2026年第4期共收录41篇

1. Visual Place Recognition for Localization of Mobile Robots in Greenhouse

Accession number: 20260620043654

Title of translation: 面向温室移动机器人视觉定位场景识别方法

Authors: Zhou, Yuncheng (1); Yu, Meiling (1); Wu, Bohang (1); Zhang, Funing (1)

Author affiliation: (1) College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang; 110161, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 151-161

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the challenges of greenhouse mobile robot localization and scene recognition in highly dynamic environments with visually similar scenes, a novel scene recognition model was proposed based on local feature selection and aggregation. The model employed a pre-trained vision Transformer (DIN0v2) as its backbone network to extract local image features and introduced a learnable query-based feature selection and aggregation strategy to generate discriminative global descriptors. By leveraging cross-attention mechanisms, the model selectively aggregated the most informative local features into compact global representations. Furthermore, a hybrid loss function combining contrastive learning and triplet learning was applied to optimize the recognition model. A comprehensive greenhouse scene dataset containing 2 100 scenes and 25 000 images was constructed, covering multiple challenging factors such as illumination variations, viewpoint changes, distance scaling, and temporal crop growth. Experimental results demonstrated that the proposed model achieved Top — 1 recall rates (R @ 1) of 88.79%, 96.49% (R@5), and 97.96% (R@ 10) on the collected dataset, outperforming state-of-the-art scene recognition benchmarks, including NetVLAD, GeM, CosPlace, EigenPlaces, MixVPR, and SALAD by 23. 70, 19. 24, 10. 64, 3. 30, 3. 90, and 0. 44 percentage points in R@ 1, respectively. The model exhibited strong robustness under varying illumination conditions (R @ 1 fluctuation © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 38

Main heading: Greenhouses

Controlled terms: Agricultural robots  -  Computer vision  -  Contrastive Learning  -  Crops  -  Extraction  -  Feature Selection  -  Robot applications

Uncontrolled terms: Crop growth  -  Feature aggregation  -  Localization of mobile robots  -  Percentage points  -  Place recognition  -  Recognition models  -  Scalings  -  Scene recognition  -  Visual localization  -  Visual place recognition

Classification code: 731.5 Robotics  -  731.6 Robot Applications  -  802.3 Chemical Operations  -  821.2 Agricultural Machinery and Equipment  -  821.5 Agricultural Products  -  821.7 Farm Buildings and Other Structures  -  1101.2 Machine Learning  -  1106.8 Computer Vision

Numerical data indexing: Age 1.37E-02yr, Percentage 1.20E+01%, Percentage 1.40E+01%, Percentage 6.394E+01%, Percentage 8.588E+01%, Percentage 8.879E+01%, Percentage 9.649E+01%, Percentage 9.796E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.015

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

2. Design and Experiment of Internal Cob-splitting Pre-threshing Device for Maize Ears

Accession number: 20260620043363

Title of translation: 玉米果穗芯轴内部胀裂预脱粒装置设计与试验

Authors: Zhou, Deyi (1); Zhang, Chengyu (1); Liu, Daxin (1); Hou, Pengfei (1); Zhang, Guodong (1); Yu, Chunsheng (1)

Author affiliation: (1) College of Biological and Agricultural Engineering, Jilin University, Changchun; 130022, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 234-245 and 256

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In conventional drum-type maize threshing, the tightly arranged kernels on the maize ear lead to a high inter-kernel support force during the initial stage of threshing, resulting in strong impacts from the threshing elements and severe kernel damage. To address this issue, a pre-threshing principle for maize ears was proposed. This approach involved pretreating the ear before threshing by inducing internal splitting of the cob from the inside out into fragments, thereby disrupting the original compact kernel arrangement, loosening the kernels, and significantly reducing the inter-kernel support force. Based on this principle, a novel internal cob-splitting pre-threshing device for maize ears was developed. The device consisted primarily of an actuating cylinder, a prismatic splitting wedge, and an ear-holding fixture. Through analysis of the ear-splitting process, key structural parameters were identified, including the number of prism edges, operating air pressure, and fixture spacing. Single-factor experiments and Box -Behnken response surface tests were conducted to investigate the influence of these factors. The results showed that the significance of each factor affecting the proportion of small fragments and kernel breakage rate followed the descending order as follows; number of prism edges, fixture spacing and air pressure. The optimal combination of parameters was determined to be 8 prism edges, 2 cm fixture spacing, and 0.55 MPa air pressure. Under this configuration, five validation tests were conducted, yielding an average small fragment proportion of 74. 38% and a kernel breakage rate of 1. 07%, closely aligning with the predicted values. The results confirmed that the device can effectively split the maize ear into fragments with a high proportion of small cob pieces, while maintaining low kernel damage and significantly reducing the inter-kernel support force. Comparative threshing tests were carried out between a pre-threshing unit with a reciprocating flexible threshing unit and a 5TY — 45 — 150 thresher, and a 5TY —45 — 150 thresher fed directly with the whole cob. The results showed that the threshing method of “pre-threshing + 5TY —45 — 150 thresher” and the threshing method of “pre-threshing + reciprocating flexible threshing device” were comparable to the threshing method of feeding the whole cob directly into the 5TY — 45 — 150 thresher. The seed breakage rate of the threshing method was reduced by 2. 73 percentage points and 2. 97 percentage points, respectively. The reductions were as high as 55. 94% and 60. 86%, respectively. It proved that the pre-threshing device can significantly improve the operation quality of the whole threshing process. The research result can provide an approach and technical support for improving the quality of mechanized maize threshing. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Prisms

Controlled terms: Atmospheric pressure  -  Cylinders (shapes)  -  Fixtures (tooling)  -  Grain (agricultural product)

Uncontrolled terms: Air-pressure  -  Inter-kernel support force  -  Internal splitting  -  Kernel loosening  -  Maize ears  -  Pre-threshing of maize ear  -  Prismatic splitting wedge  -  Splittings  -  Support forces

Classification code: 408.1 Structural Members and Shapes  -  443.1 Atmospheric Properties  -  603.1 Machine Tool Accessories  -  741.3 Optical Devices and Systems  -  821.5 Agricultural Products

Numerical data indexing: Percentage 3.80E+01%, Percentage 7.00E+00%, Percentage 8.60E+01%, Percentage 9.40E+01%, Pressure 5.50E+05Pa, Size 2.00E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.023

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

3. Dynamic Weighing Method for Cattle Based on Time and Frequency Domains

Accession number: 20260620043698

Title of translation: 基于时域与频域的牛只动态称重方法

Authors: Zhang, Yong (1, 2); Zhou, Yu (1, 2); Su, Lide (1, 2); Zhang, Shun (3); Zhang, Longfei (1, 2); Shen, Yakai (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot; 010018, China; (2) Full Mechanization Research Base of Dairy Farming Engineering and Equipment, Ministry of Agriculture and Rural Affairs, Hohhot; 010018, China; (3) Modern Agriculture and Animal Husbandry Development Center, Inner Mongolia Autonomous Region, Bayannur, Bayannur; 015001, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 327-338 and 354

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In the field of precision breeding of cattle, weight is a key indicator for measuring their health and production performance. Traditional weighing methods are not only inefficient but also costly, while existing dynamic weighing algorithms are limited by insufficient robustness and stability. In response to this issue, the hidden information and behavioral information of cattle dynamic weighing signals were quantitatively analyzed, and existing dynamic weighing algorithms were improved by proposing a cattle dynamic weighing algorithm based on classification of time-frequency domain motion state and compensation for error prediction. Firstly, preliminary weight prediction values were obtained through modal decomposition algorithm, and the reference error with static weighing parameters was calculated. Secondly, weights of the window function were optimized to establish an adaptive window function, obtain reliable signal time-frequency domain feature parameters, and explore their relationship with motion labels and corresponding reference errors in the state. Finally, a motion state classification model and two types of error compensation models were established, and the slime mold algorithm (SMA) was used to perform hyperparameter optimization on the latter. Based on this, a complete dynamic weighing model for cattle was established. The experimental results indicated that the dynamic weighing prediction model for cattle performed well. The accuracy of the motion classification model was 98. 4% . In low and high activity states, the root mean square error (RMSE) of the final weight prediction values were 4. 03 kg and 8. 96 kg, respectively, and the mean percentage error (MAPE) were 0. 53% and 0. 87%, respectively. This algorithm had good robustness and generalization ability, which can provide reference for intelligent weight monitoring in practical breeding scenarios, and it had certain significance for promoting the development of precision breeding. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Forecasting

Controlled terms: Dynamic loads  -  Dynamics  -  Error compensation  -  Frequency domain analysis  -  Mean square error  -  Modal analysis  -  Motion compensation  -  Motion estimation  -  Time domain analysis  -  Weighing

Uncontrolled terms: Cattles  -  Frequency domains  -  Function Optimization  -  Measurements of  -  Motion state  -  Motion state classification  -  State classification  -  Time domain  -  Time domain and frequency domain  -  Time frequency   -  Weight measurement of cattle  -  Window function optimization  -  Window functions

Classification code: 408 Structural Design  -  709 Electrical Engineering, Other Topics  -  731.1.1 Error Handling  -  942.1.7 Special Purpose Instruments  -  1106.3.1 Image Processing  -  1201 Mathematics  -  1201.4 Applied Mathematics  -  1201.5 Computational Mathematics  -  1201.6 Control Theory  -  1202 Statistical Methods  -  1202.2 Mathematical Statistics  -  1301.1.1 Mechanics  -  1301.7 Statistical and Nonlinear Physics

Numerical data indexing: Mass 3.00E+00kg, Mass 9.60E+01kg, Percentage 4.00E+00%, Percentage 5.30E+01%, Percentage 8.70E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.032

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

4. Design and Experiment of Small Roller Type Seed Potato Grading and Cutting Machine

Accession number: 20260620043696

Title of translation: 小型辊组式马铃薯种薯分级切块机设计与试验

Authors: Zhang, Wanzhi (1, 2); Huang, Binheng (1); Wang, Ruimin (3); Sun, Yulu (1); Wang, Xuyang (1); Liu, Shufeng (4)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian; 271018, China; (2) Shandong Engineering Research Center of Agricultural Equipment Intelligentization, Taian; 271018, China; (3) School of Information Science and Engineering, Shandong Agricultural University, Taian; 271018, China; (4) School of Mechanical and Electrical Engineering, Hainan University, Haikou; 570228, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 180-191

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of large machine and low cutting quality of potato seed potato cutting machine in China, a multi-functional small roller type potato seed potato grading and cutting machine was designed. The structural design of the whole machine and key components was carried out. Through theoretical analysis and numerical calculation, the main factors affecting the grading effect were determined to be the inclination angle of the roller group, the speed of the first row of roller group and the feeding amount. The main factors affecting the cutting effect were determined to be the vertical center distance of the clamping roller, the angle between the center line of the clamping roller and the horizontal direction and the speed of the clamping roller. Based on EDEM — RecurDyn coupling simulation and theoretical analysis, the range of rotation speed and feeding amount of a row of rollers was determined. The inclination angle, the rotation speed and feeding amount of rollers were taken as experimental factors, and the classification efficiency and classification accuracy were taken as evaluation indexes., Box — Behnken experimental design method was used to determine the optimal parameter combination of the feeding grading device. The inclination angle of the roller group was 10. 53°, the rotation speed of the first row of roller groups was 88. 7 r/min, and the feeding amount was 52. 22 kg/min. At this time, the grading accuracy was 92. 65%, and the grading efficiency was 52. 04 kg/min. The prototype test showed that under the optimal parameter combination, the grading accuracy was 91. 67%, the grading efficiency was 49.44 kg/min, the qualified rate of the cutting block was 95.75%, the cutting efficiency was 48. 24 kg/min, and the uniformity of the potato bloek was good, which met the agronomic requirements of the seed potato cutting block. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Efficiency

Controlled terms: Agricultural machinery  -  Clamping devices  -  Cutting  -  Cutting machines (mining)  -  Cutting tools  -  Feeding  -  Grading  -  Rollers (machine components)  -  Structural design

Uncontrolled terms: Coupling simulation  -  Cutting device  -  Feeding amount  -  Inclination angles  -  Potato  -  Potato grading  -  Prototype tests  -  Roller assembly  -  Rotation speed  -  Seed potato grading

Classification code: 408 Structural Design  -  502 Mines and Quarry Equipment and Operations  -  601.2 Machine Components  -  603.1 Machine Tool Accessories  -  604.1 Metal Cutting  -  605.2 Small Tools, Unpowered  -  691.2 Materials Handling Methods  -  821.2 Agricultural Machinery and Equipment  -  913.1 Production Engineering

Numerical data indexing: Angular velocity 1.169E-01rad/s, Mass flow rate 3.674E-01kg/s, Mass flow rate 4.008E-01kg/s, Mass flow rate 6.68E-02kg/s, Mass flow rate 8.25648E-01kg/s, Percentage 6.50E+01%, Percentage 6.70E+01%, Percentage 9.575E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.018

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

5. Online Detection Method of Shine Muscat Grape Brix Based on Visible Near Infrared Spectroscopy Technology

Accession number: 20260620043598

Title of translation: 基于可见-近红外光谱技术的阳光玫瑰糖度在线检测方法

Authors: Zang, Yu (1, 2); Zhang, Yizhi (2); Bian, Hongdi (2); Hao, Haoyuan (2); Li, Nan (1); Li, Jiangbo (2)

Author affiliation: (1) School of Mechatronlc Engineering and Automation, Shanghai University, Shanghai; 200444, China; (2) Intelligent Equipment Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing; 100097, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 119-127 and 150

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Rapid and non-destructive method for online determination of soluble solids content (SSC) in Shine Muscat grapes was developed by using visible — near infrared (Vis — NIR) spectroscopy. The influences of spectral acquisition speed, sampling mode, and preprocessing methods on model performance were systematically investigated, and model simplification was achieved while maintaining prediction accuracy. During spectral acquisition, each grape bunch was divided into three equal segments (front, middle, and rear), and the averaged spectra were used to represent the overall optical response of the whole bunch. Partial least squares regression (PLSR) and support vector regression (SVR) models were constructed to evaluate the effects of different preprocessing approaches. Among them, the combination of Savitzky — Golay smoothing and standard normal variate transformation (SG + SNV) yielded the best results by effectively correcting baseline drift and scattering noise, thereby enhancing spectral quality and model precision. Whole-bunch detection achieved superior performance compared with segmented detection, with SVR producing root mean square error of prediction of 0.49° Brix and correlation coefficient of 0. 91, and PLSR yielding root mean square error of prediction of 0. 45°Brix and correlation coefficient of 0. 94. As the acquisition speed was increased from 0. 15 m/s to 0. 6 m/s, the prediction accuracy was gradually declined. For wavelength selection, uninformative variable elimination (UVE) demonstrated the best performance, extracting 314 informative wavelengths from 980 while maintaining high accuracy (PLSR; root mean square error of prediction was 0.41° Brix, correlation coefficient was 0. 90) and reducing model complexity. Overall, the proposed Vis - NIR-based approach enabled accurate and stable online prediction of grape SSC at the whole-bunch level, offering a practical theoretical foundation for the commercial development of intelligent online sorting systems for bunch-type fruits. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 20

Main heading: Near infrared spectroscopy

Controlled terms: Correlation detectors  -  Error detection  -  Forecasting  -  Infrared devices  -  Mean square error  -  Nondestructive examination  -  Online systems  -  Screening  -  Support vector regression

Uncontrolled terms: Brix analyze  -  Correlation coefficient  -  Infrared: spectroscopy  -  Model specifications  -  Near Infrared  -  Near-infrared  -  On-line detection  -  Partial least square regression  -  Root-mean-square error of predictions  -  Shine muscat grape

Classification code: 215.2.1 Non-mechanical Properties Testing Equipment and Methods  -  731.1.1 Error Handling  -  741.3 Optical Devices and Systems  -  802.3 Chemical Operations  -  1101.2 Machine Learning  -  1103.4 Digital Computers and Systems  -  1202 Statistical Methods  -  1202.2 Mathematical Statistics  -  1301.1.3.1 Spectroscopy

Numerical data indexing: Velocity 1.50E+01m/s to 0.00E00m/s, Velocity 6.00E+00m/s

DOI: 10.6041/j.issn.1000-1298.2026.04.012

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

6. Design and Testing of Clamp-feed Type Picking Device for Marigold

Accession number: 20260620043279

Title of translation: 夹送式万寿菊采收装置设计与试验

Authors: Yu, Chennan (1, 2); Zhou, Xiongjun (1); Wang, Qingye (3); Chen, Zhiwei (4); Yang, Kaihao (1); Yao, Kun (1); Chen, Jianneng (1, 2)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Zhejiang Key Laboratory oj Intelligent Sensing and Robotics for Agriculture, Hangzhou; 310018, China; (3) Qixin Honor School, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (4) Institute of Tea Research, Shandong Academy of Agricultural Sciences, Jinan; 250100, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 203-212

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issues of low efficiency in manual harvesting and high damage rate in mechanical brushing harvesting of marigolds, an automated marigold harvesting platform with a clamp-feed type design was proposed. The structural design and testing of the harvesting end were carried out to meet the harvesting requirements. Through field tests of the handheld harvesting end mechanism, factors affecting the damage rate of marigolds were identified, including the center distance of the synchronous pulley, the rotation speed of the synchronous pulley, and the harvesting angle. A three-factor, three-level central composite design and response surface analysis were used to study the interaction effects of these factors on the harvesting success rate. A quadratic regression model was established with harvesting damage rate as the response variable, and the significance of each factor on the harvesting success rate was ranked. By optimizing the factors with the damage rate as the objective, the optimized parameters for the center distance of the synchronous pulley, the rotation speed of the synchronous pulley, and the harvesting angle were determined to be 56 mm, 200 r/min, and 30°, respectively, with a predicted damage rate of 6. 59% . Three sets of validation tests were conducted with the optimized parameters, and the results showed that the end harvesting device could effectively complete the marigold harvesting task, with damage rates of 8%, 4%, and 8%, respeetively. The relative error between the test values and predicted values was less than 4% . A marigold harvesting device with a mechanical arm module was designed based on the actual working environment, its design closely focused on the growth characteristics of marigold and the core requirements of precision and efficiency for harvesting operations. It can accurately and quickly move the end effector and locate the target marigold position to complete the picking action with stable support and drive. On this basis, a test platform was built, and harvesting tests were conducted. The success rate of the harvesting tests was 93. 01%, confirming the feasibility of the clamp-feed type marigold harvesting device. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 20

Main heading: Efficiency

Controlled terms: End effectors  -  Harvesting  -  Regression analysis  -  Structural design

Uncontrolled terms: Center distance  -  Clamp-feed type  -  Damage rate  -  Harvesting devices  -  Marigold  -  Mechanical brushing  -  Optimized parameter  -  Picking device  -  Rotation speed  -  Type designs

Classification code: 408 Structural Design  -  731.5 Robotics  -  821.4 Agricultural Methods  -  913.1 Production Engineering  -  1202.2 Mathematical Statistics

Numerical data indexing: Angular velocity 3.34E+00rad/s, Percentage 1.00E00%, Percentage 4.00E+00%, Percentage 5.90E+01%, Percentage 8.00E+00%, Size 5.60E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.020

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

7. Numerical Simulation and Experiment of Turbulent Flow Membrane Debris Separation Device

Accession number: 20260720051896

Title of translation: 扰流式碎后膜杂分离装置数值模拟与试验

Authors: Feng, Zhen (1, 2); Kan, Za (1, 3); Wu, Guide (4); Peng, Huijie (1, 2); Meng, Hewei (1, 3); Zhang, Bingcheng (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China; (3) Xinjiang Production and Construction Corps Key Laboratory oj Modern Agricultural Machinery, Shihezi; 832003, China; (4) Xingjiang Denong Technology Co., Ltd., Shuanghe; 833408, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 257-267

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to solve the problems of low impurity removal efficiency and high cleaning cost in the process of cleaning after machine harvesting of membrane impurities, a membrane impurity separation method was proposed, which was first turbulent diffusion and then air gravity separation, and a perturbative membrane impurity separation device was designed. Through the theoretical analysis of the process of residual membrane turbulent diffusion and membrane miscellaneous air separation, it was determined that the key factors affecting the separation performance were the inlet air velocity, turbulence angle, diffusion chamber outlet height and conveying speed. Based on the discrete element model of residual film, cotton straw and soil miscellaneous materials, the EDEM — Fluent coupling simulation was used to numerically simulate the separation process of membrane impurities, which revealed the movement law and distribution of membrane miscellaneous materials after crushing in the separation device, and provided a basis for the structural parameters and working parameters of the separation device. Experimental tests with the prototype device, using impurity removal rate and winnowing loss rate as evaluation indices, determined the influence of different factors on performance. Optimal parameters were found to be: a turbulence angle of 48°, inlet air velocity of 5. 8 m/s, and diffusion chamber outlet height of 178.5 mm, achieving an 80.26% impurity removal rate and a 12.35% film leakage rate. These results can meet subsequent resource utilization requirements and offer valuable guidance for advancing winnowing impurity removal technology in mulch film separation. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Air cleaners

Controlled terms: Agricultural machinery  -  Air  -  Cleaning  -  Computational fluid dynamics  -  Diffusion  -  Impurities  -  Membranes  -  Nafion membranes  -  Numerical models  -  Removal   -  Turbulence  -  Turbulent flow

Uncontrolled terms: Air density  -  Air density separation  -  Density separation  -  Impurity removal  -  Impurity separation  -  Inlet air  -  Post-fragment membrane impurity separation device  -  Separation devices  -  Turbulent breakup  -  Turbulent diffusion

Classification code: 205.1 Polymeric Materials  -  214 Materials Science  -  301 Fluids  -  301.1.1 Liquid Dynamics  -  301.1.2 Gas Dynamics  -  301.1.4 Computational Fluid Dynamics  -  301.2 Hydrodynamics  -  302 Thermodynamics and Heat Transfer  -  802.3 Chemical Operations  -  821.2 Agricultural Machinery and Equipment  -  1201.4 Applied Mathematics  -  1502.1.1.4.1 Air Pollution Control

Numerical data indexing: Percentage 1.235E+01%, Percentage 8.026E+01%, Size 1.785E-01m, Velocity 8.00E+00m/s

DOI: 10.6041/j.issn.1000-1298.2026.04.025

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

8. Automatic Prediction Method for Sow Estrus Based on Low-cost Electronic Ear Tags

Accession number: 20260720049730

Title of translation: 基于低成本电子耳标的母猪发情自动预测方法

Authors: Sang, Gaoli (1, 2); Yin, Yapeng (1, 2); Gao, Kaifu (1, 2); Wan, Liang (3); Yao, Xuefei (4); Luo, Chaofei (4)

Author affiliation: (1) School of Computer Science and Technology, School of Artificial Intelligence), Zhejiang Sci-tech University, Hangzhou; 310018, China; (2) College of Artificial Intelligence, Jiaxing University, Jiaxing; 314001, China; (3) School of Intelligence and Computing, Tianjin University, Tianjin; 300072, China; (4) Zhejiang Huateng Animal Husbandry Co., Ltd., Jiaxing; 314513, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 339-346

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Using ear temperature instead of body temperature to predict and analyze the estrus of sows. To address the issues of high cost and limited scalability in the automated detection of sow estrus, a prediction model (denoted as GA — LightGBM) was proposed based on the improved genetic algorithm (GA) optimizing the light gradient boosting machine (LightGBM). Compared with infrared cameras and infrared imaging equipment, low-cost and low-power electronic ear tags were used to collect real-time ear temperature data from sows, and an hourly average temperature resampling strategy was innovatively proposed. Comparative experiments showed that this strategy significantly reduced the risk of overfitting. To overcome the problems of slow convergence speed and falling into local optima in traditional genetic algorithms, a forced offspring iteration (FOI) mechanism was designed to improve the algorithm, enhancing the convergence efficiency while maintaining the global search capability. In experiments, a LightGBM model optimized by the particle swarm optimization (PSO) (denoted as PSO — LightGBM) was introduced for comparison. After verification using a dataset containing 311 sows provided by Zhejiang Huateng Animal Husbandry Co., Ltd., the improved GA-optimized LightGBM model (denoted as FOI -GA — LightGBM) achieved an accuracy of 83. 91% and an AUC of 0. 839 0 on the test set, significantly outperforming the GA — LightGBM and PSO — LightGBM models. At the same time, FOI — GA — LightGBM was also compared with random forest (RF) and support vector machine (SVM) in terms of performance. The overall performance of FOI — GA — LightGBM was superior to RF and SVM. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Particle swarm optimization (PSO)

Controlled terms: Agricultural machinery  -  Genetic algorithms  -  Support vector machines  -  Thermography (imaging)

Uncontrolled terms: Electronic ear tag  -  Forced offspring iteration  -  Gradient boosting  -  Improved genetic algorithm  -  Light gradient boosting machine  -  Light gradients  -  Machine modelling  -  Particle swarm  -  Sow estrus detection  -  Swarm optimization

Classification code: 746 Imaging Techniques  -  821.2 Agricultural Machinery and Equipment  -  1101.2 Machine Learning  -  1106 Computer Software, Data Handling and Applications  -  1201.7 Optimization Techniques

Numerical data indexing: Percentage 9.10E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.033

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

9. Soil Moisture Content Prediction Method Based on Underground Wireless Signal Propagation

Accession number: 20260720049695

Title of translation: 基于地下无线传播信号的土壤含水率预测方法

Authors: Xu, Xing (1, 2); Liu, Guojie (1, 2); Li, Bifang (1, 3); Duan, Jieli (1, 2); Yang, Zhou (1, 2); Fu, Han (1, 2); Jin, Mohui (1, 2)

Author affiliation: (1) Mechanization Research Laboratory, National Banana Industry Technology System, Guangzhou; 510642, China; (2) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (3) College of Electronic Engineering, College of Artificial Intelligence), South China Agricultural University, Guangzhou; 510642, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 347-354

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Timely and accurate acquisition of soil moisture information is essential for comprehensively understanding soil water content, improving water use efficiency, and conserving valuable water resources. At present, remote collection of soil moisture data typically requires both soil moisture sensors and wireless transmission modules. However, these approaches are limited to discrete point measurements and cannot achieve comprehensive regional assessment. Moreover, the high cost of soil moisture sensors restricts large-scale deployment. A low-cost method for predicting soil water content over an area was proposed, utilizing the working characteristics of underground wireless signal propagation which was strongly influenced by soil moisture, and its advantages in wireless communication. Based on LoRa technology and a fast machine learning approach with strong generalization capability, a LoRa-based underground wireless sensor network was designed and developed for underground environments to remotely collect data such as received signal strength indicator (RSSI), signal-to-noise ratio (SNR), and soil temperature. Using the collected data, a kernel extreme learning machine (KELM) model optimized by particle swarm optimization (PSO) was proposed to estimate soil water content, addressing the challenges of strong nonlinearity, poor fitting, and low convergence in large-scale data modeling. Experimental results showed that the proposed PSO-optimized KELM model achieved higher prediction accuracy than the extreme learning machine (ELM), support vector regression (SVR), and long short-term memory (LSTM) models. In the training dataset, the KELM model achieved a mean absolute error (MAE) of 0. 76% and a root mean square error (RMSE) of 1.02%, while in the testing dataset, the MAE and RMSE were 0. 72% and 1. 07%, respectively. The proposed method can achieve effective prediction and remote acquisition of soil moisture content without relying on the dense deployment of soil moisture sensors, providing a low-cost solution for large-area soil moisture detection. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Soil moisture

Controlled terms: Agricultural machinery  -  Costs  -  Data acquisition  -  Forecasting  -  Knowledge acquisition  -  Large datasets  -  Learning systems  -  Machine learning  -  Mean square error  -  Moisture determination   -  Moisture meters  -  Particle swarm optimization (PSO)  -  Prediction models  -  Signal to noise ratio  -  Soil surveys  -  Soil testing  -  Statistical tests  -  Water resources

Uncontrolled terms: %moisture  -  Learning machines  -  Machine modelling  -  Prediction methods  -  Prediction modelling  -  Soil moisture content  -  Soil moisture sensors  -  Soil water content  -  Wireless signal propagation  -  WUSN

Classification code: 405.3 Surveying  -  444 Water Resources  -  483.1 Soils and Soil Mechanics  -  716.1 Information Theory and Signal Processing  -  821.2 Agricultural Machinery and Equipment  -  911 Cost and Value Engineering; Industrial Economics  -  941.6 Moisture Measurements  -  942.1.8 Moisture Measuring Instruments  -  1101 Artificial Intelligence  -  1101.2 Machine Learning  -  1106 Computer Software, Data Handling and Applications  -  1106.2 Data Handling and Data Processing  -  1106.3 Digital Signal Processing  -  1201.7 Optimization Techniques  -  1202 Statistical Methods  -  1202.2 Mathematical Statistics  -  1502.1.1.4.3 Soil Pollution Control

Numerical data indexing: Percentage 1.02E+00%, Percentage 7.00E+00%, Percentage 7.20E+01%, Percentage 7.60E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.034

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

10. Optimization Design and Experiment of Seedling Picking Mechanism Based on Watt H

Accession number: 20260620043354

Title of translation: 基于 Watt-II 型的取苗机构优化设计与试验

Authors: Cui, Rongjiang (1); Jiang, Lei (2); Wang, Lei (2, 3); Fang, Ziehen (2); Yu, Gaohong (2, 3); Qiao, Jie (4)

Author affiliation: (1) Special Equipment Institute, Hangzhou Polytechnic University, Hangzhou; 310018, China; (2) Faculty of Machinery and Automation, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (3) Zhejiang Province Key Laboratory of Transplanting Equipment and Technology, Hangzhou; 310018, China; (4) Weichai New Energy Power Technology Co,, Ltd., Weifang; 261061, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 172-179

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem of easy wear of the slideway in the link-slide type seedling picking mechanism, a Watt — II six-bar seedling picking mechanism that met the trajectory requirements for automatic transplanting of vegetable plug seedlings was proposed. It adopted a fully hinged linkage structure to avoid slideway wear. Firstly, the trajectory, attitude and working requirements of the seedling picking mechanism in the three processes of seedling picking, seedling conveying and seedling releasing were analyzed, an open trajectory was designed where the forward operational path coincided with the return path. Furthermore, five key poses along this trajectory were identified and defined. Then the Watt — II six-bar mechanism was simplified into a double-rocker mechanism and a crank-rocker mechanism. The relative displacement matrix equation of the planar 2R open-chain mechanism was established, and the kinematic synthesis design equations were constructed according to the joint constraints. Through the homotopy algorithm, two sets of mechanism parameters meeting the design requirements were obtained to form the double-rocker mechanism. Combined with the quick-return ratio K, the crank-rocker mechanism was designed, and the two were combined to form the Watt — II six-bar mechanism. Finally, the structural design, virtual simulation and prototype test of the seedling picking mechanism were carried out. The results showed that the theoretical trajectory, simulation trajectory and the motion trajectory of the bench test were basically consistent, and the success rate of plug seedling picking was no less than 91. 4%, which met the design requirements of the automatic seedling picking mechanism for leafy vegetable plug seedlings. This verified the rationality of the design of the Watt — H six-bar seedling picking mechanism, which had a good application prospect. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Vegetables

Controlled terms: Connecting rods  -  Machine design  -  Seed  -  Slideways  -  Structural design  -  Trajectories  -  Wear of materials

Uncontrolled terms: Automatic transplanting  -  Bar mechanisms  -  Connecting rod mechanism  -  Crank-rocker mechanism  -  Double-rocker mechanisms  -  Homotopy algorithms  -  Plug seedling  -  Seedling picking mechanism  -  Vegetable plug seedling  -  Watt II six-bar

Classification code: 214 Materials Science  -  408 Structural Design  -  601 Mechanical Design  -  601.1 Mechanical Devices  -  601.2 Machine Components  -  603.1 Machine Tool Accessories  -  656 Space Flight and Research  -  821.5 Agricultural Products  -  904 Design

Numerical data indexing: Percentage 4.00E+00%

DOI: 10.6041/j.issn.1000-1298.2026.04.017

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

11. Design and Experiment of Moisture Regain Sensor for Seed Cotton in Cotton Pickers

Accession number: 20260620043308

Title of translation: 采棉机籽棉回潮率传感器设计与试验

Authors: Fang, Liang (1, 2); Liu, Kang (1, 2); Huang, Jie (1, 2); Chang, Jinqiang (1, 3); Shi, Yuwen (1, 2); Zeng, Zhaoquan (1, 4); Zhang, Ruoyu (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China; (3) Technology Innovation Center of Smart Farm Digital Equipment, Xinjiang Production and Construction Corps, Shihezi; 832003, China; (4) School of Energy and Materials, Shihezi University, Shihezi; 832003, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 62-71

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem that the online detection of moisture regain of seed cotton during cotton picking operations is significantly interfered by environmental temperature and contact pressure, a moisture regain sensor for seed cotton in cotton pickers was designed based on the resistive method, integrating temperature and pressure compensation mechanisms. By optimizing the resistance detection circuit to broaden the measurement range and combining temperature and pressure sensing units, a sensor hardware system capable of synchronously collecting environmental temperature, contact pressure, and seed cotton resistance was designed, and it was calibrated and performance tested. An experimental platform was built to analyze the influence of temperature, pressure, and moisture regain on the conductive characteristics of seed cotton, and a moisture regain prediction model incorporating multiparameter compensation was established. The results showed that the designed hardware circuit had an average absolute error of less than 0. 4t for temperature measurement, an average relative error of less than 0. 2% for pressure measurement, and an average relative error of less than 3% for resistance measurement. In the moisture regain prediction model, the BPNN algorithm performed best, with a coefficient of determination (R) of 0. 986 and a root mean square error (RMSE) of 0. 377% . To verify the reliability of the moisture regain sensor, indoor static tests and field harvesting tests were conducted. The indoor static test results indicated that the sensor’s detection range was from 4% to 15%, with an average absolute error of 0. 22% and an average relative error of 2. 32% . The field harvesting test results showed that the absolute error of the detection results was no greater than 0. 5%, and the relative error was no greater than 4. 32% . The tests demonstrated good accuracy and practicality, providing effective technical support for the online detection of moisture regain of seed cotton in cotton pickers. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Mean square error

Controlled terms: Cotton  -  Electric resistance measurement  -  Error detection  -  Moisture determination  -  Regain  -  Temperature measurement

Uncontrolled terms: %moisture  -  Average relative error  -  Compensation algorithm  -  Contact pressures  -  Cotton pickers  -  Environmental temperature  -  On-line detection  -  Resistance method  -  Seed cotton  -  Seed cotton moisture regain

Classification code: 213.3 Fiber Chemistry and Processing  -  731.1.1 Error Handling  -  821.5 Agricultural Products  -  941.3 Electric Variables Measurements  -  941.6 Moisture Measurements  -  941.8 Temperature Measurements  -  1202.2 Mathematical Statistics

Numerical data indexing: Percentage 2.00E+00%, Percentage 2.20E+01%, Percentage 3.00E+00%, Percentage 3.20E+01%, Percentage 3.77E+02%, Percentage 4.00E+00% to 1.50E+01%, Percentage 5.00E+00%

DOI: 10.6041/j.issn.1000-1298.2026.04.007

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

12. Estimation Method of Soil Respiration Rate in Summer Maize Farmland Based on UAV Remote Sensing

Accession number: 20260620043300

Title of translation: 基于无人机遥感的夏玉米农田土壤呼吸速率估算方法

Authors: Gui, Lihua (1); Zhang, Mengfei (1); Li, Pingyang (1); Wang, Shengpu (1); Fan, Wenze (1); Han, Wenting (1, 2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Research Institute of Water-saving Agriculture in Dry Area, Northwest A&F University, Shaanxi, Yangling; 712100, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 287-295 and 326

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurate and timely estimation of spatiotemporal dynamics of farmland soil respiration rate is crucial for revealing carbon emission patterns during agricultural production. Traditional methods can simulate soil respiration dynamics at small scales, but they remain insufficient in characterizing spatial heterogeneity at the farmland scale. To achieve accurate estimation of soil respiration at high spatial resolution, it was focused on summer maize in a typical region of central Inner Mongolia. The experiment included one control treatment (Trl; irrigation at 100% ET, where ET represents evapotranspiration) and three deficit irrigation treatments (Tr2, Tr3, Tr4) . Soil respiration rates were monitored at different growth stages by using the static chamber method, while vegetation indices and soil surface temperature (7\ iAV) were retrieved from UAV-based multispectral and thermal infrared data. The Tuiy, together with the simple pigment ratio index (SRPI), the green-blue normalized difference vegetation index (NDVI,,!,), and the normalized pigment chlorophyll index (NPCI), were incorporated into the Lloyd -Taylor model to develop an improved vegetation-heat index (VHI) model for soil respiration rate estimation. The performance of this model was further compared with that of a back propagation neural network (BPNN) model. The results showed that under Trl ~ Tr4 treatments, temperature of the soil surface (Tsf) was significantly correlated with seasonal soil respiration rate, with correlation coefficients of 0. 946, 0. 886, 0. 898 and 0. 766, respectively. Among the nine vegetation indices indicative of crop photosynthetic capacity, SRPI exhibited the strongest correlation with seasonal soil respiration rate. The VHI model based on SRPI and 7\ jAV achieved the best fitting performance (R = 0. 73), which was comparable to the BPNN model (R =0.81). Overall, it was demonstrated that integrating UAV multispectral and thermal infrared data with the VHI model enabled high-resolution characterization and mapping of soil respiration rate heterogeneity at the farmland scale, thereby improving estimation accuracy. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 36

Main heading: Unmanned aerial vehicles (UAV)

Controlled terms: Backpropagation  -  Crops  -  Farms  -  Grain (agricultural product)  -  Image resolution  -  Irrigation  -  Pigments  -  Soil surveys  -  Soil temperature  -  Soils   -  Vegetation mapping

Uncontrolled terms: Heat indices  -  Index models  -  Lloyd — taylor model  -  Soil respiration  -  Soil respiration rates  -  Summer maize  -  Taylor models  -  Thermal-infrared  -  UAV remote sensing  -  Vegetation index

Classification code: 405.3 Surveying  -  483.1 Soils and Soil Mechanics  -  652.1 Aircraft  -  804 Chemical Products  -  804.2 Inorganic Compounds  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.4 Agricultural Methods  -  821.5 Agricultural Products  -  1101.2 Machine Learning  -  1106.3.1 Image Processing

Numerical data indexing: Percentage 1.00E+02%

DOI: 10.6041/j.issn.1000-1298.2026.04.028

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

13. Design and Experiment of Needle-belt Type Electrostatic Separation Device for Residual Plastic Films in Straw Feed

Accession number: 20260620043316

Title of translation: 针带式秸秆饲料残膜静电分离装置设计与试验

Authors: Guo, Wensong (1, 2); Jiang, Haojie (1, 2); Chen, Baiyu (1, 2); Wang, Xufeng (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Tarim University, Alar; 843300, China; (2) Xinjiang Production and Construction Corps(XPCC) Key Laboratory of Utilization and Equipment of Special Agricultural and Forestry Products in Southern Xinjiang, Alar; 843300, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 268-278

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to tackle the issues of high labor intensity and low efficiency associated with manual removal of residual plastic film from straw feed in Xinjiang, a needle-belt type electrostatic separation device for residual plastic film in straw feed was designed. Based on the principle of electrostatic adsorption, the device consisted of core components, including a high-voltage electrostatic generator, electret discharge rod, and metal conveyor belt. Through theoretical analysis, the critical conditions for separating residual plastic film from straw feed were deduced, verifying the feasibility of applying the needle-belt type electrostatic separation technology to residual plastic film removal. Using COMSOL simulation software, the effects of geometric parameters and operating parameters of corona needles on electric field distribution and negative ion density were studied, and the optimal parameters were determined as follows; needle tip cone angle was 12°, needle length was 14 mm, and needle spacing was 20mm. Single-factor experiments showed that the electrode spacing (40 -60 mm), voltage (15 ~ 25 kV), conveyor belt speed (21 -28 m/min), and material feeding rate (8 - 12 kg/min) had significant impacts on the separation efficiency. A quadratic regression model was established by using the Box — Behnken experimental design, and the optimal parameter combination of the device was determined as follows; electrode spacing was 51.3 mm, voltage was 22.9 kV, belt speed was 24. 5 m/min, and feeding rate was 9.5 kg/min. Finally, the separation efficiency measured in the verification experiment was 91%, which was in good agreement with the predicted value of 92.6%, meeting the technical requirements for removing residual plastic film from straw feed. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Electrostatic separators

Controlled terms: Belt conveyors  -  Computer software  -  Cones  -  Design of experiments  -  Efficiency  -  Electric discharges  -  Electrodes  -  Electrostatic generators  -  Needles  -  Plastic films   -  Regression analysis

Uncontrolled terms: Conveyor belts  -  Electrode spacing  -  Electrostatic Separation  -  Feeding rate  -  Labour intensity  -  Plastic-film  -  Residual plastic film  -  Separation devices  -  Separation efficiency  -  Straw feed

Classification code: 101.2 Biomedical Equipment  -  207.1 Polymer Products  -  213.6 Textile Mills, Machinery and Equipment  -  692.1 Conveyors  -  701.1 Electricity: Basic Concepts and Phenomena  -  705.1 Electric Machinery  -  715 Electronic Equipment, General Purpose and Industrial  -  801.3.1 Electrochemistry  -  802.1 Chemical Plants and Equipment  -  901.3 Engineering Research  -  904 Design  -  913.1 Production Engineering  -  1106.9 Computer Software  -  1201.14 Geometry and Topology  -  1202.2 Mathematical Statistics

Numerical data indexing: Mass flow rate 1.336E-01kg/s to 2.004E-01kg/s, Mass flow rate 1.5865E-01kg/s, Percentage 9.10E+01%, Percentage 9.26E+01%, Size 1.40E-02m, Size 2.00E-02m, Size 2.10E+01m to 2.80E+01m, Size 4.00E-02m to 6.00E-02m, Size 5.00E+00m, Size 5.13E-02m, Voltage 1.50E+04V to 2.50E+04V, Voltage 2.29E+04V

DOI: 10.6041/j.issn.1000-1298.2026.04.026

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

14. Design and Experiment of Transplanter Electric Drive Double Group Seedling Cup Common Rail Type Separating Seedling System

Accession number: 20260620043283

Title of translation: 移栽机电驱双组苗筒共轨式分苗系统设计与试验

Authors: Han, Changjie (1, 2); Li, Desheng (1); Xu, Yang (1, 2); Chen, Meng (1); Shi, Zhai (1, 2); Yuan, Panpari (1, 2); Mao, Hanping (1, 3)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Xinjiang Intelligent Agricultural Machinery Equipment Engineering and Technology Research Center, Urumqi; 830052, China; (3) School of Agricultural Engineering, fiangsu University, Zhenjiang; 212013, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 162-171

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the seedling leakage issue caused by missing seedlings in fully automatic pepper tray seedling transplanters, the seedling separation process of the transplanter was analyzed and a dual-seedling cylinder independent drive system with empty-cell replenishment for seedling separation was proposed, aiming to minimize missed planting. An electric drive double group seedling cup common rail type separating seedling system was designed. The two sets of seedling cylinders operated on identical trajectories. While one set remained stationary to receive seedlings, the other set can continue performing seedling-dropping operations or execute empty-cell replenishment tasks, ensuring a continuous supply of seedlings to the planting device’s duckbill mechanism. An optical fiber identification sensor was selected for seedling absence detection, and a PLC-based automatic control system was established to acquire the sensor output signals in real time. Based on the determination of the empty-cell state derived from a binary threshold algorithm, the system triggered the actuator to initiate accelerated motion for empty-cell replenishment operations. With planting frequency, air supply pressure, and the status of the detection and compensation function (on/off) as experimental factors. The trial evaluated transplant failure rates and duckbill seedling reception rates of the planting device to identify optimal parameter combinations, followed by field validation. Results showed that under the combination of 120 plants per minute planting frequency and 0. 4 MPa air supply pressure with detection and compensation function was disabled, the average duckbill seedling reception rate was 86. 46% . When the detection and compensation function was activated, the rate was increased to 98.27%, demonstrating a significant enhancement in seedling reception efficiency. This research can provide valuable insights for the development of seedling separation devices for chili pepper tray seedlings. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Cylinders (shapes)

Controlled terms: Control systems  -  Electric drives  -  Fiber optic sensors  -  Germination  -  Optical fibers  -  Plants (botany)

Uncontrolled terms: Compensation functions  -  Detection functions  -  Double groups  -  Empty cup refill  -  Plantings  -  Plug seedling  -  Plug seedling detection  -  Seedling separation mechanism  -  Separation mechanism  -  Transplanter

Classification code: 103 Biology  -  214.1 Mechanical Properties of Materials  -  408.1 Structural Members and Shapes  -  601.3 Mechanisms  -  602.1 Mechanical Drives  -  705.1 Electric Machinery  -  731.1 Control Systems  -  741.1.2 Fiber Optics  -  821.4 Agricultural Methods  -  821.5 Agricultural Products

Numerical data indexing: Percentage 4.60E+01%, Percentage 9.827E+01%, Pressure 4.00E+06Pa

DOI: 10.6041/j.issn.1000-1298.2026.04.016

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

15. Design and Experiment of Dual-regulation Control System for No-tillage Seeding Units Based on Pressure Stabilization and Depth-limiting Vibration Reduction

Accession number: 20260620043292

Title of translation: 基于压力稳定与限深减振的双调控免耕播种单体控制系统设计与试验

Authors: He, Dong (1, 2); Wang, Chao (1, 2); Cao, Xinpeng (3); Wang, Qingjie (1, 2); Li, Hongwen (1, 2); Lu, Caiyun (1, 2); He, Jin (1, 2); Jia, Lin (1, 2); Wu, Zhengyang (1, 2)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Agricultural Equipment for Conservation Tillage, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China; (3) College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian; 271018, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 19-27 and 49

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issue that high-speed operation induces excessive vibrations of no-till seeding units, thereby deteriorating seeding quality, a dual-regulation vibration-reduction no-till seeding unit was developed based on downforce stabilization control and furrow-depth attenuation control. By integrating multiple sensors, including an inclinometer, a pin-shaft force sensor, and an angular displacement sensor, the system enabled real-time acquisition of the profiling angle, downforce cylinder thrust, and depth-limiting wheel arm rotation. Consequently, closed-loop regulation of the downforce hydraulic cylinder pressure and the damping cylinder displacement was achieved. Stable downforce output and impact-limiting damping control effectively suppressed unit vibration, enabling active regulation of downforce and seeding depth. A coupled co-simulation model of the dual-regulation hydraulic control system was constructed by using AMESim and Simulink. Simulation results indicated that PID, fuzzy-PID, and sliding-mode control (SMC) exhibited comparable performance in regulating the downforce cylinder force. However, for damping-cylinder displacement control, SMC demonstrated clear advantages over conventional PID and fuzzy-PID control, reducing the maximum overshoot by 5. 56 percentage points and 2. 01 percentage points, and shortening the settling time by 1. 27 s and 1. 45 s, respectively. A dual-regulation vibration-reduction test bench for the no-till seeding unit was built, and a downforce measurement model integrating profiling angle and hydraulic pressure was established. Experimental validation of the proposed control strategy showed that under different hydraulic pressures and four-bar linkage inclination settings, the coefficient of determination reached 0. 944 63 with an adjusted value of 0.938 19, demonstrating high control accuracy of the seeding downforce. The findings can provide a theoretical foundation for vibration-reduction control of no-till seeding units. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Cylinders (shapes)

Controlled terms: Agricultural machinery  -  Damping  -  Electric machine control  -  Hydraulic fluids  -  Hydraulic machinery  -  Seed  -  Sliding mode control  -  Stabilization  -  Three term control systems  -  Vibration control   -  Vibrations (mechanical)

Uncontrolled terms: Damping control  -  Depth-limited vibration damping  -  Dual-regulation vibration damping control system  -  Electric  -  Hydraulic control  -  No-tillage seeding  -  No-tillage seeding unit  -  Pressure stabilization  -  Vibration-damping

Classification code: 301 Fluids  -  408.1 Structural Members and Shapes  -  731.1 Control Systems  -  731.2 Control System Applications  -  731.3 Specific Variables Control  -  821.2 Agricultural Machinery and Equipment  -  821.5 Agricultural Products  -  1301.1.1 Mechanics  -  1401.1 Hydraulics  -  1401.2 Hydraulic Equipment and Machinery

Numerical data indexing: Time 2.70E+01s, Time 4.50E+01s

DOI: 10.6041/j.issn.1000-1298.2026.04.003

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

16. Kinetic Analysis and Parameter Optimization of Garlic Stem Cutting Device Based on SPH FEM

Accession number: 20260620043365

Title of translation: 基于SPH-FEM大蒜切茎装置动力学分析及参数优化

Authors: Li, Hua (1); Gao, Han (1); Wang, Yongjian (1); Yu, Haiming (1); Fu, Jieyi (1); Guo, Jinxiao (1)

Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 211800, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 192-202

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the current issues with garlic combined harvesters’ stem-cutting devices, including suboptimal cutting performance, high cutting resistance, delayed cutting causing bulb damage, and clogging of gripping and conveying mechanisms, an SPH — FEM coupled algorithm was employed to design a dual-disc garlic stem-cutting device. Dynamic analysis and parameter optimization were subsequently conducted. Firstly, the material model for garlic stems was established based on their structural characteristics, physical parameters, and mechanical properties. A simulation model of the garlic cutting process was constructed by using ANSYS/LS — DYNA. Finite element simulation results determined the optimal blade disc parameters; disc thickness of 2 mm, blade angle of 15°, and blade overlap of 15 mm. Single-factor simulation tests were conducted by using the model to establish the operational ranges for the garlic cutting device; feed rate of 1. 5 -2.5 km/h, disc rotational speed of 400 -600 r/min, and disc spacing of 1 - 3 mm. Finally, a Box — Behnken design, a three-factor, three-level orthogonal combination test plan was implemented. Bench tests determined the maximum cutting resistance of the disc under each factor level. Design-Expert 13 was employed to conduct variance analysis and response surface analysis on the test results, yielding the optimal operating parameters for the garlic stem-cutting device; feed rate of 2. 1 km/h, disc rotational speed of 560 r/min, and disc spacing of 1 mm. Bench test results indicated that under optimal operating parameters, the maximum cutting resistance was 7. 33 N with an error margin of 7. 5% . This dual-disc cutting device exhibited low cutting resistance, stable performance, and produced relatively flat stem cross-sections. Crucially, no bulb damage occurred during testing, fulfilling the stem-cutting requirements for garlic harvesting. It provided valuable reference for designing combined garlic harvesting machinery. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Finite element method

Controlled terms: Cutting  -  Cutting tools  -  Disks (structural components)  -  Harvesters  -  Machine design  -  Rotating disks

Uncontrolled terms: Coupled algorithms  -  Cutting resistance  -  Disk rotational speed  -  Double-disk stem removal apparatus  -  Element method  -  Feedrate  -  Garlic stem removal  -  Parameter optimization  -  SPH — FEM coupled algorithm  -  Stem-cutting device

Classification code: 408.1 Structural Members and Shapes  -  601 Mechanical Design  -  601.2 Machine Components  -  603.1 Machine Tool Accessories  -  604.1 Metal Cutting  -  821.2 Agricultural Machinery and Equipment  -  904 Design  -  1201.9 Numerical Methods

Numerical data indexing: Angular velocity 6.68E+00rad/s to 1.002E+01rad/s, Angular velocity 9.352E+00rad/s, Force 3.30E+01N, Percentage 5.00E+00%, Size 1.00E+03m, Size 1.00E-03m, Size 1.00E-03m to 3.00E-03m, Size 1.50E-02m, Size 2.00E-03m, Size 5.00E+03m to 2.50E+03m

DOI: 10.6041/j.issn.1000-1298.2026.04.019

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

17. BiLSTM - Transformer Hybrid for Predicting Tilt Risk of Crawler Sugarcane Harvesters in Hilly Terrain

Accession number: 20260620043289

Title of translation: 基于BiLSTM-Transformer混合模型的丘陵地区履带式甘蔗收获机倾翻风险预测

Authors: Li, Shangping (1, 2); Song, Jiahua (1, 2); Wen, Chunming (2); Li, Kaihua (3); Wei, Yutong (1, 2); Cheng, Jianhua (4)

Author affiliation: (1) College of Physics and Electronic Information, Guangxi University for Nationalities, Nanning; 530006, China; (2) Guangxi Engineering Research Center of Intelligent Vision and Collaborative Robotics, Nanning; 530006, China; (3) Nanning Taiyin Technology Co., Ltd., Nanning; 530103, China; (4) College of Mechanical Engineering, Guangxi University, Nanning; 530004, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 213-223

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To address the rollover risk of crawler-type sugarcane harvesters operating on hilly terrain-caused by a high center of gravity and narrow track width—this study establishes a real-time vibration measurement and prediction framework. Vibration acceleration signals of the harvester frame are collected during tilt tests on a dedicated experimental platform. The signals are processed in the frequency domain to extract key vibration features that characterize different inclination states. A hybrid BiLSTM -Transformer model is proposed to predict potential rollover conditions. In the proposed method, vibration acceleration data are first preprocessed and decomposed using empirical mode decomposition (EMD) to obtain denoised and reconstructed time-frequency components. The BiLSTM network effectively captures long-term temporal dependencies in the vibration sequences, while the Transformer module focuses on extracting local temporal and attention-based contextual features. The complementary strengths of these two networks enhance both learning efficiency and predictive stability. Experimental results demonstrate that the proposed hybrid model achieves a prediction accuracy of 95. 39% with an average response time of 11. 87 ms, meeting real-time monitoring requirements. To further validate model effectiveness, t — SNE dimensionality reduction visualization and confusion matrix analysis are performed, confirming the model’s discriminative capability across different tilt states. This research provides a reliable theoretical and technical foundation for the development of real-time rollover warning and automatic leveling control systems for crawler-type sugarcane harvesters in complex hilly environments. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Frequency domain analysis

Controlled terms: Dimensionality reduction  -  Forecasting  -  Harvesters  -  Leveling (machinery)  -  Real time systems  -  Vibration measurement

Uncontrolled terms: BiLSTM  -  Center of gravity  -  Crawler types  -  Hilly terrains  -  Real- time  -  Sugarcane harvesters  -  Toppling prediction  -  Track width  -  Transformer  -  Vibration acceleration

Classification code: 821.2 Agricultural Machinery and Equipment  -  941.5 Mechanical Variables Measurements  -  1101.2 Machine Learning  -  1103.4 Digital Computers and Systems  -  1201.4 Applied Mathematics  -  1201.6 Control Theory  -  1202 Statistical Methods

Numerical data indexing: Percentage 3.90E+01%, Time 8.70E-02s

DOI: 10.6041/j.issn.1000-1298.2026.04.021

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

18. Compliance Control for Strawberry Stem-breaking Harvesting Based on RPU - RPR - UPR Parallel Wrist Joint

Accession number: 20260620043653

Title of translation: 基于RPU-RPR-UPR并联腕关节草莓断柄采摘柔顺控制研究

Authors: Li, Yuechan (1); Ma, Zenghong (1, 2); Du, Xiaoqiang (1, 3)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province, Hangzhou; 310018, China; (3) Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou; 310018, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 128-137

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the challenges of dynamic end-effector payload variation, insufficient environmental interaction compliance, and limited trajectory tracking accuracy in strawberry harvesting robots, a fully decoupled parallel wrist joint based on an RPU — RPR — UPR configuration was designed, and its inverse kinematic model was established. To improve the positioning accuracy of the manipulator’s end-effector, a complete system dynamics model was developed, and an adaptive sliding mode control (ASMC) algorithm was implemented. Model uncertainties were estimated and compensated in real time by the ASMC, effectively alleviating the chattering phenomenon associated with conventional sliding mode control. As a result, the average tracking errors of the wrist joint’ s a, /3, and h degrees of freedom were reduced to 0.075 8°, 0.077 1°, and 0.041 4 mm, respectively, significantly outperforming both PID control and traditional sliding mode control (SMC) in terms of trajectory tracking accuracy and system robustness. To enhance harvesting smoothness, a fuzzy inference-based variable admittance controller was developed. Admittance parameters were dynamically adjusted according to interaction forces and system state errors, enabling autonomous modulation of the robot ‘ s stiffness-compliance characteristics and thereby improving its disturbance rejection capability and environmental adaptability. Simulation results showed that, under external disturbances of 10 N and 20 N, the proposed fuzzy variable admittance control reduced overshoot by 12. 5% and 17. 8%, and shortened settling time by 0. 14 s and 0. 25 s, respectively, compared with fixed-parameter admittance control-demonstrating superior dynamic performance. The designed parallel wrist joint was integrated into a mobile strawberry harvesting platform. Acceleration response tests revealed that, during end-effector load variations, compliant control reduced the average acceleration fluctuation amplitude by 45.5% compared with position control, indicating excellent dynamic compliance. In harvesting trials, a success rate of 93% was achieved with an average cycle time of 15 s per fruit, satisfying practical requirements for harvesting efficiency and reliability. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Fruits

Controlled terms: Adaptive control systems  -  Compliance control  -  Degrees of freedom (mechanics)  -  Disturbance rejection  -  Electric admittance  -  End effectors  -  Fuzzy inference  -  Harvesting  -  Inverse kinematics  -  Inverse problems   -  Manipulators  -  Position control  -  Robustness (control systems)  -  Three term control systems  -  Uncertainty analysis

Uncontrolled terms: Adaptive sliding mode control  -  Admittance control  -  Parallel mechanisms  -  Parallel wrists  -  Picking  -  Sliding-mode control  -  Strawberry  -  Tracking accuracy  -  Trajectory-tracking  -  Wrist joints

Classification code: 691.1 Materials Handling Equipment  -  701.1 Electricity: Basic Concepts and Phenomena  -  731 Automatic Control Principles and Applications  -  731.1 Control Systems  -  731.3 Specific Variables Control  -  731.5 Robotics  -  821.4 Agricultural Methods  -  821.5 Agricultural Products  -  1101 Artificial Intelligence  -  1201 Mathematics  -  1202.1 Probability Theory  -  1301.1.1 Mechanics

Numerical data indexing: Force 1.00E+01N, Force 2.00E+01N, Percentage 4.55E+01%, Percentage 5.00E+00%, Percentage 8.00E+00%, Percentage 9.30E+01%, Size 4.00E-03m, Time 1.40E+01s, Time 1.50E+01s, Time 2.50E+01s

DOI: 10.6041/j.issn.1000-1298.2026.04.013

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

19. Design and Experiment of Air-gap Adsorption Wheat Wide Seedling Strip Sowing Device

Accession number: 20260620043361

Title of translation: 气缝吸附式小麦宽苗带投种装置设计与试验

Authors: Liu, Benrui (1, 2); Li, Quan (1); Liu, Tao (1, 2); Wang, Chao (1, 2); Wang, Qingjie (1, 2); He, Jin (1, 2); Li, Hongwen (1, 2)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Agricultural Equipment for Conservation Tillage, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 38-49

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To address the problems of seed bouncing and non-uniform distribution during the seed delivery process of wide belt seed wheat planters, a pneumatic wide belt seed delivery device based on the action of a slit-induced adsorption force field was designed. A slit structure was introduced into the device to generate a localized adsorption force field, enabling uniform division of the falling seed population. Discrete element and finite element methods were employed to model and optimize key parameters, including the slit structure and the length of the intermediate section, thereby clarifying the effects of structural parameters on seed-guiding behavior and the uniformity of the pneumatic action zone. The pneumatic seed delivery process was simulated using a CFD — DEM coupling method. Air pressure, seeding rate, intermediate seed-guiding channel width, and slit structure were selected as influencing factors, while the longitudinal seeding rate consistency coefficient of variation among rows and the transverse in-row coefficient of variation were used as evaluation indices. Regression models were established using Minitab, and response surface analysis was conducted to determine the optimal parameter combination. The results indicate that seeding rate, slit structure, and intermediate seed-guiding channel width have significant effects on the coefficient of variation of longitudinal seeding rate consistency among rows, whereas seeding rate, air pressure, and channel width significantly affect the in-row transverse coefficient of variation. When the air pressure was -0.8 kPa, the seeding rate was 150 kg*hm, the seed-guiding channel width was 11 mm, and the slit structure was rectangular, both coefficients of variation reached their lowest overall levels, with the longitudinal seeding rate consistency coefficient of variation at 2. 16% and the in-row transverse coefficient of variation at 8. 97% . Bench tests further verified the simulation results. With increasing positive pressure, the coefficient of variation of seeding rate consistency among rows first decreased and then increased under low seeding rates, while it continuously decreased under high seeding rates; a backflow phenomenon occurred when the air pressure reached approximately 2. 25 kPa. The in-row transverse coefficient of variation remained generally within the range of 8% -15% with no significant variation, meeting the operational requirements for precision and uniform wheat sowing. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Pneumatics

Controlled terms: Discrete element methods  -  Finite difference method  -  Finite element method  -  Regression analysis  -  Seed

Uncontrolled terms: Air-pressure  -  CFD — DEM coupling  -  CFD-DEM  -  Channel widths  -  Coefficients of variations  -  Guiding device  -  Pneumatic seed delivery  -  Seeding rate  -  Slit structures  -  Wheat wide belt seed

Classification code: 821.5 Agricultural Products  -  1201.5 Computational Mathematics  -  1201.9 Numerical Methods  -  1202.2 Mathematical Statistics  -  1401.3 Pneumatics, Equipment and Machinery

Numerical data indexing: Mass 1.50E+02kg, Percentage 1.60E+01%, Percentage 8.00E+00% to 1.50E+01%, Percentage 9.70E+01%, Pressure -8.00E+02Pa, Pressure 2.50E+04Pa, Size 1.10E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.005

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

20. Rice Pest Detection Method Based on Improved YOLO v8

Accession number: 20260620043670

Title of translation: 基于改进YOLO v8的水稻害虫检测方法

Authors: Liu, Shanmei (1); Cheng, Kim (1); Zhai, Ruifang (1); Chen, Yang (1); Peng, Hui (1)

Author affiliation: (1) College of Informatics, Huazhong Agricultural University, Wuhan; 430070, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 317-326

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to achieve real-time and accurate detection of multi-scale rice pests in complex backgrounds, a dataset containing images of various rice pests was constructed and a pest detection model called YOLO v8 — FDI was proposed. The model was based on the YOLO v8n architecture, utilizing the more efficient FasterNet as its backbone network. This design optimized the network structure while maintaining sensitivity to pest features. Dynamic Head technology was incorporated, allowing the model to dynamically adjust the detection heads in the output layer. This improved the model’s accuracy and generalization for pests of different types and sizes. Furthermore, the Inner — IoU loss function was adopted to automatically adjust scaling factors during loss calculation process. This accelerated training convergence and further improved model performance. Experimental results showed that the YOLO v8 — FDI model processed a single pest image in an average time of 12. 43 m, achieving a processing speed of 80 frames per second (FPS), meeting real-time requirements for practical applications. On the test set, the model’s detection precision, mean average precision mAP@ 0. 5; 0. 95 and Fl score were 97.7%, 94.0%, and 97. 2%, respectively. Compared with YOLO v3 - tiny, YOLO v5n, YOLO v7 - tiny, YOLO v8n, YOLO v9t,and YOLO vlOn, precision was improved by 5. 2, 2.7, 6.7, 3.4, 2.2, and 3.2 percentage points, mAP@ 0. 5;0. 95 was increased by 10. 8, 5.4, 18. 1, 2. 3, 1.0, and 6. 4 percentage points, and Fl score was raised by 2. 6, 2. 0, 4. 9, 1.2, 1.3, and 2. 9 percentage points. The novelty lied in the improvements made to the YOLO v8n architecture by integrating FasterNet, Dynamic Head, and the Inner — IoU loss function. These enhancements significantly improved the model’s accuracy and generalization, offering strong technical support for real-time and accurate pest monitoring in complex backgrounds. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Complex networks

Controlled terms: Agricultural machinery  -  Distributed computer systems  -  Image enhancement  -  Network architecture  -  Pesticides

Uncontrolled terms: Complex background  -  Dynamic head  -  Fasternet  -  Model generalization  -  Percentage points  -  Pest detection  -  Real- time  -  Rice  -  Rice pests  -  YOLO v8n

Classification code: 821.2 Agricultural Machinery and Equipment  -  821.3 Agricultural Chemicals  -  1103.4 Digital Computers and Systems  -  1105 Computer Networks  -  1105.2 Internet and Web Technologies  -  1106.3.1 Image Processing  -  1502.1.1.3 Soil Pollution

Numerical data indexing: Percentage 2.00E+00%, Percentage 9.40E+01%, Percentage 9.77E+01%, Size 4.30E+01m

DOI: 10.6041/j.issn.1000-1298.2026.04.031

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

21. Optimized Design and Experiment of Secondary Tossing Cotton Stalk Crushing and Returning Device

Accession number: 20260620043481

Title of translation: 二次抛送式棉秆粉碎还田装置优化设计与试验

Authors: Liu, Xuanfeng (1, 2); Zhang, Xuejun (1); Zhou, Xin (2); Wang, Yichao (1); Yang, Yuxin (2); Jiang, Yongxin (2); Zhang, Haichun (2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Institute of Agricultural Mechanization, Xinjiang Academy of Agricultural Sciences, Urumqi; 830091, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 246-256

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issues of uneven crushing and straw drop during the cotton stalk fragmentation and returning process in Xinjiang, the design of a secondary wind-assisted cotton stalk crushing and returning device was optimized. The device employed a dual-helix crushing blade set and a wind-assisted conveying blade set for collaborative operation, integrating a diversion air duct to achieve primary crushing and secondary conveying of stalks. The structural configuration and parameters of key components were determined through theoretical analysis. To investigate the influence of operational parameters on the internal flow field during the crushing and conveying process, CFD simulations were conducted to analyze the effects of crushing blade shaft speed, conveying blade shaft speed, and the number of wind-assisted blades. A three-factor three-level orthogonal experiment was performed with crushing blade shaft speed, ground clearance, and conveying blade shaft speed as experimental variables, and stalk drop rate and crushing qualification rate as evaluation metrics. Parameter optimization yielded the optimal combination; crushing blade shaft speed of 2 490 r/min, ground clearance of 77 mm, and conveying blade shaft speed of 2 870 r/min. Field validation tests under these conditions resulted in a stalk drop rate of 3.41% and a crushing qualification rate of 97.85%, with relative errors between experimental and theoretical values below 5%, meeting industry standards. This research can provide technical support for enhancing the efficiency of cotton stalk returning equipment. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Cotton

Controlled terms: Agricultural machinery  -  Conveying  -  Crushing  -  Drops  -  Turbomachine blades

Uncontrolled terms: Collaborative operations  -  Cotton stalk  -  Crushing and returning device  -  Drop rates  -  Ground clearance  -  Optimized designs  -  Parameter optimization  -  Secondary tossing  -  Shaft speed  -  Xinjiang

Classification code: 214 Materials Science  -  301.1.1 Liquid Dynamics  -  301.2.2 Electrohydrodynamics  -  692.1 Conveyors  -  821.2 Agricultural Machinery and Equipment  -  821.5 Agricultural Products  -  1007 Turbomachinery

Numerical data indexing: Angular velocity 1.4529E+01rad/s, Angular velocity 8.183E+00rad/s, Percentage 3.41E+00%, Percentage 5.00E+00%, Percentage 9.785E+01%, Size 7.70E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.024

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

22. Field Straw Coverage Detection Method Based on Improved U KAN

Accession number: 20260620043355

Title of translation: 基于改进U-KAN的田间秸秆覆盖率检测技术

Authors: Ma, Qin (1); Chen, Zilin (1); Wang, Haotian (1); Liu, Zhe (2); Zhang, Kai (1); Shi, Xiaochen (1); Li, Hailong (3); Zhang, Jingfang (3); Wu, Caicong (1)

Author affiliation: (1) Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China; (2) College of Land Science and Technology, China Agricultural University, Beijing; 100083, China; (3) Weichai Lovol Smart Agriculture Technology Co., Ltd., Weifang; 261206, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 309-316

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurately and efficiently detecting straw coverage is crucial for soil protection and sustainable agriculture, as straw coverage not only affects soil fertility and moisture retention but also plays a key role in controlling soil erosion and improving the ecological environment. However, existing straw coverage detection models are often susceptible to interference from natural environmental factors such as lighting and shadows in practical applications. When the similarity between the straw and the soil in terms of color and texture is high, the accuracy of these models significantly decreases, leading to inaccurate coverage assessments and ultimately affecting the efficiency and reliability of farmland management decisions. Aiming to address the challenges posed by the diverse morphology of straw in images captured by vehicle-mounted cameras, including issues of image reflection and shadows, a novel semantic segmentation method called UMU — KAN for detecting straw of varying scales in natural environments was proposed. The replacement of conventional dilated convolutions in the atrous spatial pyramid pooling module with depth-wise dilated separable convolutions was proposed to enhance the extraction of fine-grained straw-related detail information. Additionally, a strip pooling branch captured features of widely spaced straw more effectively, integrating feature information from various branches through skip connections to reduce information loss. This series of improvements constructed a mixed pooling dilated spatial pyramid module, applied to the top semantic layer of the backbone network, thereby obtaining multi-scale information for sparsely distributed straw. Furthermore, a unified attention fusion module appeared during the decoding phase to effectively restore detailed edge information of straw segmentation, enabling the model to better learn features from different levels. Experimental results demonstrated that UMU — KAN achieved a mean intersection over union (mloU) of 85.36% and a mean pixel accuracy (mPA) of 91.71% on the constructed straw dataset. Compared with the Unet, Swin — Unet, and DeepLabv3 + models, UMU — KAN improved mloU by 4.20, 3.26, and 1.25 percentage points, respectively, and mPA by 3.58, 2. 39, and 0. 77 percentage points, respectively. Additionally, the parameter count of UMU — KAN was significantly lower than that of Swin — Unet and DeepLabv3 + . UMU — KAN successfully achieved accurate detection of straw in images captured by agricultural machinery cameras, ensuring high detection efficiency even under dynamic and uncontrolled outdoor conditions. This not only highlighted the model’s adaptability and precision but also further demonstrated the significant developmental potential of the KAN architecture in the field of precision agriculture, contributing to the promotion of sustainable agricultural practices and enhancing the efficiency of agricultural management. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Convolution

Controlled terms: Agriculture  -  Environmental protection  -  Image enhancement  -  Morphology  -  Natural environment  -  Semantic Segmentation  -  Semantics  -  Soil conservation  -  Soils  -  Straw   -  Sustainable agriculture  -  Textures

Uncontrolled terms: Atrous spatial pyramid  -  Detection methods  -  Moisture retention  -  Percentage points  -  Semantic segmentation  -  Soil fertility  -  Soil Protection  -  Spatial pyramids  -  Straw coverage  -  Sustainable agriculture

Classification code: 214 Materials Science  -  483.1 Soils and Soil Mechanics  -  716.1 Information Theory and Signal Processing  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.6 Agricultural Wastes  -  903.2 Information Dissemination  -  1106.3.1 Image Processing  -  1106.8 Computer Vision  -  1501.1 Sustainable Development  -  1501.2.1 Resource Conservation  -  1502.1 Environmental Impact and Protection  -  1502.2 Ecology and Ecosystems

Numerical data indexing: Percentage 8.536E+01%, Percentage 9.171E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.030

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

23. Precision Planting Control System for Electro-hydraulic Driven Potato Planter with Regard to Planting Distance

Accession number: 20260620043293

Title of translation: 马铃薯播种机株距精量控制系统设计与试验

Authors: Mao, Xu (1, 2); Wang, Da (1); Yu, Bojie (1); Li, Hao (1); Li, Yang (3); Yang, Deqiu (3); Tan, Yu (1)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) State Key Laboratory of Intelligent Agricultural Power Equipment, Beijing; 100083, China; (3) MENOBLE Co., Ltd., Beijing; 100083, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 28-37

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the limitations in plant spacing adjustment capability and the issues of low seeding precision and poor uniformity caused by high-speed slippage in traditional ground-wheel-driven potato planters, an intelligent precision seeding control system for potatoes was developed. The system replaced the mechanical ground-wheel drive with a hydraulic motor drive, achieving independent control of two seeding units through a dual-circuit hydraulic integrated valve block. A PLC controller integrating a fuzzy PID algorithm was developed, establishing a closed-loop speed regulation system based on dual feedback signals from the travel speed and hydraulic motor speed. Parameters were dynamically adjusted according to the error value (e) and the error change rate (ec), significantly enhancing plant spacing uniformity and enabling stepless adjustment capability. AMESim — Simulink co-simulation results demonstrated that; under step signal input (70 r/min) and sudden load application (100 N • m) conditions, the system exhibited excellent synchronization between the dual motors (with no overshoot), a response time under 0. 5 s, and a rotational speed fluctuation amplitude below 1.5%, converging within 0.3 s. Laboratory bench tests and field trials indicated that; across a plant spacing range of 0. 16 ~0. 24 m and operational speeds of 2 ~ 8 km/h, the actual seeding plant spacing exhibited a relative deviation not exceeding 8%, with a qualification rate reaching or exceeding 92% . These performance metrics complied with relevant industry standards and fulfilled the high-reliability requirements for precision seeding under diverse operating conditions. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Three term control systems

Controlled terms: Electric drives  -  Electric machine control  -  Electric motors  -  Hydraulic drives  -  Hydraulic motors  -  Seed  -  Speed regulators  -  Valves (mechanical)  -  Wheels

Uncontrolled terms: Electro-hydraulic drive  -  Electro-hydraulics  -  Fuzzy-PID control  -  Ground wheels  -  High Speed  -  Plant spacing  -  Plantings  -  Potato planter  -  Precise spacing control  -  Precision seeding

Classification code: 601.2 Machine Components  -  601.3 Mechanisms  -  602.1 Mechanical Drives  -  704.2 Electric Equipment  -  705.1 Electric Machinery  -  705.3 Electric Motors  -  731.1 Control Systems  -  731.2 Control System Applications  -  732.1 Control Equipment  -  821.5 Agricultural Products  -  1401.2 Hydraulic Equipment and Machinery

Numerical data indexing: Angular velocity 1.169E+00rad/s, Force 1.00E+02N, Percentage 1.50E+00%, Percentage 8.00E+00%, Percentage 9.20E+01%, Size 2.00E+03m to 8.00E+03m, Size 2.40E+01m, Time 3.00E-01s, Time 5.00E+00s

DOI: 10.6041/j.issn.1000-1298.2026.04.004

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

24. Experiment on Calculation Method of Natural Frequency of Trunk for Camellia oleifera with Constrained Cables

Accession number: 20260620043347

Title of translation: 绳索约束油茶树主干自然频率计算与试验

Authors: Tang, Lewei (1, 2); Zhang, Huiyu (1); Pan, Rui (1); Wan, Ziping (1, 2); Wu, Mingliang (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha; 410128, China; (2) Specialty Oil Crop, Camellia oleifera) Full Mechanization Research Center, Changsha; 410128, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 224-233

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The problems of high manual labor intensity as well as high harvesting cost become more serious for Camellia oleifera industry, which promote the research of Camellia oleifera harvesting technologies with high efficiency. In order to effectively improve the energy utilization rate of mechanized harvester of Camellia oleifera fruit, the cable-driven excitation approach was employed with negligible cable mass to replace the traditional rigid vibration. Based on a bifurcated basic unit of tree, cable — tree reduced system was constructed with considering two constrained cables. The energy transfer mechanism in the reduced system was investigated to deduce the calculation formula of natural frequency. An ideal truncated cone model with variable circular cross sections for branches was utilized, and the measurement approach of measuring elasticity modulus of branches with variable cross-sections was presented. Taking Camellia oleifera varieties in Hunan Province as an application example, the basic parameters of the tree and the cable were measured, the natural frequency of the cable — tree reduced system was obtained. The theoretical values of the natural frequency for the cable — tree reduced system were compared with simulation and the experimental results. It showed that the relative errors of simulation results and theoretical results were less than 6. 4%, the relative errors of the experimental results and the theoretical results were less than 8. 6%, which verified the efficiency of the proposed calculation formula of natural frequency for Camellia oleifera with constrained cables. By comparing the resulting modulus of elasticity from the presented measurement approach and the conventional three-point bending test, the relative measuring error was within 7% and thus the feasibility of the presented measurement approach was validated. The research results can provide a theoretical basis for the design of a flexible cable-driven branch-vibrating harvester for Camellia oleifera fruits. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Natural frequencies

Controlled terms: Bifurcation (mathematics)  -  Cables  -  Elastic moduli  -  Elasticity  -  Energy utilization  -  Errors  -  Forestry  -  Fruits  -  Harvesters

Uncontrolled terms: Basic units  -  Bifurcated basic unit of tree  -  Cable constraint  -  Cable — tree reduced system  -  Cable-driven  -  Camellia oleifera  -  Camellia oleifera fruits  -  Manual labors  -  Reduced systems  -  Relative errors

Classification code: 214.1.3 Elasticity, Plasticity, Creep and Deformation  -  731.1 Control Systems  -  731.1.1 Error Handling  -  821.1 Woodlands and Forestry  -  821.2 Agricultural Machinery and Equipment  -  821.5 Agricultural Products  -  1009.2 Energy Consumption  -  1201 Mathematics  -  1301.1.4 Quantum Theory; Quantum Mechanics

Numerical data indexing: Percentage 4.00E+00%, Percentage 6.00E+00%, Percentage 7.00E+00%

DOI: 10.6041/j.issn.1000-1298.2026.04.022

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

25. Design and Parameter Optimization of Adjustable Seed Cotton Cleaning Machines

Accession number: 20260620043284

Title of translation: 可调式籽棉清理机设计与参数优化研究

Authors: Wu, Yueming (1, 2); Zhang, Mengyun (1, 2); Wu, Chao (1, 2); Lu, Shihao (1, 3); Zhang, Ruoyu (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China; (3) Innovation Center for Digital Equipment and Technology for Smart Farms, Xinjiang Production and Construction Corps, Shihezi; 832003, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 84-96

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to achieve the synergistic optimization of impurity removal efficiency for the inclined seed cotton cleaner and the quality of cotton fibers post-cleaning under varying seed cotton moisture regain levels, the design of a device that adjusted the rotation angle of elliptical rods to modify the gap between adjacent grids was presented. It provided a systematic account of the device’ s key structure and operating principle, and established the adjustable range of parameters (8. 5 ~ 12.5 mm) through geometric calculations. Drawing on the test results of mass, destructive force, and destructive energy of single seed cotton lumps under a moisture regain range of 5. 5% -11.5%, the elastic collision process between single seed cotton lumps and spikes during the cleaning stage was analyzed, and the testing range for the spike roller’ s rotational speed was defined as 560 ~ 760 r/min. Building on the definition of the aforementioned testing parameter ranges, a quadratic regression orthogonal rotational combination experimental design was implemented—with spike roller rotational speed, seed cotton feeding rate, gap between adjacent grids, and seed cotton moisture regained as experimental factors, and the machine ‘ s impurity removal efficiency and seed cotton short fiber rate as evaluation indices. From this design, regression equations describing the relationships between the evaluation indices and individual experimental factors were derived. Furthermore, a mapping relationship between seed cotton moisture regain and processing parameters was established by using the non-dominated sorting genetic algorithm with an elitist strategy (here after referred to as NSGA - II). Verification tests under multiple operating conditions demonstrated that in comparison with the pre-optimization state, the machine’ s impurity removal efficiency was enhanced by a maximum of 14. 14 percentage points, while the seed cotton short fiber rate was decreased by a maximum of 11.22 percentage points. For different parameter combinations, the maximum relative error associated with the machine’ s impurity removal efficiency was less than 4. 59%, and that for the seed cotton short fiber rate was less than 2. 80%, thereby validating the reliability of the regression model and the optimized parameters. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 20

Main heading: Cotton

Controlled terms: Agricultural machinery  -  Cleaning  -  Cotton fibers  -  Efficiency  -  Genetic algorithms  -  Regain  -  Removal  -  Rollers (machine components)

Uncontrolled terms: Adjustment of gap between adjacent grid  -  Cleaning machine  -  Impurity removal  -  Impurity removal efficiency  -  Inclined seed cotton cleaning machine  -  Parameter optimization  -  Removal efficiencies  -  Seed cotton  -  Short Fiber  -  Short fiber rate

Classification code: 213.1 Natural Fibers  -  213.3 Fiber Chemistry and Processing  -  601.2 Machine Components  -  802.3 Chemical Operations  -  821.2 Agricultural Machinery and Equipment  -  821.5 Agricultural Products  -  913.1 Production Engineering  -  1106 Computer Software, Data Handling and Applications  -  1201.7 Optimization Techniques

Numerical data indexing: Angular velocity 9.352E+00rad/s to 1.2692E+01rad/s, Percentage 5.00E+00% to 1.15E+01%, Percentage 5.90E+01%, Percentage 8.00E+01%, Size 5.00E-03m to 1.25E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.009

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

26. Design and Implementation of Digital Twin Monitoring System for Seed Cotton Cleaning Machine

Accession number: 20260620043685

Title of translation: 籽棉清理机数字孪生监测系统设计与实现

Authors: Yan, Wenbin (1, 2); Zhang, Ruoyu (1, 3); Wu, Chao (1, 3); Chen, Mingxiao (1, 2); Xu, Jiankang (1, 2); Li, Yulin (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China; (3) Innovation Center for Digital Equipment and Technology for Smart Farms, Shihezi Production and Construction Corps, Shihezi; 832003, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 72-83

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The seed cotton cleaning machine, as the core of cotton processing, faces operational challenges that limit overall efficiency. These include the inability to monitor equipment status in real time, delayed and passive fault alerts, and loosely defined operation and maintenance strategies during the impurity removal process. Such limitations have constrained further improvements in cotton processing quality, production efficiency, and overall enterprise profitability. To address these issues, digital twin technology was applied to create a virtual replica of the physical seed cotton cleaning machine. Based on a detailed analysis of the machine’ s operational principles and mechanical structure, a high-fidelity digital twin model was constructed. This model established a dynamic, bidirectional mapping mechanism between the physical machine and its virtual counterpart, enabling seamless data exchange and state synchronization. Using the Unity platform, a comprehensive digital twin monitoring system was developed for the seed cotton cleaning machine. This system integrated real-time data acquisition, simulation, and analysis capabilities. It allowed for real-time monitoring of the machine’ s operational status, facilitated proactive fault warnings through predictive analytics, and supported dynamic optimization of process decisions based on simulated scenarios. Performance evaluations of the system demonstrated strong stability and reliability with key metrics, including a data packet loss rate of 0, a CPU usage rate of approximately 5%, an average GPU memory occupancy of around 4%, and an average motion simulation frame time of 20.416 ms. The system was verified to possess excellent stability, reliability and robustness. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 22

Main heading: Predictive analytics

Controlled terms: Cleaning  -  Cotton  -  Data acquisition  -  Data reliability  -  Digital twin  -  Efficiency  -  Electronic data interchange  -  Physical addresses  -  Removal  -  Virtual addresses

Uncontrolled terms: Cleaning machine  -  Cotton processing  -  Design and implementations  -  Fault early warnings  -  Monitoring system  -  Operational challenges  -  Overall efficiency  -  Real- time  -  Seed cotton  -  Seed cotton cleaning machine

Classification code: 802.3 Chemical Operations  -  821.5 Agricultural Products  -  913.1 Production Engineering  -  1103 Computer Systems and Equipment  -  1103.1 Data Storage, Equipment and Techniques  -  1104 Computer Architecture  -  1106.2 Data Handling and Data Processing  -  1106.5 Computer Applications  -  1106.6 Data Analytics

Numerical data indexing: Percentage 4.00E+00%, Percentage 5.00E+00%, Time 2.0416E-02s

DOI: 10.6041/j.issn.1000-1298.2026.04.008

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

27. Strawberry Maturity Recognition in Unstructured Environments Based on MSCS YOLO

Accession number: 20260620043282

Title of translation: 基于MSCS-YOLO的非结构化环境中草莓成熟度识别

Authors: Wang, Yongsheng (1); Ding, Yu (1); Zhang, Ruochen (2, 3); Xu, Hongguang (1); Fan, Yue (4)

Author affiliation: (1) Artificial Intelligence College, Hebei Oriental College, Langfang; 065000, China; (2) Research Center for Intelligent Equipment Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (3) National Engineering Research Center for Intelligent Equipment in Agriculture, Beijing; 100097, China; (4) Economics and Management College, Hebei Oriental College, Langfang; 065000, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 296-308

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the problems of small strawberry individuals and serious inter-individual occlusion, a strawberry ripeness detection method was proposed based on MSCS — YOLO in an unstructured environment. The method introduced the multi-scale dilated attention (MSDA) mechanism in the Neck part of the YOLO v8n model, which enlarged the sensory field of the model and solved the problem of small strawberry fruits and easy to ignore features. Meanwhile, the improved C2f — Triplet attention structure was utilized to replace the C2f structure in the Neck part to capture the information of the strawberry image more comprehensively from the three dimensions, which enhanced the model’s target recognition ability in the case of fruit occlusion. Embedding the improved SAHead detection head into the YOLO v8n model enhanced the model’s recognition accuracy for strawberries with different ripeness levels in unstructured environments. The experimental results showed that the MSCS —YOLO model achieved an average accuracy of 94. 22% in the task of recognizing three types of strawberries; ripe, moderately ripe and unripe, which was 1. 38 percentage points and 5. 42 percentage points higher than that of the YOLO v8n and RTDETR — L models, respectively; among them, the accuracy of recognizing ripe and moderately ripe strawberries achieved 96. 35% and 92. 00%, which was 0. 82 percentage points and 3. 66 percentage points higher than that of the YOLO v8n model, respectively. The MSCS — YOLO model demonstrated better recognition performance and higher accuracy regardless of evening, sunny day, direct sunlight or light irradiation conditions. In addition, the model size of the improved model was 6. 42 MB, which was 45.22% and 86.93% smaller than that of the YOLO v7 - tiny and YOLO v9c models, respectively, and achieved the synergistic optimization of accuracy and efficiency while maintaining a similar model size with YOLO v8n. Therefore, the MSCS — YOLO model was more advantageous for deployment and application in resource-limited environments, and it can provide reliable technical support for later practical applications on strawberry maturity. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Fruits

Controlled terms: Flowcharting  -  Image enhancement

Uncontrolled terms: Attention mechanisms  -  Detection methods  -  Model size  -  Multi-scales  -  Percentage points  -  Sahead  -  Strawberry maturities  -  Strawberry maturity recognition  -  Unstructured environments  -  YOLO v8n

Classification code: 821.5 Agricultural Products  -  1106.1 Computer Programming  -  1106.3.1 Image Processing

Numerical data indexing: Percentage 0.00E00%, Percentage 2.20E+01%, Percentage 3.50E+01%, Percentage 4.522E+01%, Percentage 8.693E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.029

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

28. Autonomous Navigation Methods of Greenhouse Asparagus Harvesting Robot Based on 3D LiDAR SLAM

Accession number: 20260620043364

Title of translation: 基于3D激光雷达SLAM的温室芦笋采收机器人自主导航方法

Authors: Wang, Xiaochan (1, 2); Xie, Shenliang (1); Huang, Xuekai (1); Wang, Dezhi (1); Huang, Huixing (1)

Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Jiangsu Province Engineering Laboratory for Modern Facility Agriculture Technology and Equipment, Nanjing; 210031, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: 2026

Publication year: 2026

Pages: 138-150

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the challenges posed by the natural growth of asparagus branches and leaves obstructing pathways and the limited working space in raised beds, which result in significant map construction noise, large localization errors, and low mapping accuracy during the autonomous navigation of asparagus harvesting robots, an autonomous navigation system was presented based on 3D LiDAR SLAM for greenhouse asparagus harvesting robots. Initially, 3D point cloud data from the greenhouse environment were acquired by using a Velodyne 16-line 3D LiDAR sensor combined with an N100 inertial measurement unit (IMU) . An adaptive point cloud filtering method was employed to preprocess the point cloud data, removing noise caused by the asparagus branches and leaves, thereby reducing the computational burden on the navigation system. Subsequently, a global re-localization process was performed by using the Cartographer pure localization algorithm based on extended Kalman filtering (EKF). For path planning, the Dijkstra algorithm was utilized for global path planning, while the dynamic window approach (DWA) was applied for local path planning. Experimental results demonstrated that the optimal parameter combination for the adaptive point cloud filtering method was kt =6.912,5, = 0.334, and,s2 = 0.918. The integration of adaptive point cloud filtering with the Cartographer algorithm enabled high-precision mapping in the greenhouse environment, with a maximum absolute error of 0. 056 m, a maximum relative error of 9. 3%, and a root mean square error of 0. 035 m. The improved localization algorithm achieved lateral deviation no greater than 0. 196 m and longitudinal deviation no greater than 0. 082 m in the greenhouse environment. During autonomous navigation at speeds of 0. 10 m/s, 0. 20 m/s, and 0. 30 m/s, the lateral, longitudinal, and heading mean deviations were no greater than 0. 082 m, 0. 091 m, and 7. 562°, respectively, while their corresponding standard deviations did not exceed 0. 078 m, 0. 092 m, and 6. 561°. The proposed navigation framework satisfied the high-precision mapping, localization, and navigation requirements for autonomous systems in greenhouse environments, providing a theoretical and technical foundation for the deployment of harvesting robots in agricultural settings. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Greenhouses

Controlled terms: Adaptive filtering  -  Adaptive filters  -  Air navigation  -  Clouds  -  Errors  -  Extended Kalman filters  -  Harvesting  -  Intelligent systems  -  Mapping  -  Mean square error   -  Motion planning  -  Navigation systems  -  Optical radar  -  Robots  -  SLAM robotics

Uncontrolled terms: Adaptive point cloud filtering  -  Asparagu harvesting robot  -  Autonomous navigation  -  Filtering method  -  Greenhouse environment  -  Harvesting robot  -  LiDAR SLAM  -  Localization algorithm  -  Point cloud data  -  Point-clouds

Classification code: 405.3 Surveying  -  435.1 Navigation  -  435.1.1 Air Navigation and Traffic Control  -  443 Meteorology  -  703.2 Electric Filters  -  716.1 Information Theory and Signal Processing  -  716.2 Radar Systems and Equipment  -  731.1.1 Error Handling  -  731.5 Robotics  -  741.3 Optical Devices and Systems  -  821.4 Agricultural Methods  -  821.7 Farm Buildings and Other Structures  -  1101 Artificial Intelligence  -  1202.2 Mathematical Statistics

Numerical data indexing: Percentage 3.00E+00%, Size 1.96E+02m, Size 3.50E+01m, Size 5.60E+01m, Size 7.80E+01m, Size 8.20E+01m, Size 9.10E+01m, Size 9.20E+01m, Velocity 1.00E+01m/s, Velocity 2.00E+01m/s, Velocity 3.00E+01m/s

DOI: 10.6041/j.issn.1000-1298.2026.04.014

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

29. Design and Experiment of Target Control System for Field Laser Weeding Robot

Accession number: 20260820097114

Title of translation: 田间激光除草机器人对靶控制系统设计与试验

Authors: Zhong, Huiyu (1, 2); Chen, Yaoyang (1); Li, Jie (1, 2); Zhang, Xinyue (1, 2); Li, Yu (1); Wang, Qingjie (1, 2); Li, Hui (3)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Agricultural Equipment for Conservation Tillage, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China; (3) Shandong Society for Agricultural Machinery, Jinan; 250100, China

Corresponding author: Wang, Qingjie(wangqiingjie@cau.edu.cn)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 10-18

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Weeds compete with crops for nutrients and negatively affect agricultural yield. Traditional chemical weeding, though efficient, tends to cause environmental pollution and herbicide resistance. To achieve green, high-precision, and non-contact weeding operations, a target-oriented control system for a laser weeding robot was designed based on visual perception and path control. The system consisted of a depth camera, galvanometer scanner, and high-power CO2 laser, enabling weed detection, spatial localization, and laser operation. A Teensy 3.2 microcontroller-based integrated control scheme for the galvanometer and laser was proposed, which combined with the XY2100 communication protocol and TTL triggering mechanism, allowed precise galvanometer control and laser switching without the need for an additional control card. A camera-galvanometer extrinsic calibration method combining manual measurement and refinement optimization was established, and an attitude-error compensation algorithm based on geometric inverse solving was proposed to achieve automatic correction of aiming and firing under different pose conditions, followed by verification experiments. The results showed that the average aiming error of the system remained below 1 cm at different heights and tilt angles, and the laser weeding hit rate reached 98.6%. The optimal operating parameters were determined as a working height of 80 cm and a laser exposure time of 0.5 s. This system can enable high-precision, low-energy autonomous weeding and provide a reference for the application of laser weeding technology in complex field environments. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Calibration

Controlled terms: Cameras  -  Carbon dioxide lasers  -  Crops  -  Error compensation  -  Galvanometers  -  Herbicides  -  Weed control

Uncontrolled terms: Agricultural yields  -  Environmental pollutions  -  External parameter calibration  -  Galvo control  -  High-precision  -  Laser aiming  -  Laser weeding robot  -  Parameters calibrations  -  Weed identification  -  Weeding robots

Classification code: 731.1.1 Error Handling  -  742.2 Photographic and Video Equipment  -  744.1 Gas Lasers  -  803 Chemical Agents and Basic Industrial Chemicals  -  804.1 Organic Compounds  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.5 Agricultural Products  -  942.1.4 Electric and Electronic Instruments

Numerical data indexing: Percentage 9.86E+01%, Size 1.00E-02m, Size 8.00E-01m, Time 5.00E-01s

DOI: 10.6041/j.issn.1000-1298.2026.04.002

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

30. Analysis of Ecological Environment Evolution in Minqin Basin Considering Changes of Water Resources Condition

Accession number: 20260720049699

Title of translation: 考虑水资源条件变化的民勤盆地生态环境演变分析

Authors: Cao, Yin (1); Zhao, Hongli (1, 2); Ye, Yuntao (1, 2); Zhao, Huizi (1); Zhang, Huaiwen (1); Hua, Wenjing (1); Gan, Yu (1)

Author affiliation: (1) Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing; 100038, China; (2) Key Laboratory of River Basin Digital Twinning of Ministry of Water Resources, Beijing; 100038, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 381-390

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Ecological environment is closely related to the development of society and economy. Analyzing the process of ecological environment evolution is of great significance for guiding regional ecological environmental protection. However, analysis of regional ecological environment evolution based on a single indicator such as surface water area, groundwater level, normalized difference vegetation index (NDVI), etc., has limitation in a single perspective. Taking the Minqin Basin in the lower reaches of the Shiyang River as the study area. Firstly, spatial and temporal changes of four indicators, including surface water area and storage of Qingtu Lake, the terminal lake of the Shiyang River, groundwater level and storage anomaly, land use, and NDVI in Minqin Basin were analyzed. Then a comprehensive analysis of ecological environment evolution was conducted for the Minqin Basin from multiple perspectives, including surface and groundwater resource variations, land use type changes, and NDVI dynamics. The results shown that the water surface area and storage of Qingtu Lake generally followed a trend of drying up, increasing and shrinking. The groundwater water level and storage anomaly in the Minqin Basin generally showed a downward trend, with a significant slowdown in the decline from 2007 to 2013. The changes in land use types in the Minqin Basin were mainly characterized by the conversion between cropland, grassland, and barren, and since 2017, desertification in the Minqin Basin intensified. The NDVI in the Minqin Basin showed a non-significant increasing trend with a rate of 0.000 5 a1. By integrating the characteristics of the changes of surface water and groundwater resources conditions, land use types, and NDVI changes, the process of the ecological environment evolution in the Minqin Basin from 2003 to 2022 was divided into three stages of rapid degradation (2003-2006), recovery (2007-2013), and re-degradation (2014-2022) based on multi-perspective. Changes of water resources conditions induced by human activities constituted the primary factor influencing ecological evolution in the Minqin Basin. Establishing a regional economic and social development model that was coordinated with and compatible to the water resource carrying capacity of the Minqin Basin should be prioritized as a key direction for ecological conservation in the region. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 45

Main heading: Lakes

Controlled terms: Digital storage  -  Ecology  -  Economic and social effects  -  Groundwater  -  Groundwater resources  -  Land use  -  Natural environment  -  Regional planning  -  Rivers  -  Surface water resources

Uncontrolled terms: Change of water resource condition  -  Driving factors  -  Ecological environment evolution  -  Ecological environments  -  Minqin basin  -  Multi-source data  -  Multi-Sources  -  Resource conditions  -  Source data  -  Waters resources

Classification code: 403 Urban and Regional Planning and Development  -  403.2 Regional Planning and Development  -  407 Maritime and Port Structures; Rivers and Other Waterways  -  444.1 Surface Water  -  444.2 Groundwater  -  971 Social Sciences  -  1103.1 Data Storage, Equipment and Techniques  -  1502.2 Ecology and Ecosystems

DOI: 10.6041/j.issn.1000-1298.2026.04.037

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

31. Fuzzy Adaptive Energy Management Strategy for Hybrid Electric Tractors

Accession number: 20260720049728

Title of translation: 混合动力电动拖拉机模糊自适应能量管理策略研究

Authors: Gao, Zongyu (1, 2); Chai, Jianmin (3); Nie, Jing (1, 4); Li, Liqiao (1, 3)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery, Shihezi; 832003, China; (3) Management Committee of Xinjiang Production and Construction Corps Shihezi National Agricultural Science and Technology Park, Shihezi; 832011, China; (4) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China

Corresponding author: Li, Liqiao(liliqiao1108@163.com)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 108-118

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems such as low traction efficiency, short driving range and high energy consumption caused by frequent discharge of the power system due to the intense load fluctuations during the plowing operation of non-road mobile electric tractors, an adaptive energy management strategy for hybrid system combining fuzzy logic control and operation mode was proposed. The non-road mobile operation mode of the hybrid electric tractor was established. On this basis, the energy flow model of the lithium battery and supercapacitor hybrid system under different operation modes was established and the overall power system was modelled. Based on the analysis of the power requirements in the operation process, a fuzzy adaptive dynamic threshold adjustment strategy for the output voltage of the power system was proposed, and its weights were optimized by genetic algorithm with the goal of minimizing the energy-saving rate. Through simulation experiments, the power allocation, the state of charge and energy consumption under four energy control strategies were compared respectively to verify the power allocation effect of the hybrid system in different operation modes under different power allocation control strategies. The simulation experiments showed that compared with the proportional power allocation control strategy, the fuzzy adaptive control method control strategy could relatively increase the total braking energy recovery rate by 61.5%, the relative reduction rate of total energy consumption could reach 19.96% the peak current of lithium batteries could be reduced by 39.96%, and the driving range of electric tractors could be increased by 19.53%. The results showed that the proposed control method had the performance of improving the traction efficiency of electric tractors, extending the driving range, reducing energy consumption and prolonging the battery service life. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Energy management

Controlled terms: Adaptive control systems  -  Braking  -  Charging (batteries)  -  Electric machine control  -  Electric power system control  -  Electric traction  -  Energy efficiency  -  Energy management systems  -  Energy utilization  -  Fuzzy logic   -  Hybrid power  -  Hybrid systems  -  Lithium  -  Lithium batteries  -  Power control  -  Roads and streets  -  Traction control  -  Tractors (agricultural)  -  Tractors (truck)

Uncontrolled terms: Control strategies  -  Driving range  -  Electric tractors  -  Energy  -  Fuzzy adaptive  -  Hybrid  -  Operation mode  -  Power  -  Power allocations  -  Working mode

Classification code: 202.2.4 Lithium and Alloys  -  202.9.1 Alkali Metals  -  406.2 Roads and Streets  -  433 Rail Transportation  -  602 Mechanical Drives and Transmissions  -  663.1 Heavy Duty Motor Vehicles  -  702 Electric Batteries and Fuel Cells  -  702.1.1 Primary Batteries  -  702.1.2 Secondary Batteries  -  706.1 Electric Power Systems  -  731.1 Control Systems  -  731.2 Control System Applications  -  731.3 Specific Variables Control  -  821.2 Agricultural Machinery and Equipment  -  1009 Energy Management  -  1009.2 Energy Consumption  -  1102.1 Computer Theory, Includes Computational Logic, Automata Theory, Switching Theory, Programming Theory  -  1201.12 Modeling and Simulation  -  1501.1.1 Sustainable Transport

Numerical data indexing: Percentage 1.953E+01%, Percentage 1.996E+01%, Percentage 3.996E+01%, Percentage 6.15E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.011

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

32. Remote Sensing Segmentation of Cultivated Land Based on Multi-scale Attention Vision Mamba U - Net

Accession number: 20260720049732

Title of translation: 基于多尺度注意力视觉 Mamba U-Net的耕地遥感 分割方法

Authors: Hou, Xin’gang (1); Wang, Qin (1); Ling, Weifeng (1)

Author affiliation: (1) School of Accounting, Xijing University, Xi’an; 710123, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 279-286

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurate remote sensing image segmentation of cultivated land (CLRSIS) is crucial for yield prediction, agricultural management, and national food security. However, it remains challenging due to the high-resolution, large size and various remote sensing farmland images with irregularly boundaries and complex background. Convolutional neural networks (CNNs) and Transformers have been widely applied to RSI segmentation, but both of them have limited ability to handle long-range dependencies because of inherent locality or computational complexity. Aiming at the limitation of CNNs and Transformers, and the technical difficulties in CLRSIS, a multi-scale attention visual Mamba U Net (MSAVMUNet) model for CLRSIS was proposed. This model achieved performance breakthroughs through three innovative modules; firstly, modified visual state space module (MVSS) adopted a bidirectional selective scanning mechanism, enabling long-range dependency modeling while maintaining linear computational complexity. Secondly, channel-aware attention visual state-space (CAAVSS) effectively enhanced the discrimination between cultivated land and background features through dynamic spectral-spatial feature recalibration. Finally, multi-scale feature aggregation module (MSAA) built a cross-level feature pyramid to achieve multi-granularity information fusion. Experiments on public cultivated land datasets showed that this method was significantly superior to existing methods in terms of segmentation accuracy and computational efficiency, with the average segmentation precision accuracy and DSC achieving 85.60% and 84.46%, respectively. The research result can provide reliable technical support for the precise monitoring of cultivated land in smart agriculture. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 19

Main heading: Image segmentation

Controlled terms: Complex networks  -  Computational complexity  -  Computational efficiency  -  Convolutional neural networks  -  Cultivation  -  Farms  -  Remote sensing  -  Smart agriculture  -  Space optics  -  State space methods

Uncontrolled terms: Channel aware  -  Channel-aware attention VSS  -  Cultivated lands  -  Images segmentations  -  Multi-scale attention aggregation  -  Multi-scale attention mamba U-net  -  Multi-scales  -  Remote sensing image segmentation of cultivated land  -  Remote sensing images

Classification code: 655.2 Spacecraft Subsystems  -  731.1 Control Systems  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.4 Agricultural Methods  -  1101.2.1 Deep Learning  -  1102.1 Computer Theory, Includes Computational Logic, Automata Theory, Switching Theory, Programming Theory  -  1105 Computer Networks  -  1106.3.1 Image Processing  -  1201.6 Control Theory

Numerical data indexing: Percentage 8.446E+01%, Percentage 8.56E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.027

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

33. Multi-feature Fusion-based Pose Estimation Method for UAVs in Orchards

Accession number: 20260720049663

Title of translation: 基于多特征融合的果园无人机位姿估计方法

Authors: Liu, Xuhang (1); Chu, Zilong (1); Zhao, Hongli (1); Yu, Jiahui (1); Han, Wenting (1, 2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest a and F University, Shaanxi, Yangling; 712100, China; (2) Institute of Water-saving Agriculture in Arid Areas, Northwest a and F University, Shaanxi, Yangling; 712100, China

Corresponding author: Liu, Xuhang(liuxuhang@nwafu.edu.cn)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 1-9

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the challenge where canopy occlusion and repetitive features compromise unmanned aerial vehicle (UAV) pose estimation systems in orchard environments, a multi-feature fusion-based pose estimation method for UAVs in orchards was designed by introducing visual-inertial odometry technology and incorporating geometric constraints from point and line features. Firstly, the EDLines algorithm replaced the traditional LSD for extracting line features, while optical flow enabled rapid tracking and matching of feature points and lines across consecutive frames, with feature poses obtained through 3D feature reconstruction. Secondly, a tightly coupled pose estimation model was constructed to fuse inertial and visual information, within a local sliding window framework, a jointly minimized global cost function was established, the accurate position and attitude information of the orchard UAV was obtained by solving the cost function through optimization methods. Finally, comparative experiments were conducted in fruit-bearing apple orchards and grape greenhouses, with absolute trajectory error and relative trajectory error serving as evaluation metrics to validate the method’s effectiveness. Experimental results demonstrated that compared with traditional pose estimation methods utilizing LSD algorithm-extracted line features, the proposed method reduced the average absolute trajectory error by 10% and the average relative trajectory error by 27% . This approach effectively enhanced the accuracy and robustness of orchard drone navigation systems, providing reliable support for ensuring the safety of orchard drone operations. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Orchards

Controlled terms: Air navigation  -  Antennas  -  Computer vision  -  Cost estimating  -  Cost functions  -  Drones  -  Errors  -  Fruits  -  Navigation systems  -  Trajectories   -  Vision

Uncontrolled terms: Aerial vehicle  -  Estimation methods  -  Line features  -  Multi-feature fusion  -  Multi-sensor fusion  -  Odometry  -  Orchard unmanned aerial vehicle  -  Pose-estimation  -  Trajectory errors  -  Visual-inertial odometry

Classification code: 101.5 Ergonomics and Human Factors Engineering  -  435.1 Navigation  -  435.1.1 Air Navigation and Traffic Control  -  652.1.2 Military Aircraft  -  656 Space Flight and Research  -  716.5.1 Antennas  -  731.1.1 Error Handling  -  741.2 Vision  -  821.4 Agricultural Methods  -  821.5 Agricultural Products  -  911 Cost and Value Engineering; Industrial Economics  -  1106.8 Computer Vision  -  1201.7 Optimization Techniques

Numerical data indexing: Percentage 1.00E+01%, Percentage 2.70E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.001

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

34. Impact of Soil Texture on Accuracy of Saturated Soil Water Flux Direction Measurement Through Ratio Method

Accession number: 20260720049654

Title of translation: 土壤质地对比率法测量饱和土壤水通量方向精度的影响

Authors: Lu, Fuyun (1); Wu, Yang (2); Yang, Xijian (1); Wang, Wei (1)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Institute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100093, China

Corresponding author: Wang, Wei(weiwang@cau.edu.cn)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 399-406

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The direction of soil water flux is a key parameter in saturated soil flow fields. Soil texture significantly affects pore connectivity, which introduces randomness into the direction of water flow. Therefore, measuring water flux direction requires consideration of an appropriate spatial scale. The direction of saturated soil water flux can be determined by combining the ratio method with the principle of vector composition. Based on the above requirements, a penta-needle heat pulse probe (PHPP) was. designed to measure water flux magnitude in any two mutually perpendicular directions within a plane and to determine flux direction through vector composition. Experiments were conducted in saturated sand, sandy loam, and silt loam, with each soil type repacked three times. The experimental results showed that the accuracy of this method in measuring soil water flux direction was significantly influenced by soil texture. For fluxes greater than 4 cm/h, the mean absolute percentage errors (MAPE) of angle measurements in sand, sandy loam, and silt loam were 4.96%, 6.18%, and 15.06%, respectively. This indicated that the accuracy of water flux direction measurements was decreased with finer soil texture. Compared with fluxes below 4 cm/h, the standard deviations of angle measurements in sand, sandy loam, and silt loam were decreased by 10. 40°, 6. 65° and 6. 71°, respectively, for fluxes above 4 cm/h. This indicated that the accuracy of water flux direction measurements was improved with the increase of flux. Stable water flux angle measurements, with absolute errors below 7.5°, were achieved in sand at fluxes above 6 cm/h and in sandy loam above 3 cm/h, but not in silt loam. These findings suggested that pore connectivity in packed soils varied with texture under different fluxes and hydraulic gradients, thereby affecting measurement precision. Additionally, the geometric relationship between soil particle size and probe spacing affected the measurement accuracy of the ratio method. Optimizing the probe spacing of the PHPP based on soil particle size distribution may improve the reliability of water flux angle measurements by using the vector composition method. These findings can contribute to the development and practical application of heat pulse technology. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Probes

Controlled terms: Angle measurement  -  Flow of water  -  Food products  -  Particle size analysis  -  Quality control  -  Sand  -  Silt  -  Soil conditioners  -  Soil surveys  -  Textures   -  Vectors

Uncontrolled terms: Heat pulse  -  Heat pulse technique  -  Penta-needle heat pulse probe  -  Pulse technique  -  Pulse-probe  -  Ratio method  -  Soil textures  -  Soil water flux direction  -  Soil water fluxes

Classification code: 214 Materials Science  -  301.1.1 Liquid Dynamics  -  405.3 Surveying  -  482.2 Rocks  -  483.1 Soils and Soil Mechanics  -  805 Chemical Engineering  -  822.3 Food Products  -  913.3 Quality Assurance and Control  -  941.5 Mechanical Variables Measurements  -  1201.1 Algebra and Number Theory  -  1201.4 Applied Mathematics  -  1201.14 Geometry and Topology

Numerical data indexing: Percentage 1.506E+01%, Percentage 4.96E+00%, Percentage 6.18E+00%, Size 3.00E-02m, Size 4.00E-02m, Size 6.00E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.039

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

35. Comprehensive Assessment of Global Gross Primary Productivity Products Based on Flux Tower Observation Data

Accession number: 20260720049656

Title of translation: 基于通量塔观测数据的全球总初级生产力产品综合评估

Authors: Qian, Long (1); Wu, Lifeng (2); Yu, Xingjiao (1); Chen, Junying (1, 3); Xiang, Youzhen (1, 3); Liu, Xiaogang (2); Zhang, Zhitao (1, 4)

Author affiliation: (1) College of Water Resources and Architectural Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming; 650500, China; (3) Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Shaanxi, Yangling; 712100, China; (4) Xinjiang Research Institute of Agriculture in Arid Areas, Northwest A&F University, Urumqi; 830091, China

Corresponding author: Zhang, Zhitao(zhitaozhang@126.com)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 369-380

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurately estimating the spatiotemporal dynamics of global gross primary productivity (GPP) and its underlying mechanisms is crucial for understanding the global carbon cycle and climate change. Satellite remote sensing enables continuous observation of large-scale vegetation dynamics, providing valuable opportunities to study the spatial and temporal variations of GPP on a global scale. However, different GPP products often exhibit significant discrepancies in global GPP estimates, and comprehensive validation and comparison of these products at the global level has not yet been conducted. Therefore, the spatiotemporal consistency and interannual trends of eight GPP products (ECLUE, GLASS, GOSIF, MOD17A2H, MuSyQ, PMLv2, EC LUE, and VPM) during 2003-2014 were evaluated by using observations from 147 global flux towers. Spatiotemporal analysis revealed exceptionally strong temporal correlations among products (R2 > 0.96) . Spatially, all products exhibited high comparability (R2 ≥ 0.702) except GOSIF, which showed weaker consistency with others (R2 ≤ = 0.573) Annual GPP estimates ranged from 678.3g/(m2·a) (MOD17A2H) to 1 223.0 g/(m2·a) (GOSIF). All products except GLASS displayed increasing trends, with the northern hemisphere dominating the GPP increase. The proportion of ascending areas varied substantially across products, peaking in VPM (72.4%) and reaching a minimum in GOSIF (45.2%). Validation against flux tower data identified PMLv2 as the best-performing product R2 = 0.664), while EC-LUE (R2 = 0.547) and GLASS (R2 = 0.572) showed relatively lower accuracy. Systematic overestimations were observed in GOSIF, GLASS, and PMLv2 across most sites. Furthermore, the products demonstrated higher accuracy in America, high-latitude regions, and wetlands (WET) and evergreen needleleaf forests (ENF). The research results were significant for improving the ability of ecosystem process models to simulate different regions, and they contributed to a deep understanding of regional ecosystem carbon dynamics and the global carbon cycle. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 45

Main heading: Glass

Controlled terms: Carbon  -  Carbon cycle  -  Climate change  -  Forestry  -  Remote sensing  -  Towers  -  Vegetation  -  Wetlands

Uncontrolled terms: Assessment  -  Comprehensive assessment  -  Flux towers  -  Global carbon cycle  -  Gross primary productivity  -  Gross primary productivity product  -  Mann kendall trend test  -  Mann-Kendall trends  -  Trend tests

Classification code: 103 Biology  -  204.4 Glass  -  402.4 Towers  -  483.1 Soils and Soil Mechanics  -  731.1 Control Systems  -  804 Chemical Products  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.1 Woodlands and Forestry  -  1502.1.2 Climate Change  -  1502.2 Ecology and Ecosystems

Numerical data indexing: Mass 2.23E-01kg, Mass 6.783E-01kg, Percentage 4.52E+01%, Percentage 7.24E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.036

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

36. Design and Experiment of Automatic Row-following System for Tobacco Harvester Based on Dynamic Region of Interest

Accession number: 20260720049675

Title of translation: 基于动态兴趣空间的烟草收获机自动对行系统 设计与试验

Authors: Wang, Xiaole (1, 2); Dai, Baobao (1); Dai, Zhen (1); Hu, Zhiwei (1); Li, Yuxuan (1); Zhao, Jinhui (3); Yang, Yang (1, 2); Chen, Liqing (1, 2)

Author affiliation: (1) School of Engineering, Anhui Agricultural University, Hefei; 230036, China; (2) Anhui Provincial Engineering Research Center of Intelligent Agricultural Machinery, Hefei; 230036, China; (3) Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing; 100083, China

Corresponding author: Yang, Yang(yy2016@ahau.edu.cn)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 50-61

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the problems as multiple interference factors, and long computation time in processing field information using current radar perception, an automatic alignment system that combined laser radar and Beidou positioning for tobacco harvesters. The control algorithm fit the point cloud processing centerline based on the historical positioning coordinates of the aircraft body, effectively solving problems such as deviate guide lines and misalignment caused by aircraft body deviation. Based on the collected point cloud information of tobacco plants, the current row spacing and plant height of the field were calculated as the decision basis for extracting the region of interest (ROI). To shorten the processing time of point clouds, the length, width, and height range of ROI space were dynamically adjusted, and interference point clouds were filtered out. A crop row classification method was proposed based on point cloud density, and the initial clustering center of K-means algorithm was determined through vertical projection and sliding window method to improve the accuracy of tobacco row navigation line fitting. The optimal preview algorithm was used to track and drive the obtained forward tobacco navigation line. Automatic parallel testing was conducted in three tobacco fields with different row spacing. The maximum lateral error between the center of the machine and the actual centerline of the tobacco row was 0.107 m, with an average lateral error of 0.074 m. The accuracy of the harvest navigation line was 94.8%, indicating that the system can effectively ensure automatic parallel driving of the harvester. The proposed dynamic ROI point cloud processing algorithm reduced the average point cloud processing time from 536.2 ms to 148.95 ms compared with existing algorithms. The tobacco harvester automatic alignment system and dynamic ROI point cloud processing algorithm proposed can provide technical references for unmanned autonomous operation of field planting crop equipment. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Tobacco

Controlled terms: Alignment  -  Clustering algorithms  -  Crops  -  Fighter aircraft  -  Harvesters  -  Optimization  -  Radio navigation

Uncontrolled terms: Automatic row-following travel  -  Cloud processing  -  Dynamic region  -  Dynamic region of interest point cloud  -  Optimal preview algorithm  -  Point-clouds  -  Region-of-interest  -  Regions of interest  -  Row following  -  Tobacco harvesters

Classification code: 435.1 Navigation  -  601.1 Mechanical Devices  -  652.1.2 Military Aircraft  -  716.3 Radio Systems and Equipment  -  821.2 Agricultural Machinery and Equipment  -  821.5 Agricultural Products  -  903.1 Information Sources and Analysis  -  1201.7 Optimization Techniques

Numerical data indexing: Percentage 9.48E+01%, Size 1.07E-01m, Size 7.40E-02m, Time 5.362E-01s to 1.4895E-01s

DOI: 10.6041/j.issn.1000-1298.2026.04.006

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

37. Analysis of Uncertainties and Identification of Impact Factors of Unbalances of Water Supplies and Water Demands under Extreme Dry Years

Accession number: 20260720049670

Title of translation: 极端枯水下供需水失衡驱动要素识别与不确定性分析

Authors: Wang, Youzhi (1, 2); Liu, Shufang (1, 2); Han, Jinxu (1, 2); Luo, Yun (1, 2); Li, Qiangkun (1, 2)

Author affiliation: (1) Yellow River Institute of Hydraulic Research, Yellow River Conservancy Commission, Zhengzhou; 450003, China; (2) Yellow River Laboratory, Zhengzhou; 450003, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 391-398

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to identify impact factors of unbalances of water supplies and water demand (referred to WSD) of Yellow River Basin under extreme dry years to support water resources management, the WSD was measured by ranges and depth of WSD. Besides, responses of WSD on metro-hydrological elements, economic and society, reservoir regulation, ecology and environments were explored by the principal component analysis method (PCA). Moreover, uncertainties of surface water supplies and discharges of reservoirs were measured by stochastic functions that were verified by Kolmogorov Smirnov test (KS) and augmented dickey fuller (AD) approaches. The influences of single and interactive parameters on WSD were studied by three-level factors method. The results showed that WSD of Yellow River Basin ranged from medium, relatively high and high degree. Surface water supplies and discharges of reservoirs had the most impacts on WSD and explanation rate reached about 55.055%. Xiaolangdi reservoir had the biggest impact on WSD, followed by surface water supplies and Wanjiazhai reservoir. These results could identify key impact factors of WSD under interactions among hydrometeorology. socioeconomics, reservoir operation and ecol ogical environment. Besides, it could explore impacts of uncertainties on WSD, supporting water resources management of Huanghe River. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Principal component analysis

Controlled terms: Economics  -  Reservoir management  -  Reservoirs (water)  -  Rivers  -  Stochastic systems  -  Uncertainty analysis  -  Water resources exploration

Uncontrolled terms: ‘Dry’ [  -  Extreme dry year  -  Imbalance between water supply and water demand  -  Principal-component analysis  -  Sensitive analysis  -  Surface water supply  -  Uncertainty  -  Water demand  -  Water-supply demand  -  Yellow River basin

Classification code: 407 Maritime and Port Structures; Rivers and Other Waterways  -  407.1.1 Hydrotechnical Engineering Structures  -  441.2 Reservoirs  -  444 Water Resources  -  512.1.2 Petroleum Development Operations  -  971 Social Sciences  -  1101.2 Machine Learning  -  1202.1 Probability Theory

Numerical data indexing: Percentage 5.5055E+01%

DOI: 10.6041/j.issn.1000-1298.2026.04.038

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

38. Design and Experiment of Online Lint Cotton Moisture Regain Detection Device Based on Resistance Method

Accession number: 20260720049662

Title of translation: 基于电阻法的皮棉回潮率在线检测装置设计与试验

Authors: Xu, Jiankang (1, 2); Wang, Peiyu (1, 2); Zhang, Ruoyu (1, 2); Qian, Yifu (1, 2); Fang, Liang (1, 2); Chang, Jinqiang (1, 3); Liu, Zunyan (4)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China; (3) Technology Innovation Center of Smart Farm Digital Equipment, Xinjiang Production and Construction Corps, Shihezi; 832003, China; (4) Technology Innovation Center of Inspection and Testing Technology of Cotton and Its Products, State Administration for Market Regulation, Tumushuke; 843900, China

Corresponding author: Zhang, Ruoyu(ry248@163.com)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 97-107

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the challenges of quantitative sampling under negative pressure, low real-time detection accuracy of moisture content, and poor stability during the cotton processing, an online moisture content detection device for lint cotton was developed based on the resistance method. A novel online detection method, combining “dynamic quantitative sampling—weight constant pressure measuremen—multi-parameter compensation was proposed. Key components, including a flip-type sampling mechanism and weight detection system, were designed to achieve stable sampling and continuous detection of lint cotton in a high-speed flow state. Based on the electrical resistance characteristics of lint cotton and environmental temperature and humidity data, a multi-parameter moisture content prediction model was constructed. After comparing various algorithms, the random forest model was identified as the most accurate predictor, with a coefficient of determination (R2) of 0.98 and a root mean square error (RMSE) of 0.22%. Performance validation tests showed that the average deviation between the proposed online detection device and the standard measurement instrument was 0.1%, with an average detection time of 23. 4 s per sample. The impact of sample weight on the moisture content measurement results was weak (Pearson correlation coefficient was 0.47). The experimental results demonstrated that the device offered high detection accuracy and good stability, meeting the real-time and accuracy requirements for moisture content detection in cotton processing. This device can provide reliable technical support for intelligent regulation and quality traceability in the cotton processing industry. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Mean square error

Controlled terms: Correlation methods  -  Cotton  -  Moisture  -  Sampling  -  Signal detection

Uncontrolled terms: %moisture  -  Content detection  -  Cotton processing  -  Detection accuracy  -  Detection device  -  Lint cotton  -  Multiparameters  -  On-line detection  -  Quantitative sampling  -  Resistance method

Classification code: 716.1 Information Theory and Signal Processing  -  821.5 Agricultural Products  -  941.6 Moisture Measurements  -  1202 Statistical Methods  -  1202.2 Mathematical Statistics

Numerical data indexing: Percentage 1.00E-01%, Percentage 2.20E-01%, Time 4.00E+00s

DOI: 10.6041/j.issn.1000-1298.2026.04.010

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

39. Design and Experiment of Vibration Energy Harvesting Device for High-horsepower Tractors

Accession number: 20260720049705

Title of translation: 大功率拖拉机振动能量收集装置设计与试验

Authors: Yao, Yanchun (1, 2); Xiu, Weijia (1); Jia, Longfei (1); Wu, Jida (1, 3); Geng, Duanyang (1, 3); Li, Yongsheng (4)

Author affiliation: (1) College of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo; 255049, China; (2) Institute of Modern Agricultural Equipment, Shandong University of Technology, Zibo; 255049, China; (3) Shandong Province Field Crop Intelligent Agricultural Technology and Intelligent Agricultural Machinery Equipment Primary Laboratory, Zibo; 255049, China; (4) Research Institute of Agricultural Machinery and Equipment, Shandong Wuzheng Group, Jining; 272111, China

Corresponding author: Geng, Duanyang(dygxt@sdut.edu.en)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 415-426

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Agricultural equipment in the field operation process continues to produce mechanical vibration, capture its vibration energy and realize agricultural machinery self-power supply is of practical significance. For the application of vibration energy harvesting device can’t match the external excitation or mechanical structure vibration frequency, energy harvesting efficiency is low, a resonance frequency adjustable piezoelectric-electromagnetic coupling vibration energy harvesting device was designed, combining the use of bicrystalline piezoelectric cantilever beam structure, and the combination of electromagnetic induction and piezoelectric effect, to achieve the resonance frequency adjustable from 14.8 Hz to 31.0 Hz, and to broaden the bandwidth of the vibration energy harvesting. Based on Hamilton’s principle, an electromechanical coupling mathematical model was established, which revealed the regulation mechanism of the resonant frequency of the system. Through indoor experiments, the effects of different load resistances, excitation acceleration, excitation frequency, and magnetic distance on the power generation performance were investigated, and the optimal load resistance configurations and resonant frequencies under different magnetic distances were determined. Field tests were carried out by using EH2604 high power tractor to study the power generation performance of the vibration energy recovery device under the soil surface of farmland. The results showed that when the optimal load resistances for the cantilever piezoelectric patch, electromagnetic coil, and bending piezoelectric transducer were 850 ΚΩ, 990 Ω, and 300 ΚΩ, respectively, and the optimal magnetic distance was 53 mm, the vibration energy output power peaked. The device can effectively collect vibration energy under different magnetic distances and vehicle speeds, and the output power tended to increase with the increase of vehicle speed, and the magnetic distance was 38 mm, and the maximum output power was 25.97 µW at a vehicle speed of 12 km/h. The research result can provide technical solutions and ideas for the development of self-supply energy system of agricultural machinery for reference. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Natural frequencies

Controlled terms: Acceleration  -  Agriculture  -  Couplings  -  Electric excitation  -  Electromagnetic coupling  -  Electromagnetic induction  -  Electromechanical coupling  -  Energy efficiency  -  Energy harvesting  -  Mechanical efficiency   -  Piezoelectric transducers  -  Soils  -  Tractors (agricultural)  -  Tractors (truck)  -  Vibrations (mechanical)

Uncontrolled terms: Electromagnetics  -  High power  -  High power tractor  -  Magnetic distances  -  Piezoelectric  -  Piezoelectric-electromagnetic coupling  -  Tunable resonant frequency  -  Tunables  -  Vibration energy harvesting  -  Vibration energy harvesting device

Classification code: 483.1 Soils and Soil Mechanics  -  601.2 Machine Components  -  602.1 Mechanical Drives  -  663.1 Heavy Duty Motor Vehicles  -  701.1 Electricity: Basic Concepts and Phenomena  -  701.2 Magnetism: Basic Concepts and Phenomena  -  703 Electric Circuits  -  731.1 Control Systems  -  752.1 Acoustic Devices  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.2 Agricultural Machinery and Equipment  -  1009 Energy Management  -  1301.1.1 Mechanics  -  1301.1.4 Quantum Theory; Quantum Mechanics

Numerical data indexing: Electrical resistance 9.90E+02Ohm, Frequency 1.48E+01Hz to 3.10E+01Hz, Size 1.20E+04m, Size 3.80E-02m, Size 5.30E-02m

DOI: 10.6041/j.issn.1000-1298.2026.04.041

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

40. Design and Experiment of Automatic Detection System for Soil Available Nitrogen, Phosphorus and Potassium

Accession number: 20260720049688

Title of translation: 土壤速效氮磷钾自动检测系统设计与试验

Authors: Yao, Yetong (1, 2); Wang, Jun (1, 2); Dong, Wanjing (1, 2); Tian, Yiwei (1, 2); Zhang, Yang (1, 2); Ding, Youchun (1, 2)

Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key Laboratory of Agricultural Equipment in Mid-lower Yangtze River, Ministry of Agriculture and Rural Affairs, Wuhan; 430070, China

Corresponding author: Ding, Youchun(kingbug163@163.com)

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 355-368 and 398

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issues of low efficiency and insufficient automation in traditional soil available nitrogen, phosphorus and potassium (NPK) content detection, as well as the limited path planning and tracking performance of vehicle-mounted detection equipment in complex farmland environments, an autonomous detection system for soil available NPK in field empowered by an unmanned operation platform was established. It integrated Beidou positioning and a four-wheel drive steering platform, optimized sensor detection models, designed a hierarchical-adaptive traversal path planning method for fertilizer-measuring points and a path tracking control algorithm based on genetic algorithm (GA)optimized linear quadratic regulator (LQR), and built an autonomous fertilizer detection system with cloud-edge architecture. For in-situ, rapid detection of soil fertility indicators, random forest (RF) prediction mode was selected as the optimal algorithm after comparing four machine learning models. Its relative prediction errors for available N, P and K were below 16.44%, 19.26% and 13.91%, respectively, with an average 49.46% accuracy improvement over the direct measurement accuracy of sensors without prior modeling. To accurately characterize the spatial distribution of field-scale fertility indicators, the optimal detection point spacing was determined by quantifying the Christiansen uniformity coefficient (CUC) across different sampling densities; three continuous traversal path planning schemes-comb path (CP), comb cross-row path (CCP), and comb fifth-order Bézier path (CFBP)—were designed for flat obstacle-free, large-obstacle, and small-obstacle farmland environments, respectively. Simulation tests showed that the GALQR controller improved the platform’s path tracking accuracy by an average of 24.32%, with maximum absolute lateral deviation and heading angle of 1.71 cm and 1.69°, respectively. Field tests demonstrated that under straight path tracking, the GA — LQR algorithm reduced the maximum absolute lateral deviation, maximum absolute heading angle, average absolute parking error at detection points, and total detection time by 15.62%, 19.59%, 20.79%, and 13.43%, respectively, compared with the conventional LQR algorithm; under curved path tracking, the corresponding indicators were decreased by 19.28%, 27.34%, 22.94%, and 15.76%. Additionally, the optimized algorithm shortened the detection time per hectare by 927 s, reduced the single-point detection process by 6.28 s, and improved the positioning and detection accuracy by an average of 14.26%. The research result can provide a reference for the autonomy, informatization, and intelligentization of soil available NPK content information acquisition. © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Motion planning

Controlled terms: Agricultural machinery  -  All wheel drive vehicles  -  Errors  -  Farms  -  Four wheel steering  -  Learning algorithms  -  Machine learning  -  Navigation  -  Nitrogen fertilizers  -  Phosphorus   -  Potassium  -  Simulation platform  -  Soil surveys  -  Three term control systems  -  Vehicle detection  -  Vehicle locating systems

Uncontrolled terms: Automatic Detection  -  Available nitrogen  -  Available phosphorus  -  Path tracking  -  Path tracking control  -  Phosphorus and potassium  -  Prediction modelling  -  Random forest prediction modeling  -  Random forests  -  Soil available nitrogen

Classification code: 202.9.1 Alkali Metals  -  405.3 Surveying  -  435.1 Navigation  -  435.2 Tracking and Positioning  -  483.1 Soils and Soil Mechanics  -  662.1 Automobiles  -  662.3 Automobile Components and Materials  -  731.1 Control Systems  -  731.1.1 Error Handling  -  804 Chemical Products  -  821 Agricultural Equipment and Methods; Vegetation and Pest Control  -  821.2 Agricultural Machinery and Equipment  -  821.3 Agricultural Chemicals  -  1101 Artificial Intelligence  -  1101.2 Machine Learning  -  1106.3.1 Image Processing  -  1201.12 Modeling and Simulation

Numerical data indexing: Percentage 1.343E+01%, Percentage 1.391E+01%, Percentage 1.426E+01%, Percentage 1.562E+01%, Percentage 1.576E+01%, Percentage 1.644E+01%, Percentage 1.926E+01%, Percentage 1.928E+01%, Percentage 1.959E+01%, Percentage 2.079E+01%, Percentage 2.294E+01%, Percentage 2.432E+01%, Percentage 2.734E+01%, Percentage 4.946E+01%, Size 1.71E-02m, Time 6.28E+00s, Time 9.27E+02s

DOI: 10.6041/j.issn.1000-1298.2026.04.035

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.

41. Mechanistic Insights into Phosphorylation-mediated Apoptosis and Proteolysis of Myofibrillar Proteins in Postmortem Muscle

Accession number: 20260720049700

Title of translation: 宰后成熟期间蛋白质磷酸化对细胞凋亡和肌原纤维蛋白降解的影响机制研究

Authors: Zhang, Jiaying (1); Lei, Qing (1); Song, Shu’nan (1); Li, Conghui (1); Ge, Wupeng (1)

Author affiliation: (1) College of Food Science and Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China

Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Abbreviated source title: Nongye Jixie Xuebao

Volume: 57

Issue: 4

Issue date: February 2026

Publication year: 2026

Pages: 407-414

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to investigate the effect mechanism of protein phosphorylation on apoptosis and myofibrillar protein degradation during maturation, psoas major (PM) muscles injected with protein kinase A (PKA) and alkaline phosphatase (AP) ware used as the experiment subjects. Mitochondrial dysfunction, apoptosis, myofiber type and the degradation of myofibrillar protein were measured and analyzed. The results showed that the AP group had higher mitochondrial membrane permeability, cytochrome e (Cytc) oxidation level, and caspase activity at 12~72 h postmortem compared with both the PKA and control groups (P © 2026 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 33

Main heading: Phosphorylation

Controlled terms: Antigen-antibody reactions  -  Cell death  -  Cell membranes  -  Degradation  -  Mitochondria  -  Muscle

Uncontrolled terms: ALkaline phosphatase  -  Caspases  -  Mitochondrial dysfunction  -  Myofiber type  -  Myofibers  -  Myofibrillar protein degradation  -  Myofibrillar proteins  -  Protein degradation  -  Protein kinase A  -  Psoas major

Classification code: 101.3 Tissue Engineering  -  103 Biology  -  103.2 Immunology  -  203 Biomaterials  -  802.2 Chemical Reactions

Numerical data indexing: Size -7.62E-02m, Time 1.728E+05s, Time 2.16E+04s, Time 4.32E+04s to 2.592E+05s, Time 4.32E+04s, Time 7.20E+03s to 1.728E+05s, Time 7.20E+03s to 2.592E+05s

DOI: 10.6041/j.issn.1000-1298.2026.04.040

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

Compilation and indexing terms, Copyright 2026 Elsevier Inc.