strip below under different slopes, it was concluded that heavier straw was more affected by slope than lighter straw. Field test results indicated that at a 0 degrees slope, the straw clearing rate (SCR) was 98.1 % for the sowing-strip below and 98.4 % for the sowing-strip above, with a difference of 0.3 %. At a 6 degrees slope, the SCR was 93.3 % for the sowing-strip below and 97.8 % for the sowing-strip above, with a difference of 4.5 %. The discrepancies between simulation and field results were not significant. The designed device meets the agronomic requirements for cross-slope tillage on sloped farmland.

To enhance the operational stability and adaptability of soil-covering and compaction devices during no-till seeding on sloped farmland, this study developed a DEM-MBD coupled simulation model suited for conditions involving real-time slope variation and applied it to the design and analysis of a slope-adaptive covering-compacting device (SACCD). By coupling multi-body dynamics with the discrete element method, the model simulated the motion behavior and soil interaction process of the SACCD under different slope change rates, revealing its asynchronous response characteristics and profiling compaction mechanisms during dynamic slope transitions. Field experiments further verified the device's performance and the accuracy of the simulation. At the Lishu test site, the SACCD achieved a coefficient of variation of soil compaction of 20.4% under an average surface slope variation rate of 0.087 rad/s. At the Keshan test site, the coefficient of variation of soil compaction was 18.9%, with an almost constant slope. The differences between simulation and field results for the coefficient of variation of soil compaction were 8.32% (Lishu) and 1.02% (Keshan), confirming the reliability of the model and the rationality of the SACCD structural design. Overall, the simulation and field results demonstrate that the SACCD can maintain effective profiling posture and compaction performance under dynamic slope variation, providing a feasible approach and theoretical basis for the design and performance prediction of soil-covering and compaction devices for complex sloped farmland.

The complex anisotropy and rhizosphere consolidation of maize stubble severely restrict seeding quality in conservation tillage. Current Discrete Element Method (DEM) models, however, are often constrained by structural homogenization and the lack of root-soil adhesion, failing to reproduce authentic field interactions. This limitation creates a critical gap in bridging macroscopic power predictions with microscopic breakage mechanisms. Accordingly, this study introduces the Anisotropic Assembly and Rhizosphere Micro-Particle Filling (AA-RF) strategy. The AA module reconstructs the full-element stubble using a dual-medium alternating arrangement of homogeneous pith and double-sphere strip-like rind units, integrated with four layers of main roots. A step-by-step collaborative calibration process yielded a vertical cutting force relative error of only 0.49%. Furthermore, addressing both interface voids and adhesion deficiency, the RF module secondarily fills the inverted conical root system with high-adhesion soil micro-particles. This dual-action approach eliminates non-physical voids while successfully simulating the rhizosheath consolidation effect formed by secondary roots and exudates. Based on field benchmarks, comparative analysis established the effectiveness of the filling strategy in reproducing authentic root-soil interactions, followed by the calibration of the optimal micro-particle radius. Subsequent back-analysis of simulation deviations revealed that rigid pith particles cannot mimic actual plastic collapse. This fundamental mechanism explains the discrepancy between simulated (rigid toppling) and field (local fracture) failure modes, clarifying the model’s validity boundary. Final dynamic validation (2–6 km/h) confirmed high precision, with maximum relative errors of 2.90% for operation power and 7.37% for cleaning rate. Ultimately, the AA-RF strategy successfully bridges the simulation gap between macroscopic operation indicators and microscopic breakage mechanisms. By accurately reproducing complex root-soil consolidation, this dual-action methodology demonstrates significant advanced nature and broad universality, offering a robust DEM modeling paradigm for a wide range of deep-root crops.

Based on the principle of dilute-phase pneumatic conveying, this study proposes an innovative design for a pneumatic straw suction device for conservation tillage to reduce pressure drop and improve conveying efficiency. A coupled simulation method combining the Discrete Element Method (DEM) with Computational Fluid Dynamics (CFD) was employed, and its accuracy was validated through bench tests. The distribution and variation of airflow, straw particle motion, and the interaction of these parameters were investigated to achieve low pressure drop and high efficiency. By analysing the sources of pressure drop, it was found that the primary factors affecting airflow and particle conveying were the inner diameter of the air duct or the upper surface of the suction chamber, the bending diameter ratio of the elbow, and the fan rotational speed. The response surface optimisation revealed that the best low-loss, high-efficiency performance was achieved when the diameter of the air duct, the bending diameter ratio, and the fan rotational speed were set to 200 mm, 1.54, and 2900 rpm, respectively. Under these conditions, the pressure drop down, pressure drop up, and the percentage of straw mass were 12.58 Pa, 17.12 Pa, and 3.15 %, respectively. This study provides new insights into the interaction between straw particles and airflow in pneumatic conveying systems.

Accurate assessment of straw mulch mass is essential for evaluating conservation tillage practices. However, conventional field sampling methods often suffer from boundary-induced errors due to unclear separation of surface straw, which can introduce significant measurement deviations. To address this limitation, a stabilizing ring-assisted rotary shear system is proposed to enable locally confined cutting and controlled severing of boundary straw prior to mass measurement. To mechanistically capture this process, a soil-straw-tool coupled discrete element method (DEM) framework is established, allowing simultaneous representation of multi-material interactions that are not resolved in conventional single soil or straw simulations. The effects of stabilizing ring confinement, severing column rotational sequences, axial velocity, and axial acceleration are systematically analyzed during cutting. Simulation results show that ring-assisted confinement stabilizes blade-straw contact, enabling sustained shear accumulation and improved cutting continuity. Rotation reversal interrupts shear transfer despite higher mechanical loads, reducing effective cutting. Displacement-based analysis further indicates that cutting under constant axial velocity is capacity-limited and governed by spatial progression, whereas axial acceleration enhances early-stage shear engagement through rapid blade-straw interaction. These findings provide new insights into the mechanics of confined straw cutting, and reveals the effects of coordinated confinement, rotational motion, and axial kinematics on cutting efficiency. The proposed system and methodology offer a practical foundation not only for accurate measurement of straw mulch mass, but also for optimizing mechanized straw management systems.

Straw mulching is an important practice in conservation tillage. Although it improves soil quality and moisture retention, it also creates strong occlusion between crops and weeds, which reduces the recognition accuracy of vision systems and limits the stability of variable rate spraying. To address this challenge, this study proposes an integrated framework that combines occlusion level detection with structural completion for maize weed segmentation and spraying control. A MetaYOLOv8-Level network is developed by incorporating an occlusion level prediction head and light weight architectural optimisation. This design enables the joint estimation of target class and occlusion severity. For both lightly and heavily occluded targets, an Amodal Mask2Former network is applied to generate complete masks through dual branch decoding and multi scale deformable attention. A heuristic post processing module is used when further refinement is needed to improve boundary continuity. Based on these perception results, a stratified variable rate spraying strategy is introduced to adjust dosage according to the estimated area and occlusion level. Experiments on a residue covered dataset and field trials in maize fields in Liaoning Province verified the effectiveness of the proposed method. The detection model achieved an mAP@0.5 of 89.6 % and an occlusion level accuracy of 87.3 %. The completion module reached a Dice of 0.809 under heavy occlusion. With the heuristic post processing module, BF1 increased by 0.088 and HD95 was reduced by up to 2.0 pixels. In field spraying tests, the proposed strategy increased the overall dose compliance rate from 67.0% (T0) and 56.7% (T1) to 82.3%, reduced ODR and UDR to 5.0% and 12.7%, respectively, and improved compliance by 16.0–28.0 percentage points under L1 conditions and by 24.0–36.0 percentage points under L2 conditions compared with the baseline strategies.

The resolution of the ground wheel encoder is a critical parameter determining the speed measurement accuracy and seeding quality of electrically driven precision planters. However, the intrinsic influence mechanism of this parameter has not been systematically quantified. A corn electrically driven seeding control system compatible with multi-resolution encoders was developed. Comprehensive bench and field tests were conducted to evaluate the effects of six resolutions (50, 100, 300, 500, 1000, and 1500P & sdot;R- 1) on seeding quality indicators, including the qualified seeding index (QFI) and the coefficient of variation for seed spacing (CVd). Results revealed a nonlinear relationship between resolution and seeding quality. The resolutions of 50, 100, 300, and 1000P & sdot;R- 1 were identified as the "performance sweet spot," where QFI consistently exceeded 97%. Within this range, the 300P & sdot;R- 1 encoder demonstrated optimal robustness, achieving a steady-state speed measurement relative error (Delta e) of only 0.31% and maintaining the lowest field QFI fluctuation. Conversely, significant performance degradation was observed in two specific zones: the "critical zone" (500 P & sdot;R- 1), where specific frequency response characteristics amplified system noise, causing high speed-measurement deviation (sigma e= 0.774); and the "bottleneck zone" (1500P & sdot;R- 1), where hardware processing limits led to severe pulse loss and a systematic error of 8.12%. Contrary to the assumption that higher resolution yields better control, this study confirms that the 50-300P & sdot;R- 1 range offers the optimal balance of accuracy and stability for small and medium-sized planters using standard microcontrollers. This selection strategy effectively avoids instability and hardware-limited bottlenecks, facilitating the cost-effective adoption of precision seeding technology.

Accurate crop residue detection is essential for effective evaluation of its coverage rate. Varying light conditions in field environments, however, pose a significant challenge to achieving precise detection. To address this issue, this study developed a mobile closed system with artificial lighting (MCSAL) for in-field crop residue detection. The MCSAL consists of artificial lighting, a chamber movement control mechanism, and a line-controlled mobile platform, creating an entirely artificial light-controlled detection environment. The DeepLabv3+ network was employed as the crop residue detection model, which achieved a pixel accuracy of 91.40 %. Furthermore, a response surface experiment was designed to investigate the effects of artificial lighting parameters, including illumination intensity, illumination angle, and illumination height on detection accuracy, followed by parameter optimization. The optimal parameter settings were: 1163.00 lux illumination intensity, 49.65° illumination angle, and 415.14 mm illumination height. The experiments conducted with parameter combinations demonstrated the superior performance of the proposed model, with crop residue pixel accuracy that significantly improved from 91.40 % to 93.66 %. This approach preliminarily explored the detection performance of crop residue under artificial light conditions, highlighting the potential of the MCSAL for crop residue detection. It also offers an effective technological solution for accurate in-field crop residue detection.

In light of the growing conflicts between human activities and land use, enhancing the precision of seeding control throughout the entire maize seeding process is crucial for ensuring seeding quality and increasing yield per unit area. However, current research on maize seeding control methods has predominantly focused on the uniform speed seeding stage. Little attention has been paid to the acceleration stage, where speed variations are more complex and impose higher requirements for speed measurement and real-time control. To address this issue, this paper develops a maize seeding control system based on the Tracking Differentiator Filter-Optimal Tracking Control (TDF-OTC) method, aiming to improve the seeding quality during the acceleration stage from both input and output perspectives of the control system. An electric-driven seeding system was built on a pneumatic precision high-speed maize planter to provide the hardware platform for implementing the TDF-OTC method. A nonlinear tracking differentiator (NLTD) based on TDF was designed to address the filtering problem of oscillatory speed measurement signals, leveraging its ability to balance tracking speed and noise reduction. This ensures accurate forward speed input for the control system. Additionally, a linear quadratic tracker (LQT) based on OTC was designed to minimize error performance metrics and compel the system's actual output to track the target output trajectory. This resolved the rapid tracking of the drastically changing target rotational speed of seed metering drive motor, ensuring accurate motor speed output for the control system. Considering the real-world conditions of accelerated seeding operations, the parameters of NLTD and LQT were determined using MATLAB Simulink to ensure optimal performance. A series of tests was conducted to evaluate the performance of the proposed method. The TDF test results demonstrated that the NLTD effectively filtered and reduced noise from oscillatory speed input signals. The accelerated response test results of OTC showed that the designed LQT outperformed PID controllers in acceleration tracking capability. Accelerated seeding test in the field, where the planter accelerated from a standstill to approximately 3.5-4.0 m/s, revealed that the TDF-OTC method achieved an average seeding qualification rate (ASQR) of 90.63% and an average coefficient of variation of seeding spacing (ACVSP) of 21.66%. Compared to the PID method, these results represented a year-on-year improvement of 12.28% in ASQR and a reduction of 14.99% in ACVSP, affirming the effectiveness of the proposed method in improving seeding quality during the acceleration stage. This study provides a valuable reference for advancements in precision seeding.

During contour no-tillage sowing, traditional no-tillage seeders face challenges due to large transverse surface undulations. To address this, a slope-adaptive covering-compacting device (SACCD) was developed. This study aimed to accurately predict the operational performance of SACCD. The Edinburgh Elasto-Plastic Adhesion (EEPA) model was calibrated using field data on soil compaction and bulk density from the black soil region of northeastern China. Plate compression tests and cone penetration tests were conducted to determine the optimal EEPA model parameters. The calibration errors for soil bulk density were 0.2 %, while the errors for soil compaction at depths of 2.5 cm and 5 cm were 1.8 % and 2.0 %, respectively. A DEM-MBD coupled simulation model was then established. It simulated the interaction between SACCD and soil particles under varying slope conditions after furrow opening. The study evaluated the effects of slope angles and the elastic coefficient of the adaptive spring on soil compaction. Optimal operating parameters for SACCD were identified. Field tests showed that SACCD significantly outperformed the longitudinal profiling covering-compacting device (LPCCD). It reduced the coefficient of variation (CV) of soil compaction by 44.9 %, improved the CV of sowing depth by 7.3 %, and increased the emergence rate by 11.6 %. These results highlight the SACCD's bidirectional profiling capability and its potential to enhance crop yields. In field tests, the soil compaction at a 5 cm depth differed by 5.2 % from simulation results, while the CV of soil compaction differed by 7.9 %.

Granulating surface straw and returning it to the field in conservation tillage can prevent straw blockage, effectively improve sowing quality, and enhance soil fertility. However, straw modelling methods must be updated for accuracy to guide the optimal engineering of mechanised strip applications. This study elucidates granulated straw's particle size and length distribution through mathematical statistical analysis. The differential in tangential and normal compression loads is ascertained via uniaxial compression, three-point bending, and shear examinations. The contact parameters amongst straw particles are calibrated using the cylinder lifting technique. A novel approach is introduced for constructing and calibrating an anisotropic bidirectional bonding model tailored explicitly for materials exhibiting significant discrepancies in tangential and normal load. Utilising the Box-Behnken test design, mathematical models correlating bonding parameters with tangential and normal loads are developed. The study further investigates the effects of variations in interaction parameters on the assessment of the load, culminating in the identification of an optimal set of bonding parameters. Simulation outcomes from uniaxial compression and three-point bending tests revealed deviations from actual target values by 5.9 % and 2.4 %, respectively, with consistent deformation patterns observed. During the validation phase of mechanised straw-breaking strip application, the average discrepancy of test outcomes is recorded at 8.6 %, affirmatively simulating the roller device's field mechanised straw-breaking strip application process. This research offers technical backing for the swift establishment of anisotropic material models and the optimisation design of key components of agricultural machinery.

When monitoring seed positions in soil using ultrasonic waves, the main challenge is obtaining acoustic wave characteristics at the seed locations. This study developed a three-dimensional ultrasonic model with the double media of seed–soil using the discrete element method to visualize signal variations and analyze propagation characteristics. The effects of the compression ratio (0/6/12%), excitation frequency (20/40/60 kHz), and amplitude (5/10/15 μm) on signal variation and attenuation were analyzed. The results show consistent trends: time/frequency domain signal intensity increased with a higher compression ratio and amplitude but decreased with frequency. Comparing ultrasonic signals at soil particles before and after the seed along the propagation path shows that the seed significantly absorbs and attenuates ultrasonic waves. Time domain intensity drops 93.99%, and first and residual wave frequency peaks decrease by 88.06% and 96.39%, respectively. Additionally, comparing ultrasonic propagation velocities in the double media of seed–soil and the single soil medium reveals that the velocity in the seed is significantly higher than that in the soil. At compression ratios of 0%, 6%, and 12%, the sound velocity in the seed is 990.47%, 562.72%, and 431.34% of that in the soil, respectively. These findings help distinguish seed presence and provide a basis for ultrasonic seed position monitoring after sowing.

Crop straw chopping and returning technology has gained global implementation to enhance soil structure and fertility, facilitating increased crop yield. Nevertheless, technological adoption faces challenges from inherent limitations in machinery performance, including poor chopping and returning quality and high energy consumption. Consequently, this review first presented a theoretical framework that described the mechanical properties of straw, its fracture dynamics, interactions with airflow, and motion characteristics during the chopping process. Then, based on the straw returning process, the chopping devices were classified into five types: the chopped blade, the chopping machine, the chopping device combined with a no-tillage or reduced-tillage seeder, the chopping and ditch-burying machine, the chopping and mixing machine, and the harvester-powered chopping device. Advancements in spreading devices were also summarized. Finally, six key directions for future research were proposed: developing an intelligent field straw distribution mapping system, engineering adaptive self-regulating mechanisms for chopping and returning equipment, elucidating the mechanics and kinematics of straw in the chopping and returning process, implementing real-time quality assessment systems for straw returning operations, pioneering high forward-speed (>8 km/h) straw returning machines, and establishing context-specific straw residue management frameworks. This review provided a reference and offered support for the global application of straw returning technology.

Rotary tillage is a common cultivation for mixing cultivated soils with various dopants, including liquid amendments. The mixing performance of rotary tillage should be understood quantitatively. This study aimed to further validate the added value of the discrete element method (DEM) for spray-location selection in rotary tillage with the application of liquid amendments. A normalized amendment mixing index (AMI) was defined to describe the mixing of liquid amendments with soils. The AMI was used to quantify the mixing situations of the horizontally sliced subspace (HSS) and the vertically sliced subspace (VSS). The effect of spray position on the AMI of the slices was statistically analyzed. A field experiment was conducted using a spray position configuration that yielded the highest AMI in the simulation. The experimental AMIs were captured by processing images of vertical soil profiles. Simulated results show that spray position significantly affects the AMI, and spraying in the front of the tillage obtained the highest AMI. The experimental average AMI of VSS had an error of 7.08 % related to the simulation. Statistical analysis showed no significant difference between the simulation and experimental results. These results indicate that the AMI can distinguish between soil spaces containing only impregnated components and those containing only unimpregnated components, and can quantitatively describe the mixing situation in experiments and simulations. DEM simulation can provide reliable insights on spraylocation selection to apply amendments with a rotary tiller. These are expected to support the DEM simulation of solid-liquid mixing to investigate the mixing situation.

While straw mulching has been recognized for mitigating compaction, the multifactorial effects of straw parameters (content, length, laying modes) under static versus dynamic loads remain poorly quantified. Straw mulching may alter the stress transfer in the soil when applying static or dynamic loads. This study systematically evaluated stress and energy dissipation mechanisms using laboratory simulations: a plate sinkage test and an adapted Proctor test. The results demonstrated that the straw content (0-20 Mg/hm(2)) dominantly governs dissipation efficiency, with maximum stress dissipation ratios of 45.6% (static load >200 kPa) and energy dissipation ratios of 38.64% (dynamic high-energy). Longer straw (0.20 m) and ordered laying modes enhanced stress dispersion only under low static loads, while dynamic loads exhibited weaker dissipation. The study reveals that the damping effect of straw is strongest under low stress static load, so it is necessary to reduce the compaction of agricultural machinery and optimize the allocation of straw, such as 15-20 Mg/hm(2), to alleviate compaction in clay loam soils. These findings can provide actionable insights for designing straw-based soil conservation strategies and improving compaction prediction models in mechanized agriculture.

Parameter calibration is a key component of the discrete element method (DEM). Limitations on the predictive accuracy of DEM parameters calibrated by in-situ simulation approaches exist but are always ignored by researchers. To determine a DEM parameter combination for accurately predicting the seeding depth in non-contact seeding, under a condition of varying vertical velocities, this study constructed a two-dimensional look-up table (LUT) of seeding depths with DEM parameters as inputs using the in-situ simulation. According to the experimental results of seeding depths in five soil bins with different water content, multiple parameter combinations for each soil bin were found in the LUT with their prediction accuracies higher than 95 % under a fixed seed vertical velocity. Although the vertical velocity was different from it in the calibration, the parameter combinations for each soil bin were expected to have at least one that could accurately predict seeding depth with the same parameter combination. Thus, the experimental results of seeding depth at varying vertical velocities for each soil bin and their simulated results were compared. The results demonstrated strong simulation-experiment correlations (R-2 > 0.88) for parameter combinations in each soil bin under varying vertical velocities, though the correlation weakened with increasing velocity. Optimal parameter combinations were uniquely identified per soil bin through correlation maximization. The validated DEM parameters showed prediction errors of 2.42-21.23 % related to vertical velocities. This research provides foundational insights for developing real-time pressure adjustment systems in non-contact wheat seeding using spatial soil property databases.

Mechanical chopping and returning maize stover to the field has been widely promoted in China in recent years. It is of great significance to precisely predict the fundamental parameters and quality during processing. However, modern equipment has been restricted to the unreasonable simplification and low computational efficiency of numerical models for maize stover chopping. In this study, a series of experiments were first conducted to obtain the physical properties of maize stover, including the average stover density and moisture contents. Three-point bending, tensile, and shear tests were then carried out to measure the static and dynamic friction coefficients and the restitution coefficients during collision. The load-displacement correlations were obtained for the maize stover with three moisture contents after three-point bending tests. The results indicated that the stover shared the higher intensity, as the increase of the moisture content. The tensile and shear tests show that the tensile strength of maize stover with a moisture content of 60% ± 5% was measured as 19.92 MPa, and the shear strength was measured as 2.45 MPa. In addition, the maize stover was simplified into the breakable flexible fiber model. Specifically, the multi-segment sphero-cylinder elements were connected by node spheres using the discrete element. The node spheres were utilized to control the twisting, bending, stretching, and compression of the fibers, as well as the transmission of forces and torques. The motion of each node sphere was calculated with Newton’s second law, indicating the realistic simulation of the stover’s physical interactions. The tensile or shear stress fracture criteria were used with Rocky DEM software. The fracture occurred when the normal or tangential stress at the node spheres exceeded the strength limits. Moreover, the steepest ascent and Box-Behnken design were employed to calibrate four model parameters during simulation: elastic ratio, plastic ratio, bending angle limit, and failure ratio. The calibration results show that the optimal rotational speed of the chopping blade shaft was determined to be 2 088.4 r/min, the optimal forward speed of the machine was 3.3 km/h, the optimal sliding cutting angle of the chopping blade was 32.3°, and the ideal arrangement of the blades was a spiral configuration. Therefore, the chopping pass rate was 93.39% under the optimal parameters. Finally, the breakable flexible fiber model was applied to perform the large-scale simulations in a real maize field. A numerical model of a maize field was established within a 2 m × 10 m domain, consisting of upright stubble and stover on the surface. A global simulation of stover chopping and returning to the field was carried out to compare with the field experiments. The chopping pass rate was 92.58% from the field experiment, with a deviation of 0.87% (less than 2%), compared with the simulation. The field test validated the feasibility of the improved model and the accuracy of the numerical model. In conclusion, the breakable flexible fiber model shared the reasonable calibration suitable for the numerical simulations of stover chopping. The finding can also provide a sound basis to optimize the structure and working parameters of key components in stover chopping and returning machinery.

Complex field conditions in conservation tillage significantly enhance the vibration of no-tillage planters, which is even more intense at high velocity, limiting the development and promotion of no-tillage seeding of high-speed precision technology. At present, it is difficult to understand the vibration characteristics of no-tillage planters, and how to reduce the influence of vibration on furrowing quality is still a critical problem. In this study, a depthlimiting vibration model of the no-tillage seeding unit (NTSU) was established based on the nonlinear continuous contact force model and dynamic analysis. The cone index test was used to calibrate DEM parameters for modeling the simulated soil, which was used to study the effect of soil compaction on the vibration of no-tillage unit. The multibody dynamics (MBD) and discrete element method (DEM) coupled simulation technology of coupled furrowing operation was proposed as the test vibration analysis method. The effects of the working velocity, the spring stiffness coefficient (SSC), and the cone index on the vibration characteristics of the NTSU were studied through orthogonal tests and analysis. The simulation and field test results show that the working velocity is the primary influence factor of the vibration of the no-tillage planter, but it is also affected by the downforce and soil compactness. The maximum amplitude increased as the working velocity increased, but the main frequencies of the vibration are concentrated in a low frequency band from 2 to 10 Hz. Reasonable working velocity and SSC (downforce) settings can effectively reduce the vibration of the NTSU and improve the quality of seeding. To sum up, this paper proposed a new method that can effectively and precisely simulate the furrowing operation, and study the influence of NTSU structure on its vibration. It would provide a theoretical basis for the optimization design of the vibration damping system.