2025年第12期

2025年第12期

2025年第12期共收录75篇

1. Design and Test of Anti-instability System of Hilly and Mountain Track Agricultural Machinery Transfer Platform

Accession number: 20255119744958

Title of translation: 丘陵山地轨道农机具转运平台防失稳系统设计与试验

Authors: Xiao, Maohua (1); Ding, Jiachen (1); Zhu, Yejun (1); Ke, Wentao (1); Xie, Chenshuo (1); Wang, Jiabo (2); Shi, Haoqi (3)

Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Jiangsu Vocational College of Agriculture and Forestry, Zhenjiang; 212400, China; (3) China Europe Engineering College, Shanghai University, Shanghai; 200444, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: 2025

Publication year: 2025

Pages: 170-179

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Hilly and mountainous regions are characterized by complex terrain and agricultural machinery with high centers of gravity, which often leads to instability and rollover during rail transport operations. To address this challenge, a hydraulic automatic leveling anti-instability system for a mountain rail transport platform was proposed. The system integrated an ADXL345 triaxial accelerometer for real-time attitude monitoring and employed a particle swarm optimization fuzzy PID (PSO Fuzzy – PID) controller, using the platform’s Z-axis tilt angle as the feedback variable. A simulation model was established in Simulink to compare the performance of conventional PID, fuzzy PID, and PSO Fuzzy — PID controllers. Simulation results demonstrated that the PSO Fuzzy — PID controller achieved a rapid response time of 0. 181 s with zero overshoot, and outperformed conventional PID and fuzzy PID controllers in terms of adjustment time, stability, and overall dynamic response. Static experimental tests were conducted under track inclinations of 4°, 7°, and 10°, and the PSO Fuzzy — PID controller yielded an average leveling error standard deviation of only 0.068°, with maximum error constrained within 0.45°. The average leveling time was reduced by approximately 6.3% and 15.6% compared with that of fuzzy PID and conventional PID, respectively. Dynamic experiments further revealed that the system maintained a response delay below 0.4 s, with platform attitude fluctuations confined to - 0.079° to 0.497°, thereby meeting the precise leveling requirement within ±10°. These results confirmed the effectiveness and reliability of the proposed PSO Fuzzy — PID based hydraulic leveling system. The system significantly enhanced the operational stability and safety of agricultural machinery transport on hilly rail platforms, providing valuable technical support for the intelligent development and practical application of agricultural transport equipment in mountainous regions. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Particle swarm optimization (PSO)

Controlled terms: Agricultural machinery? - ?Agriculture? - ?Controllers? - ?Electric control equipment? - ?Hydraulic machinery? - ?Leveling (machinery)? - ?Proportional control systems? - ?Railroad transportation? - ?Simulation platform? - ?System stability

Uncontrolled terms: Agricultural machinery transfer platform? - ?Automatic leveling? - ?Fuzzy PID controller? - ?Fuzzy-PID? - ?Hilly and mountainous rail transportation? - ?Hydraulic automatic leveling? - ?Levelings? - ?Mountainous regions? - ?Particle swarm optimization algorithm? - ?Rail transportation

Classification code: 433 Rail Transportation? - ?704.2 Electric Equipment? - ?731.1 Control Systems? - ?732.1 Control Equipment? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?961 Systems Science? - ?1106 Computer Software, Data Handling and Applications? - ?1201.7 Optimization Techniques? - ?1201.12 Modeling and Simulation? - ?1401.2 Hydraulic Equipment and Machinery

Numerical data indexing: Percentage 1.56E+01%, Percentage 6.30E+00%, Time 1.81E+02s, Time 4.00E-01s

DOI: 10.6041/j.issn.1000-1298.2025.12.015

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

2. Lightweight Cattle Face Recognition Algorithm Based on Multi-scale Fusion Network

Accession number: 20255119744949

Title of translation: 基于多尺度融合网络的轻量化牛脸识别算法

Authors: Qi, Yongsheng (1, 2); Quan, Jiale (1); Luan, Haotian (1); Liu, Liqiang (1, 2); Liu, Huiwen (1, 2)

Author affiliation: (1) School of Electric Power, Inner Mongolia University of Technology, Hohhot; 010080, China; (2) Center for Intelligent Energy Technology and Equipment Engineering, Hohhot; 010080, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: 2025

Publication year: 2025

Pages: 615-622 and 644

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In intelligent cattle farming, the application of facial recognition technology for cattle is crucial. However, due to the complex and variable farming environment and the non-planar characteristics of cattle faces, facial recognition technology often faces challenges such as insufficient recognition accuracy and poor robustness in practical applications. To address these issues, a FaceNet based on multi-scale fusion network (FMF) was proposed, which identified cattle through facial features. Firstly, the MSRCR method was used for color restoration preprocessing of the input cattle face images to reduce the impact of lighting on the FMF algorithm. Subsequently, a more lightweight MobileNet V3 was introduced into the main feature extraction network to reduce the model parameters and computation while ensuring high feature extraction capability. Finally, a composite dual-branch adaptive attention mechanism (M_CBAM) was proposed for multi-scale feature fusion. M_CBAM adjusted the weighting coefficients based on important features of the feature maps, adaptively weighting serial CBAM and parallel CBAM weights, then performed multi-scale feature fusion of local fine features and global features of cattle faces, improving facial recognition accuracy. To explore the effectiveness and real-time performance of the proposed algorithm, ablation experiments were conducted on a self-made cattle face dataset, and the results were compared with current mainstream recognition algorithms. Finally, the algorithm was deployed on the Jetson AGX Xavier embedded platform for application testing. The test results showed that the proposed algorithm achieved an accuracy of 93. 86% and an FPS of 30. 02 f/s on an open test set collected from other dairy farms. Under the condition of fast model inference speed, the recognition accuracy was significantly better than that of the original network and comparison networks. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Feature extraction

Controlled terms: Agriculture? - ?Extraction? - ?Face recognition? - ?Fighter aircraft? - ?Scales (weighing instruments)

Uncontrolled terms: Attention mechanisms? - ?Cattles? - ?Cow face recognition? - ?Facenet? - ?Facial recognition? - ?Features extraction? - ?Features fusions? - ?Multi-scale features? - ?Multiscale fusion? - ?Recognition accuracy

Classification code: 652.1.2 Military Aircraft? - ?802.3 Chemical Operations? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?942.1.7 Special Purpose Instruments? - ?1101.2 Machine Learning? - ?1106.8 Computer Vision

Numerical data indexing: Percentage 8.60E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.056

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

3. Design and Experiment of Rotary-cut Combined Type Deep Fertilization Device for Rapeseed Direct Seeding Strip

Accession number: 20255119745609

Title of translation: 油菜直播播种带旋切组合深施肥装置设计与试验

Authors: Xiao, Wenli (1, 2); Liao, Qingxi (1, 2); Liao, Yitao (1, 2); Wang, Xufeng (3); Shan, Yiyin (1); Du, Wenbin (1)

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; (3) College of Mechanical and Electronic Engineering, Tarim University, Alar; 843300, China

Corresponding author: Liao, Qingxi(liaoqx@mail.hzau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 223-234

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the fact that a large amount of straw and sticky soil of oilseed rape direct seeding in the middle and lower reaches of the Yangtze River, from the perspective of combining oilseed rape seedbed preparation and deep fertilizer application operation, a preparation method of seedbed with the whole width of the compartment shallowly rotated and the seeding belt rotated and cut for deep loosening and deep application of fertilizer was proposed, and a rotary-cutting combined deep fertilizer application device was designed. Based on the characteristics of rice root distribution in the previous crop in the tillage layer, combined with the root growth characteristics of rapeseed plants, the fertilizer depth of 100 ~ 150 mm and the deep loosening depth of 200 mm were determined; based on the kinetic analysis of the stubble cutting and breaking disc to cut off the stubble force, and the notch slip-cutting curves were qualitatively analyzed, the radius of the disc, the angle of the slip-cutting and the number of the notches were determined; based on the plowing depth, key parameters of the deep loosening and breaking shovels were determined; and the key parameters of the rotary-cutting and breaking shovel were determined through the single disturbed area, and the row spacing of rotary-cutting combined deep fertilizer application device was obtained. Using discrete element software to simulate the operational performance of a rotary-cutting combined deep fertilizer application device, the results showed that when the fertilizer depth was 150 mm, the seed bed belt was reasonably constructed, and the straw was evenly mixed and buried. The fertilizer depth was 156.60 mm, with a depth stability coefficient of 87.46%, and a uniformity coefficient of 13.18%. The field performance test showed that when the fertilizer depth was 150 mm, the stubble burying rate was 86.65%; the plowing depth of the seed bed belt and non-seed bed belt was 191.17 mm and 112.50 mm, respectively; the stability coefficient of plowing depth was 90.70% and 91.18%, respectively; the actual fertilizer depth was 149.44 mm, and the qualified rate of fertilizer depth was 85.80%. The field sowing test showed that when the fertilizer depth was 150 mm, the actual fertilizer depth was 151.56 mm, the qualified rate of fertilizer depth was 85.83%, the coefficient of variation of fertilizer uniformity was 14.33%, and the seedling emergence rate under the treatment of rotary-cutting combined deep fertilizer device was 88.97%, which was higher than that of rotary-tillage mixed fertilizer and rotary-tillage without fertilizer, and the length of the main root in the flowering stage was increased by 22.24% and 38.26%, the diameter of the main root neck was increased by 0.60% and 3.57%, and rapeseed yield was increased by 14.02% and 37.50%, respectively. The results showed that the rotary-cutting combined deep fertilization device provided a suitable seedbed strip and fertilization effect for the growth of oilseed rape, which could provide a reference for the preparation of seedbed and deep fertilization for mechanized direct seeding of oilseed rape. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Oilseeds

Controlled terms: Agricultural machinery? - ?Application programs? - ?Crops? - ?Cultivation? - ?Cutting? - ?Fertilizers? - ?Plants (botany)? - ?Shovels? - ?Soil testing? - ?Soils

Uncontrolled terms: Breakings? - ?Construction of seeding belt? - ?Deep fertilization? - ?Direct seeder? - ?Direct-seeding? - ?Fertilisation? - ?Fertilizer applications? - ?Oil seed rape? - ?Rapeseed? - ?Rotary-cut combined

Classification code: 103 Biology? - ?483.1 Soils and Soil Mechanics? - ?604.1 Metal Cutting? - ?605.2 Small Tools, Unpowered? - ?821.2 Agricultural Machinery and Equipment? - ?821.3 Agricultural Chemicals? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1106 Computer Software, Data Handling and Applications? - ?1502.1.1.3 Soil Pollution? - ?1502.1.1.4.3 Soil Pollution Control

Numerical data indexing: Percentage 1.318E+01%, Percentage 1.402E+01%, Percentage 1.433E+01%, Percentage 2.224E+01%, Percentage 3.57E+00%, Percentage 3.75E+01%, Percentage 3.826E+01%, Percentage 6.00E-01%, Percentage 8.583E+01%, Percentage 8.58E+01%, Percentage 8.665E+01%, Percentage 8.746E+01%, Percentage 8.897E+01%, Percentage 9.07E+01%, Percentage 9.118E+01%, Size 1.00E-01m to 1.50E-01m, Size 1.125E-01m, Size 1.4944E-01m, Size 1.50E-01m, Size 1.5156E-01m, Size 1.566E-01m, Size 1.9117E-01m, Size 2.00E-01m

DOI: 10.6041/j.issn.1000-1298.2025.12.020

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

4. Characterization Extraction and Classification of Pleurotus eryngii Based on FCML - YOLO v8

Accession number: 20255119745598

Title of translation: 基于 FCML-YOLO v8 的杏鲍菇表征提取与分级方法

Authors: Xie, Limin (1, 2); Wu, Haoyu (3); Jing, Jun (1); Ye, Dapeng (1, 2); Fang, Bing (1, 2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou; 350002, China; (2) Fujian Key Laboratory of Agricultural Information Sensoring Technology, Fuzhou; 350002, China; (3) School of Future Technology, Fujian Agriculture and Forestry University, Fuzhou; 350002, China

Corresponding author: Fang, Bing(fangbing008@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 534-545

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Addressing the challenges of apricot mushroom grading, which relies heavily on manual labor, is inefficient, and prone to subjectivity. An automated grading and detection method for apricot mushrooms named FCML - YOLO v8 was proposed. Building upon the improved YOLO v8n - seg, the network sequentially integrated the feature-focused diffusion pyramid network (FDPN), characteristic attention fusion module (CAFM), and multi-level channel attention (MLCA) mechanism. By combining the FCML - YOLO v8 model with subordinate judgment, mask merging, and center screening methods, accurate assessments of apricot mushroom size and disease spot conditions was achieved. Additionally, through image refinement and curve-fitting techniques, it effectively quantified the curvature of apricot mushrooms. Furthermore, by leveraging CIE XYZ color space values, the color characteristics of apricot mushrooms were precisely analyzed. By integrating these four indicators, the automated grading and detection of apricot mushrooms were successfully implemented. Experimental results demonstrated that the FCML - YOLO v8 model achieved a precision of 94.41%, a recall rate of 88.48%, and an mAP@ 0.5 of 92.04% in bounding box prediction. In mask detection, it achieved a precision of 90.52%, a recall rate of 84.14%, and an mAP@ 0.5 of 86.79%. Compared with the original YOLO v8n - seg model, the mAP @ 0.5 of FCML - YOLO v8 was improved by 6.39 and 4.79 percentage points, respectively, in bounding box prediction and mask detection. In the constructed apricot mushroom grading and detection experimental setup, the FCML - YOLO v8 model achieved an mAP@ 0.5 of 92.98%, fully meeting the requirements of industrial-grade applications. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 33

Main heading: Deep learning

Controlled terms: Computer vision? - ?Curve fitting? - ?Diagnosis? - ?Fungi? - ?Grading? - ?Masks? - ?Selenium compounds

Uncontrolled terms: Automated detection? - ?Automated grading? - ?Characterization extraction? - ?Deep learning? - ?Grading methods? - ?Machine-vision? - ?Pleurotu eryngi? - ?Pleurotus? - ?Recall rate? - ?Targets detection

Classification code: 102.1 Medicine? - ?103 Biology? - ?103.1 Microbiology? - ?202.9.3 Others, including Bismuth, Boron, Cadmium, Cobalt, Mercury, Niobium, Selenium, Silicon, Tellurium and Zirconium? - ?714.2 Semiconductor Devices and Integrated Circuits? - ?804.2 Inorganic Compounds? - ?1101.2.1 Deep Learning? - ?1106.8 Computer Vision? - ?1201.9 Numerical Methods

Numerical data indexing: Percentage 8.414E+01%, Percentage 8.679E+01%, Percentage 8.848E+01%, Percentage 9.052E+01%, Percentage 9.204E+01%, Percentage 9.298E+01%, Percentage 9.441E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.049

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

5. Spatio-temporal Patterns and Influencing Factors of Coupling Coordination in Human-Land-Water Systems of Yellow River Basin

Accession number: 20255119745658

Title of translation: 黄河流域人-地-水系统耦合协调时空格局与影响因素

Authors: Xie, Xiaotong (1); Chen, Songhui (1); Li, Yingchao (1); He, Weikang (1); Li, Xiaoshun (2)

Author affiliation: (1) College of Resources and Environment, Henan Agricultural University, Zhengzhou; 450046, China; (2) School of Public Administration, China University of Mining and Technology, Xuzhou; 221116, China

Corresponding author: Li, Yingchao(yeli666@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 425-435

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The human-land-water systems within a river basin are interconnected and exhibit mutually reinforcing relationships. Investigating their coupling coordination degree and influencing factors is crucial for achieving regional high-quality development and ecological civilization construction. Taking the nine provinces in the Yellow River Basin as the study area, the entropy method and a comprehensive evaluation method were employed to measure the index levels of the human system, land system, and water system within the Yellow River Basin from 2013 to 2022. Building upon this foundation, the coupling coordination degree model and fixed effects (FE) model were utilized to analyze and evaluate the spatio-temporal differentiation characteristics of the human-land-water systems coupling coordination degree and its influencing factors at both dual (human-land, human-water, land-water) and ternary (human-land-water) levels. The results indicated that from 2013 to 2022, the overall human-land-water systems in the nine provinces showed steady progress, although the development speeds of the subsystems varied, mostly exhibiting a fluctuating upward trend. Significant spatial disparities existed in the coupling coordination degree across the nine provinces during 2013-2022. By 2022, five provinces (Inner Mongolia, Ningxia, Shanxi, Henan, Shandong) reached an intermediate coordination level, while the other four provinces still had considerable room for development. The coupling coordination degrees of the dual systems (human-land, human-water, land-water) in all provinces also generally showed a year-by-year strengthening trend. Technological investment and rural governance investment positively influenced the coupling coordination degree. Industrial structure upgrading, the degree of openness, fixed asset investment, and government regulatory capacity exerted varying degrees of influence on the coupling coordination degree. In conclusion, against the backdrop of advancing the major national strategy for ecological protection and high-quality development in the Yellow River Basin, differentiated pathways for synergistic human-land-water development should be formulated for the upper, middle, and lower reaches. This would facilitate the rational coordination of multi-system development relationships within the basin and promote healthy and sustainable regional development in the future. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 37

Main heading: Watersheds

Controlled terms: Ecology? - ?Investments? - ?Regional planning? - ?Rivers

Uncontrolled terms: Coordination degree? - ?Coupling coordination degree? - ?High quality? - ?Human-water, land-water-water system? - ?Influence factor? - ?River basins? - ?Spatiotemporal patterns? - ?Water system? - ?Water-water? - ?Yellow River basin

Classification code: 403.2 Regional Planning and Development? - ?407 Maritime and Port Structures; Rivers and Other Waterways? - ?911.2 Industrial Economics? - ?1502.2 Ecology and Ecosystems? - ?1502.3 Hydrology

DOI: 10.6041/j.issn.1000-1298.2025.12.039

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

6. Investigation of Characteristics and Assembly Mechanisms of Bacterial Community Structure in Sediments of the Second Drainage Ditch in Yinchuan City

Accession number: 20255119731906

Title of translation: 银川市第二排水沟沉积物细菌群落结构特征与构建机制研究

Authors: Xu, Cheng (1); Wei, Zeyu (1); Qiu, Xiaocong (2); Fu, Yongliang (1); Wang, Chuyou (1); Dong, Juniin (1); Zhao, Zengfeng (1)

Author affiliation: (1) School of Civil and Hjdraulic Engineering, Ningxia Vniversity, Yinchuan; 750021, China; (2) School of Life Science, Ningxia University, Yinchuan; 750021, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 738-749

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: High-throughput sequenoing teohnology, non-metric multidimensional soaling (NMDS), neutral Community model (NCM) and structural equation modelling (SEM) were used to analyze Sediment physico chemical properties, bacterial structural features, Community assembly,and driving mechanisms in order to examine the bacterial Community structure characteristics and Community assembly processes of Sediments in the Second Drainage Channel of Yinchuan City. The findings indicated that whereas total nitrogen (T N) and ammonium nitrogen (N H 4 - N) concentrations did not substantially correlate with a-diversity indices, electrical conductivity (E C) did considerably positively correlate with Chaol, Observed, Shannon, and Simpson diversity indices. Thiobacillus, Bacteroidetes_vadinHAll , and Dechloromonas were the major genera in the bacterial phyla Proteobacteria and Desulfobacterota. Results from PER — SIMPER, DNCI, and the NCM model consistently showed that stochastic processes dominated the bacterial Community assembly between August 2021 and August 2022. EC, NH4-N, and total phosphorus (TP) were the main drivers of the neutrality model’s stochasticity (R) and the stability of the co-occurrence network structure, according to SEM analysis. Co-occurrence network stability was specifically directly and significantly impacted negatively by EC (r = - 0. 369) and positively by TP (r = 0. 504) . The research revealed the bacterial assembly methods, co-occurrence network topology, and the driving impacts of physicochemical parameters on R and network stability, in addition to advancing the understanding of structure characteristics of bacterial communities in aquatic Sediments. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 42

Main heading: Stochastic models

Controlled terms: Aquatic organisms? - ?Assembly? - ?Bacteria? - ?Network topology? - ?Nitrogen compounds? - ?Physicochemical properties? - ?Random processes? - ?Sediments? - ?Stochastic systems

Uncontrolled terms: Assembly mechanism? - ?Bacterial community? - ?Bacterial community structure? - ?Co-occurrence networks? - ?Community assembly? - ?Community model? - ?Neutral community model model? - ?Structural equation models? - ?Structure characteristic? - ?Total phosphorus

Classification code: 103.1 Microbiology? - ?471 Marine Science and Oceanography? - ?483 Soil Mechanics and Foundations? - ?801.3 Physical Chemistry? - ?804.1 Organic Compounds? - ?804.2 Inorganic Compounds? - ?913.1 Production Engineering? - ?1201.8 Discrete Mathematics and Combinatorics, Includes Graph Theory, Set Theory? - ?1202.1 Probability Theory

DOI: 10.6041/j.issn.1000-1298.2025.12.068

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

7. Impact of Fishpond - Rice - Crab Integrated Co-culture Model on Structure of Soil Bacterial Community in Rice Fields

Accession number: 20255119732526

Title of translation: 不同鱼塘-稻蟹复合种养模式下稻田土壤细菌群落结构研究

Authors: Xu, Cheng (1); Wang, Kai (1); Qiu, Xiaocong (2); Zhou, Wei (3); Ni, Cheng (1); Yuan, Jinlong (4)

Author affiliation: (1) School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan; 750021, China; (2) School of Life Science, Ningxia University, Yinchuan; 750021, China; (3) Key Lahoratory of Water Ecology and Atmospheric Environment Quality Monitoring and Evaluation in Ningxia Hui Autonomous Region, Yinchuan; 750000, China; (4) Hubei University of Automotive Technology, Shiyan; 442002, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 717-726

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to address the problems of taüwater treatment in fishpond aquaculture in the Ningxia region and the scarcity of water resources in rice — crab co-culture Systems, the bacterial Community structure and soil environmental factors of a fishpond — rice — crab integrated co-culture model (RS) were compared and contrasted with the traditional Yellow River-irrigated rice — crab co-culture model (CK) as control. The primary environmental factors influencing alterations in the Organization of the bacterial population were also identified. The composition and structural variations of soil bacterial communities under both CK and RS models from April to August were examined, together with their associations with soil physicochemical markers, using 16S rRNA high-throughput sequencing techniques. The findings demonstrated that the RS model changed the species richness of soil bacteria while decreasing soil pH value and raising ammonium nitrogen and accessible phosphorus levels. The greatest Chaol and Shannon diversity indices appeared in April, while the lowest appeared in May. Proteobacteria, Bacteroidota, and Firmicutes were the most prevalent bacterial phyla from April to August, with Pseudomonas being the most prevalent genus. The oumulative relative abundance of Pseudomonas was decreased by 7. 61 percentage points, Thiobacülus was increased by 4. 94 pereentage points, and Unspecified_Bacteria was increased by 1. 83 percentage points as compared with the CK model; changes in other taxa were within ± 1 percentage point. Redundancy analysis showed that the most important variables influencing the top ten bacterial phyla were pH value, total nitrogen, ammonium nitrogen, total potassium, and organic matter concentration. Total potassium exhibited the highest explanatory power (23. 67%) among them, exhibiting negative relationships with other phyla and positive correlations with Proteobacteria. In general, the top ten phyla showed a positive correlation with nitrate nitrogen concentration. As a result, the fishpond — rice — crab integrated co-culture paradigm optimized the makeup of the bacterial Community, boosted bacterial species diversity, and greatly improved soil environmental conditions and structure. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 45

Main heading: Shellfish

Controlled terms: Abiotic? - ?Bacteria? - ?Biotic? - ?Fish ponds? - ?Nitrogen? - ?Potassium? - ?Redundancy? - ?RNA? - ?Water treatment

Uncontrolled terms: Abundance? - ?Bacterial community structure? - ?Co-cultures? - ?Crab integrated co-culture? - ?Culture modelling? - ?Fishpond? - ?Percentage points? - ?Redundancy analysis? - ?Rice? - ?Soil bacterial community

Classification code: 101.1 Biomedical Engineering? - ?101.7.1 Genetic Engineering? - ?103 Biology? - ?103.1 Microbiology? - ?202.9.1 Alkali Metals? - ?445.1 Water Treatment Techniques? - ?804 Chemical Products? - ?821.4 Agricultural Methods? - ?913.3 Quality Assurance and Control? - ?1502.2 Ecology and Ecosystems

Numerical data indexing: Percentage 6.70E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.066

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

8. Research and Experiment on Communication Network Design for Autonomous Operation Hydrogen Fuel Cell Tractor

Accession number: 20255119762226

Title of translation: 自主作业氢燃料电池拖拉机通信网络设计与试验

Authors: Xu, Liyou (1, 2); Shang, Yuchen (1, 2); Lei, Shenghui (1, 2); Yan, Xianghai (1, 2); Liu, Mengnan (2, 3)

Author affiliation: (1) College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang; 471000, China; (2) State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang; 471039, China; (3) YTO Group Corporation, Luoyang; 471000, China

Corresponding author: Liu, Mengnan(liumengnan27@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 69-77

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the issue that traditional communication network cabling methods are unable to meet the requirements of high efficiency, stability and functional expansion for information transmission in autonomous hydrogen fuel cell tractors, a multi-rate control area network (CAN) bus architecture was proposed based on the SAE J1939 protocol and ISO 11783 standard. Firstly, the data flow requirements for sensing, positioning, drive control, etc. were analyzed in combination with the autonomous operation process in the field. Then, using the principle of minimum complexity in graph theory, multiple topologies were compared and a gateway plus three-bus structure was determined. The CAN communication network nodes were divided based on the structure of the autonomous operation hydrogen fuel cell tractor and its working conditions, and the functions of each node were defined. For common network topologies, a mathematical model was established based on graph theory, and the total information volume per second N and the node information volume per second Z of each structure were analyzed and compared. A high-speed and low-speed dual-bus structure was adopted to design the communication network of the autonomous operation hydrogen fuel cell tractor, with bus rates selected as 500kb/s and 250kb/s. The communication message and system software design were developed based on the SAE J1939 protocol and ISO 11783 standard. The hardware functions and communication effects of the communication system were tested by using CANoe software and verified on the whole vehicle. The test results of the bus load rate were 28.22%, 19.20% and 22.85%, all below the 50% requirement. These results verified the feasibility and provided a feasible solution for the design of the communication network of autonomous operation hydrogen fuel cell tractors. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Gateways (computer networks)

Controlled terms: Automobile testing? - ?Buses? - ?Data communication systems? - ?Data flow analysis? - ?Data transfer? - ?Graph theory? - ?Hydrogen? - ?Hydrogen fuels? - ?Internet protocols? - ?Network architecture ? - ?Network topology? - ?Powertrains? - ?Process control? - ?Software testing? - ?Vehicle to vehicle communications

Uncontrolled terms: Autonomous operations? - ?Bus structures? - ?Communication networks design? - ?Communications networks? - ?Communications protocols? - ?Communications systems? - ?Control area network? - ?Higher efficiency? - ?Hydrogen fuel cell tractor? - ?Hydrogen fuel cells

Classification code: 522.1 Gas Fuels? - ?662 Automobiles and Smaller Vehicles? - ?662.3 Automobile Components and Materials? - ?663.1 Heavy Duty Motor Vehicles? - ?663.2 Heavy Duty Motor Vehicle Components? - ?716.3 Radio Systems and Equipment? - ?731 Automatic Control Principles and Applications? - ?804 Chemical Products? - ?913.3 Quality Assurance and Control? - ?1103.3 Data Communication, Equipment and Techniques? - ?1105 Computer Networks? - ?1105.2 Internet and Web Technologies? - ?1106 Computer Software, Data Handling and Applications? - ?1106.2 Data Handling and Data Processing? - ?1106.9 Computer Software? - ?1201.8 Discrete Mathematics and Combinatorics, Includes Graph Theory, Set Theory

Numerical data indexing: Bit rate 2.50E+05bit/s, Bit rate 5.00E+05bit/s, Percentage 1.92E+01%, Percentage 2.285E+01%, Percentage 2.822E+01%, Percentage 5.00E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.005

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

9. Particle Fertilizer Flow Microwave Signal Measurement Based on Variational Mode Decomposition and Wavelet Analysis

Accession number: 20255119745602

Title of translation: 基于变分模态分解联合小波分析的颗粒肥流量微波信号测量研究

Authors: Yang, Liwei (1); Zhang, Yuchen (1); Zhan, Zekai (2); Jin, Ziyang (1); Peng, Yonglin (1); Zhu, Yufei (2)

Author affiliation: (1) Key Laboratory of Smart Agriculture System Integration, Ministry of Education, China Agricultural University, Beijing; 100083, China; (2) College of Engineering, China Agricultural University, Beijing; 100083, China

Corresponding author: Yang, Liwei(yangliwei@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 623-633

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The accurate measurement of granular fertilizer mass flow rate presents a significant challenge for achieving precision fertilization. Due to the complex dynamics of granular flows, traditional measurement methods often struggle to handle the resulting signals, which are typically characterized by significant noise and non-stationarity. To address this issue, a novel pre-processing algorithm for granular fertilizer flow signals acquired by a microwave sensor was proposed. Initially, a model of the fertilizer discharge pipeline was constructed and simulation experiments were conducted. These simulations determined that under conditions of a 400 mm pipeline length and 30 mm diameter, the impact of particle collisions within the pipeline on velocity was minimized. Based on these simulation results, a signal acquisition platform for granular fertilizer mass flow was established. Through analysis of the acquired flow signals, a hybrid denoising algorithm combining variational mode decomposition (VMD) and discrete wavelet transform (DWT) was innovatively proposed. Experimental results demonstrated that after processing with this algorithm, the signal-to-noise ratio of the signal was increased by 7.375 7 dB, and the root mean square error was decreased by 57%. The algorithm effectively separated the noise component from the signal, thereby significantly improving the measurement accuracy of the granular fertilizer mass flow rate. Finally, real-world vehicle tests were conducted. The processed flow signals exhibited a maximum relative error of 13.84% and a minimum relative error of 1.36%. The results confirmed that the experimental platform developed and the proposed denoising algorithm provided reliable technical support for precision fertilization. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 20

Main heading: Flow rate

Controlled terms: Errors? - ?Fertilizers? - ?Granular materials? - ?Mean square error? - ?Microwave devices? - ?Modal analysis? - ?Pipelines? - ?Signal analysis? - ?Signal denoising? - ?Signal reconstruction ? - ?Signal to noise ratio? - ?Simulation platform? - ?Variational mode decomposition? - ?Wavelet decomposition

Uncontrolled terms: De-noising algorithm? - ?Flow rate measurements? - ?Flow signals? - ?Granular fertilizers? - ?Mass-flow rate? - ?Modal decomposition? - ?Mode decomposition? - ?Precision fertilizations? - ?Variational modal decomposition? - ?Wavelet denoising

Classification code: 214 Materials Science? - ?301.1 Fluid Flow? - ?610.1 Pipe, Piping, and Pipelines? - ?716.1 Information Theory and Signal Processing? - ?731.1.1 Error Handling? - ?821.3 Agricultural Chemicals? - ?941.5 Mechanical Variables Measurements? - ?1106.3 Digital Signal Processing? - ?1201.3 Mathematical Transformations? - ?1201.5 Computational Mathematics? - ?1201.12 Modeling and Simulation? - ?1202.2 Mathematical Statistics? - ?1502.1.1.3 Soil Pollution

Numerical data indexing: Decibel 7.00E+00dB, Percentage 1.36E+00%, Percentage 1.384E+01%, Percentage 5.70E+01%, Size 3.00E-02m, Size 4.00E-01m

DOI: 10.6041/j.issn.1000-1298.2025.12.057

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

10. Effects of Long-term Application of Organic Fertilizer on Hydrogen and Oxygen Isotopic Distribution and Wheat Water Utilization

Accession number: 20255119731923

Title of translation: 长期增施有机肥对氢氧同位素分布与小麦水分利用的影响

Authors: Yang, Yonghui (1, 2); Wu, Jiabin (3); Gao, Cuimin (1, 4); Zhang, Yunhong (1, 4); Pan, Xiaoying (1, 2); He, Fang (1, 2); Han, Weifeng (1, 4)

Author affiliation: (1) Institute of Plant Nutrition, Agricultural Resources and Environmental Sciences, Henan Academy of Agricultural Sciences, Zhengzhou; 450002, China; (2) Yuanyang Experimental Station of Crop Water Use, Ministry of Agriculture and Rural Affairs, Yuanyang, 453514, China; (3) Institute qf Water Resources jor Pastoral Area, Ministry of Water Resources, Hohhot; 010020, China; (4) Field Scientific Observation and Research Station of Water-saving Agriculture in the Yellow River Basin of Henan Province, Yuanyang, 453514, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 707-716

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: An indoor a n d a field experiment were conducted to study the water-stable large aggregates, soil organic carbon content, saturated hydraulic conductivity, hydrogen isotope distribution, physiological characteristics of wheat photosynthesis and water utilization under long-term application of organic fertilizer and chemical fertilizer, thus ascertaining soil moisture distribution and water use mechanism of long-term application of organic fertilizer. The results showed that the organic fertilizer significantly inereased the proportion of soil macro-aggregate, soil organic carbon content, saturated hydraulic conductivity, and thus led to the high stability of soil structure. The abundance of hydrogen and oxygen decreased gradually with the deepening of the soil layer. In the jointing period, the long-term application of chemieal fertilizer mainly used the water in 0 ~ 60 cm soil layer, and the yield of organic fertilizer mainly used the water of 0 - 2 0 cm soil layer, while the contribution rate of soil moisture of 0 ~ 20 cm soil layer was significantly higher than that of other soil layers, reaching more than 5 0 % . In the heading period, the long-term application of chemieal fertilizer and organic fertilizer mainly used the water in 0 ~ 20 cm soil layer, and the contribution rate of soil moisture in this soil layer was still more than 50% . In the filling period, the long-term application of chemieal fertilizer mainly used the water in 0 ~ 20 cm soil layer. The long-term application of organic fertilizer mainly used the water in 20 - 4 0 cm soil layer, and its contribution rate reached 5 0 . 2 % . With the advancement of wheat growth period, the soil water storage decreased gradually. Long-term application of organic fertilizer was more condueive to reducing the ineffective loss of soil water in the early stage of wheat growth, which improved the soil water storage, and then promoted the supply of water in the late stage of wheat growth. Compared with application of chemieal fertilizer, long-term application of organic fertilizer was more condueive to improving the photosynthetic rate, stomatal conductivity and leaf water use efficiency of wheat in different growth periods. With the advancement of wheat growth period, its above-ground biomass gradually inereased and above-ground biomass of organic fertilizer was higher than that of chemieal fertilizer. Ultimately, long-term application of organic carbon content significantly improved wheat yield and water use efficiency. Corcorrelation analysis showed that the water supply of 40 - 6 0 cm and 80 ~ 100 cm soil layers at jointing stage, and 20 - 80 cm soil layer at filling stage of wheat were more condueive to improving wheat yield, while soil supply of 40 - 6 0 cm, 80 - 100 cm at jointing stage, 60 - 100 cm at heading stage, and 80 - 100 cm at filling stage of wheat were more favorable to improve the water use efficiency. It concluded that the long-term application of organic fertilizer improved the soil structure, enhanced the storage, conservation and utilization capacity of preeipitation in the soil, improved the photosynthetic physiological characteristics of wheat, and promoted the increase of yield and water saving and efficiency. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 22

Main heading: Aggregates

Controlled terms: Fertilizers? - ?Forestry? - ?Hydraulic conductivity? - ?Hydrogen? - ?Isotopes? - ?Organic carbon? - ?Oxygen? - ?Photosynthesis? - ?Soil moisture? - ?Soil surveys

Uncontrolled terms: Contribution rate? - ?Growth period? - ?Hydrogen isotope? - ?Organic fertilizers? - ?Oxygen isotopes? - ?Photo synthetic characteristic? - ?Soil layer? - ?Soil structure? - ?Soil-structure? - ?Water utilization

Classification code: 217.2.2 Concrete Reinforcements? - ?405.3 Surveying? - ?483.1 Soils and Soil Mechanics? - ?741.1 Light/Optics? - ?802.2 Chemical Reactions? - ?804 Chemical Products? - ?804.1 Organic Compounds? - ?821.1 Woodlands and Forestry? - ?821.3 Agricultural Chemicals? - ?1401.1 Hydraulics? - ?1502.1.1.3 Soil Pollution

Numerical data indexing: Percentage 0.00E00%, Percentage 2.00E+00%, Percentage 5.00E+01%, Size 0.00E00m, Size 0.00E00m to 2.00E-01m, Size 0.00E00m to 6.00E-01m, Size 2.00E-01m to 8.00E-01m, Size 6.00E-01m to 1.00E00m, Size 8.00E-01m to 1.00E00m

DOI: 10.6041/j.issn.1000-1298.2025.12.065

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

11. Integrated Intelligent Control System for Water and Fertilizer in Vineyards in Arid Hot Valley Area Based on Internet of Things

Accession number: 20255119745592

Title of translation: 基于物联网的干热河谷区葡萄水肥一体化智能调控系统研究

Authors: Yu, Liming (1); Gu, Chenguang (1); Li, Na (1); Fu, Jun (2); Xing, Liwen (3)

Author affiliation: (1) College of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming; 650051, China; (2) Yuanmou County Guoranhao Agricultural Technology Co., Ltd., Yuanmou, 651399, China; (3) College of Water Resources and Hydropower, Sichuan University, Chengdu; 610065, China

Corresponding author: Li, Na(kjclina@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 289-300

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the key issues of low irrigation water use efficiency and backward management levels in grape cultivation in arid valley regions. It focused on collecting big data on the habitat and physiology of grape crops, integrating agronomic theoretical data, and an integrated decision-making system for water and fertilizer management was designed based on comprehensive multi-data coupling analysis. The system utilized standard Modbus protocol sensors for data collection and employed a LORA low-power wireless networking transmission module with freely settable timing. By integrating devices such as cloud boxes, gateways, and DTUs, the system established a soil and environmental Internet of things (IOT) monitoring and collection system, achieving continuous online monitoring and data collection of soil and the environment. The LORA wireless network transmission adopted the Modbus - RTU protocol for data transfer. The system incorporated a crop cultivation model built with an optimized fuzzy PID control algorithm based on the revised PM model. Through this model, the system can drive decision-making for irrigation and fertilization management, optimizing the agricultural production process. It achieved online control of integrated water and fertilizer irrigation equipment, reducing the need for manual operation. Experimental results showed that compared with traditional PID and fuzzy PID, the system’s overshoot was reduced by 13.6 percentage points and 3.6 percentage points respectively, the system response rate was increased by 58.2% and 26.6% respectively; water usage was reduced by 25.0% and 13.5% respectively, and fertilizer usage was reduced by 30.0% and 17.1% respectively. This system aimed to promote the upgrade of integrated water and fertilizer technology, transforming the decision-making mechanism from “theory-oriented, experience-guided, and fixed-value regulation” to a benchmark based on big data analysis and judgment, with the expectation of providing technical support for the realization of real-time and precise regulation of integrated water and fertilizer management in grape plantations in arid valley regions. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Big data

Controlled terms: Arid regions? - ?Crops? - ?Cultivation? - ?Data acquisition? - ?Data assimilation? - ?Data communication systems? - ?Data flow analysis? - ?Data integration? - ?Data mining? - ?Data reduction ? - ?Data transfer? - ?Decision making? - ?Digital storage? - ?Fertilizers? - ?Information management? - ?Internet protocols? - ?Irrigation? - ?Transmissions

Uncontrolled terms: Area-based? - ?Data collection? - ?Fertilizer management? - ?Integrated intelligent control systems? - ?Key Issues? - ?LORA wireless networking? - ?Percentage points? - ?Valley areas? - ?Water and fertilizer integration? - ?Wireless networking

Classification code: 443 Meteorology? - ?444 Water Resources? - ?602.2 Mechanical Transmissions? - ?821.3 Agricultural Chemicals? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?903 Information Science? - ?912.2 Management? - ?1103.1 Data Storage, Equipment and Techniques? - ?1103.3 Data Communication, Equipment and Techniques? - ?1105 Computer Networks? - ?1106 Computer Software, Data Handling and Applications? - ?1106.2 Data Handling and Data Processing? - ?1106.2.1 Data Mining? - ?1502.1.1.3 Soil Pollution

Numerical data indexing: Percentage 1.35E+01%, Percentage 1.71E+01%, Percentage 2.50E+01%, Percentage 2.66E+01%, Percentage 3.00E+01%, Percentage 5.82E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.026

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

12. Design and Kinematic Analysis of Mobile Parallel Mechanism with Over Constrained Branch Chains

Accession number: 20255119731969

Title of translation: 一种含过约束支链的多模式移动并联机构设计与仿真

Authors: Zhang, Chunyan (1); Xia, Yuang (1); Yu, Xinyue (2)

Author affiliation: (1) School of Mechanical and Automotive Engineering, Shanghai University of Engineering Seienee, Shanghai; 201620, China; (2) Weilai Automobile(Anhui) Co. , Ltd., Hefei; 230061, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 799-810

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: A multi-mode mobile parallel mechanism with over constrained branch chains was designed, and its degrees of freedom and kinematics were deeply analyzed. When exploring the motion of the parallel mechanism, the influence of the over constrained branch chain on its motion stability was studied, and the motion Simulation and physical production were carried out to verify the motion of the mechanism and the realization of each mode. Firstly, according to the analysis of the connection between the constrained branch chain and the platform branch chain, a multi-mode mobile parallel mechanism with constrained branch chain was obtained according to its configuration design. The degree of freedom of the two modes of the mechanism, quadrilateral rolling mode and spherical rolling mode, was analyzed by means of the bar group model. The comparative analysis of the mechanism with or without over constrained branch chains was carried out, the centroid coordinates were solved according to ZMP theory, the relationship between the mechanism with or without over constrained branch chains and the angle was compared and analyzed, and Matlab was used to carry out comparative analysis of the centroid Situation of the mechanism with motion. Finally, the kinematic Simulation of the mechanism was carried out by ADAMS, and the prototype was made to verify the movement of the mechanism and the realization of each mode. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Kinematics

Controlled terms: Chains? - ?Degrees of freedom (mechanics)? - ?MATLAB

Uncontrolled terms: Comparative analyzes? - ?Design Analysis? - ?Kinematic Analysis? - ?Mobile parallel mechanism? - ?Motion stability? - ?Multimodes? - ?Over constrained branch chain? - ?Over-constrained? - ?Parallel mechanisms? - ?Rolling mode

Classification code: 601.2 Machine Components? - ?602.1 Mechanical Drives? - ?1106.5 Computer Applications? - ?1201.5 Computational Mathematics? - ?1301.1.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2025.12.074

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

13. Discrete Element Method Based Modeling and Parameter Calibration for Millet Threshing Mixture

Accession number: 20255119745631

Title of translation: 基于离散元法的谷子脱出物建模与参数标定

Authors: Zhang, Dongming (1); Huang, Ziyang (1); Chen, Yifu (1); Yi, Shujuan (1); Li, Yifei (1, 2)

Author affiliation: (1) College of Engineering, Heilongjiang Bayi Agricultural University, Daqing; 163319, China; (2) College of Engineering, Northeast Agricultural University, Harbin; 150030, China

Corresponding author: Yi, Shujuan(yishujuan_2005@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 354-365

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to solve the problem of lack of accurate modeling and parameter support for multi-component heterogeneous particles in the clearing link during the combined millet harvesting process, a research on the modeling and parameter calibration of grain threshing mixture was carried out. Based on the compositional characteristics of millet threshing mixture, three types of typical particle models were constructed for seeds, millet panicle clusters and stalks, and the discrete element method combined with the auto-filling technology was used to model spheres, heteromorphs and cylinders, respectively, and the modeling morphology was optimized through the analysis of the number of filled spherical surfaces and the degree of morphological differences. Based on the determination of physical parameters of particles, using the angle of repose as an index, the parameter calibration method combining Plackett - Burman test, the steepest ascent test and Box - Behnken response surface optimization was adopted to realize the correction of contact parameters of seeds, millet panicle clusters and short stalks, and the average errors of simulation and actual angle of repose were 1.94%, 3.72% and 1.16%, respectively. In order to verify the accuracy of the model, high-speed camera validation tests were carried out, and the particle trajectories were extracted by using TEMA software and compared with the simulation results. The results showed that the overlap of the three types of particle trajectories was greater than 0.75, and the obtained mean absolute error and root mean square error were at a low level, indicating that the simulation trajectories were highly consistent with the measured results in terms of amplitude and trend, which verified the accuracy, and the model constructed was highly consistent with the measured results. The results showed that the modeling method and calibration parameters constructed had good physical consistency and engineering applicability, which can provide effective support for the particle dynamics simulation and mechanism research of millet cleaning process. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Trajectories

Controlled terms: Agriculture? - ?Calibration? - ?Discrete element methods? - ?Elementary particles? - ?Errors? - ?Finite difference method? - ?Mean square error? - ?Morphology? - ?Plants (botany)? - ?Software testing

Uncontrolled terms: Angle of repose? - ?Combine harvest? - ?Discrete elements method? - ?Millet? - ?Millet threshing mixture? - ?Model calibration? - ?Modeling by discrete element method? - ?Parameters calibrations? - ?Parametric calibration? - ?Particle trajectories

Classification code: 103 Biology? - ?214 Materials Science? - ?656 Space Flight and Research? - ?731.1.1 Error Handling? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?1106.9 Computer Software? - ?1201.5 Computational Mathematics? - ?1201.9 Numerical Methods? - ?1202.2 Mathematical Statistics? - ?1301.2.1 High Energy Physics

Numerical data indexing: Percentage 1.16E+00%, Percentage 1.94E+00%, Percentage 3.72E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.032

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

14. Design and Experiment of Reciprocating Roller Precision Seed Stem Metering for Giant Juncao

Accession number: 20255119745597

Title of translation: 往复辊式巨菌草精量排种器设计与试验

Authors: Zhang, Jianchao (1); Sun, Yuanze (1); Yu, Zhihong (1); Li, Gangtie (2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot; 010018, China; (2) College of Desert Control Science and Engineering, Inner Mongolia Agricultural University, Hohhot; 010011, China

Corresponding author: Yu, Zhihong(yzhyqyzhyq@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 235-246

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to achieve orderly seeding of giant Juncao seed stems, enhance seeding efficiency and accuracy, and prevent damage to seed buds, a reciprocating roller precision seed dispenser for giant Juncao seed was designed. This device consisted of a reciprocating seed feeding mechanism, a roller seed dispensing mechanism, and seed guiding components. Based on the physical characteristics of giant Juncao seed stems in the Northwest region and the agronomic requirements for planting the stems, theoretical analyses were conducted on the processes of seed feeding, dispensing, and output of the device to determine the structures and parameters of key components. The working process of the seed dispenser was simulated by using the EDEM method to analyze the forces and motions acting on the stems, confirming that no damage occurred during the seed feeding phase. Using seed filling rate, clogging rate, and qualified planting distance as experimental indicators, a second-order regression orthogonal rotary combination simulation experiment was designed. The optimal structural parameter combination for the seed dispensing roller was determined to be: groove depth of 16 mm, groove width of 24 mm, and surface spacing of 7 mm. The optimal structural parameters for the seed output port were as follows: side plate inclination angle of 45°, opening width of 45 mm, and opening length of 30 mm. To determine the best operational parameters for the seed dispenser, the qualified planting distance rate and the variation coefficient of planting distance were used as experimental factors in a second-order regression orthogonal rotary combination test. The results showed that when the rotation speed of the seed dispensing roller was 11.57 r/min, the height from the seed discharge port to the ground was 191.56 mm, and the inclination angle was 35.77°, the qualified planting distance rate reached 96.4%, with a variation coefficient of 9.98%. The working performance of the seed dispenser met the agronomic requirements for giant reed planting. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Dispensers

Controlled terms: Agronomy? - ?Feeding? - ?Plants (botany)? - ?Rollers (machine components)? - ?Seed? - ?Structural optimization

Uncontrolled terms: Inclination angles? - ?Parameter optimization? - ?Plantings? - ?Reciprocating roller? - ?Second orders? - ?Seed dispenser? - ?Seed stem of giant juncao? - ?Seeding efficiency? - ?Structural parameter? - ?Variation coefficient

Classification code: 103 Biology? - ?601.2 Machine Components? - ?691.2 Materials Handling Methods? - ?694.2 Storage? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1201.7 Optimization Techniques

Numerical data indexing: Angular velocity 1.93219E-01rad/s, Percentage 9.64E+01%, Percentage 9.98E+00%, Size 1.60E-02m, Size 1.9156E-01m, Size 2.40E-02m, Size 3.00E-02m, Size 4.50E-02m, Size 7.00E-03m

DOI: 10.6041/j.issn.1000-1298.2025.12.021

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

15. Drive Wheel Slip Rate Detection Method and Experiment for Tractor Based on Multi-sensor Data Fusion

Accession number: 20255119745613

Title of translation: 基于多传感器数据融合的拖拉机驱动轮滑转率检测方法与试验

Authors: Zhang, Shuo (1); Luo, Yanging (1); Wen, Jingming (1); Chen, Yu (1); Gong, Handong (1); Chen, Jun (1)

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

Corresponding author: Chen, Jun(chenjun_jdxy@nwsuaf.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 190-200

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurate detection of the drive wheel slip in tractor ploughing operations is fundamental to achieving slip control, which helps improve the traction efficiency and ploughing quality of a tractor. To address the issue of ensuring the accuracy and real-time performance of slip rate detection under heavy load ploughing conditions, a slip rate detection method based on multisensor data fusion was proposed. A real-time data collection platform for tractor ploughing operations was established. Field experiments were conducted to obtain tillage speed, forward acceleration, tractor pitch angle, roll angle, traction resistance, tillage depth and corresponding slip rate under different operating conditions. A datasets was constructed and subjected to statistical analysis. Four machine learning algorithms-random forest (RF), support vector regression (SVR), radial basis function neural network (RBFNN), and artificial neural network (ANN)-were employed to construct the slip rate detection models. The hyperparameters of these models were optimized by using grid search and particle swarm optimization (PSO). The performance of the models was evaluated via three metrics: the coefficient of determination (R2), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The results indicated that, except for the RE model, which exhibited overfitting, the other three models achieved satisfactory slip rate predictions (R2 > 0.9). Among them, the ANN model optimized with particle swarm optimization (PSO) for initial threshold weight optimization outperformed both the SVR model with an R2 of 0.918, an RMSE of 2.6% and a MAPE of 8.9%, and the RBFNN model with an R2 of 0.903, an RMSE of 3.0%, and a MAPE of 8.8% on the test dataset, achieving an R2 of 0.937, an RMSE of 1.0%, and a MAPE of 7.6%. This method enabled reliable and accurate detection of tractor drive wheel slip rate, offering an approach for precise online detection and control of slip rate. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Tractors (truck)

Controlled terms: Agriculture? - ?Data acquisition? - ?Data fusion? - ?Learning algorithms? - ?Mean square error? - ?Particle swarm optimization (PSO)? - ?Radial basis function networks? - ?Statistical tests? - ?Swarm intelligence? - ?Traction (friction) ? - ?Traction control? - ?Tractors (agricultural)? - ?Wheels

Uncontrolled terms: Detection methods? - ?Hyper-parameter optimizations? - ?Multi sensors data fusion? - ?Percentage error? - ?Plowing operation? - ?Rate detection? - ?Root mean square errors? - ?Slip rates? - ?Tractor? - ?Wheel slips

Classification code: 601.2 Machine Components? - ?663.1 Heavy Duty Motor Vehicles? - ?731.2 Control System Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?1101 Artificial Intelligence? - ?1101.2 Machine Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1106.2 Data Handling and Data Processing? - ?1201.7 Optimization Techniques? - ?1202.2 Mathematical Statistics? - ?1301.1.1 Mechanics

Numerical data indexing: Percentage 1.00E00%, Percentage 2.60E+00%, Percentage 3.00E+00%, Percentage 7.60E+00%, Percentage 8.80E+00%, Percentage 8.90E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.017

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

16. Residual Film - Root Stubble-elastic Tooth Interactions Based on SPH - FEM Coupling

Accession number: 20255119745604

Title of translation: 基于 SPH-FEM 耦合的残膜-根茬-弹齿互作规律研究

Authors: Zhang, Xuejun (1, 2); Shi, Yangyang (1); Yan, Jinshan (1, 2); Shi, Zenglu (1, 2); Ma, Xu (1, 2); Hou, Zhaoquan (1); Li, Huazhi (1)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Xinjiang Key Laboratory of Intelligent Agricultural Equipment, Urumqi; 830052, China

Corresponding author: Yan, Jinshan(jshan.yan@xjau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 386-396 and 406

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The existing residual plastic film recovery techniques in Xinjiang’s cotton fields primarily focus on mechanical properties, neglecting the dragging effect of root stubble on the film during collection. This results in residual film readily becoming entangled in the root stubble. It confirmed the operational parameters of the pick-up teeth by analyzing the recovery of residual film when picking up teeth in conditions containing root stubble. Employing a coupled finite element method (FEM) and smooth particle hydrodynamics (SPH) algorithm, the tines, stubble, and residual film were modeled as FEM meshes, while the soil was represented as SPH particles. This enabled simulation of the shear strain, peak stress, pick-up height, and tensile stress exerted by root stubble on the residual film. The recovery of residual plastic film in the presence of cotton root stubble was simulated and the recovery efficiency was analyzed. Field trial results indicated that when root stubble height ranged from 5 cm to 9 cm, the average recovery rate of residual film reached 91.25%, with a residual film retention rate on root stubble of 4.30%. When root stubble height was 10 ~ 12 cm, the average residual film recovery rate across plots was 82.66%, with 12.55% of residual film remaining on the root stubble. Plots with root stubble heights of 5 ~ 9 cm exhibited an 8.59 percentage point increase in recovery rates compared with plots with root stubble heights of 10 ~ 12 cm, alongside an 8.25 percentage point reduction in residual plastic film on stubble. In trial plots with root stubble heights of 5 ~ 9 cm, the residual film retention rate on root stubble was 45.34% lower than in plots with root stubble heights of 10 ~ 12 cm. The research findings can provide theoretical support for the correlation between root stubble and plastic film remnants, as well as for enhancing the recovery rate of plastic film remnants. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Shear strain

Controlled terms: Cotton? - ?Finite element method? - ?Hydrodynamics? - ?Pickups? - ?Plastic films? - ?Recovery? - ?Shear flow

Uncontrolled terms: Cotton stalk? - ?Cotton stalk stubble? - ?Element method? - ?Film recovery? - ?Plastic-film? - ?Residual films? - ?Residual rate? - ?Smooth particle hydrodynamic - finite element method? - ?Smooth particle hydrodynamics? - ?Stubble-elastic tooth

Classification code: 207.1 Polymer Products? - ?214.1.1 Stress and Strain? - ?301.1.5 Flow of Fluid-Like Materials? - ?301.2 Hydrodynamics? - ?752 Sound Devices, Equipment and Systems? - ?821.5 Agricultural Products? - ?1201.9 Numerical Methods? - ?1301.1.1 Mechanics? - ?1501.3 Sustainable Waste Managment

Numerical data indexing: Percentage 1.255E+01%, Percentage 4.30E+00%, Percentage 4.534E+01%, Percentage 8.266E+01%, Percentage 9.125E+01%, Size 1.00E-01m to 1.20E-01m, Size 5.00E-02m to 9.00E-02m

DOI: 10.6041/j.issn.1000-1298.2025.12.035

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

17. Accurate Detection of Cucumber Powdery Mildew Fungus in Microscopic Images Based on PG - YOLO v8s

Accession number: 20255119745622

Title of translation: 基于 PG-YOLO v8s 的黄瓜白粉病菌显微图像精准检测

Authors: Zhang, Yiding (1); Han, Zonghuan (2); Qiao, Chen (2); Zhang, Lingxian (2)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China

Corresponding author: Zhang, Lingxian(zhanglx@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 522-533

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Cucumber is one of the most important vegetables and economic crops in the world. The occurrence of fungal diseases in cucumbers seriously threatens the safety of cucumber production, with powdery mildew being one of the most common fungal diseases. With the rapid development of computer technology, more and more deep learning algorithms are being applied to identify powdery mildew fungus. However, existing algorithms suffer from low accuracy in recognizing small and occluded targets, as well as insufficient localization precision. To address this issue, the parallelized patch-aware attention (PPA) module was firstly introduced into the backbone network of YOLO v8s. By employing a parallel multi-branch structure and attention mechanism, it effectively captured multi-scale features of small targets, preserved critical information during multiple downsampling processes, and enhanced the performance of small target detection. Additionally, the global-to-local spatial aggregation (GLSA) module was introduced into the neck, which combined global contextual information with local detail features, significantly improving the model’s feature representation capability. This module enhanced the detection performance for small targets and complex scenes by better capturing multi-scale features. Experimental results showed that PG - YOLO v8s significantly improved powdery mildew fungus detection performance compared with YOLO v8s. The network achieved high precision in detecting powdery mildew fungus, with notable improvements in the detection accuracy of small and occluded targets. The research result can provide a high-throughput method for detecting powdery mildew fungus, enabling precise early detection and guiding early intelligent decision-making in cucumber production. This approach can help to improve disease control efficiency, ensure cucumber yield and quality, and it was of great significance for the sustainable development of agricultural production. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 34

Main heading: Object detection

Controlled terms: Crops? - ?Decision making? - ?Deep learning? - ?Disease control? - ?Fungi? - ?Learning algorithms? - ?Object recognition? - ?Sustainable development? - ?Throughput

Uncontrolled terms: Cucumber? - ?Detection performance? - ?Fungal disease? - ?Multi-scale features? - ?Objects detection? - ?Powdery mildew? - ?Powdery mildew fungus? - ?Small objects? - ?Small targets? - ?YOLO v8

Classification code: 102.1.2 Health Science? - ?103 Biology? - ?103.1 Microbiology? - ?821.5 Agricultural Products? - ?912.2 Management? - ?913.2 Production Control? - ?1101.2 Machine Learning? - ?1101.2.1 Deep Learning? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision? - ?1501.1 Sustainable Development

DOI: 10.6041/j.issn.1000-1298.2025.12.048

Funding Details: Number: 2024M763577, Acronym: -, Sponsor: China Postdoctoral Science Foundation; Number: 62176261, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: National Natural Science Foundation of China (62176261); China Postdoctoral Science Foundation (2024M763577)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

18. Review of Research on Key Technologies for New Power Transmission Systems in Tractors

Accession number: 20255119745594

Title of translation: 拖拉机新型动力传动系统关键技术研究综述

Authors: Zhao, Sixia (1, 2); Li, Xianzhe (1, 2); Yan, Xianghai (1, 2); Zhang, Junjiang (1, 2); Wu, Yiwei (1, 2); Xu, Liyou (1, 2)

Author affiliation: (1) College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang; 471003, China; (2) National Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang; 471000, China

Corresponding author: Xu, Liyou(xlyou@haust.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 24-40

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The tractor serving as the core power equipment for achieving agricultural modernization and efficient production, has a technological development level that directly influences the efficiency, cost, and sustainability of agricultural operations. The industry is rapidly evolving toward high-end, intelligent, and green directions, with new power transmission technologies becoming the most critical and dynamic area of innovation in this transformation. A comprehensive review of the current research status of new power transmission technologies for tractors, both domestically and internationally was provided, which systematically addressed the field from three dimensions: theoretical research on new transmission systems, development of key technologies, and industrial applications. It was focused on diverse technical pathways, including power shift transmission, hydro-mechanical continuously variable transmission, pure electric drive systems, as well as diesel-electric hybrid, hydrogen hybrid, and methane hybrid power systems. It delved into the basic structure, working principles, and performance characteristics of these power transmission systems, and the development status of key technologies was analyzed by examining typical tractor products from China and other countries, along with their practical application outcomes and productization paths. The critical bottleneck issues that needed to be overcome in current new power transmission technologies were generalized and summarized, primarily including battery capacity and charging rates, control precision and stability, environmental adaptability of electric drive systems, multi-energy source management, and the production and storage of new energy sources. Finally, it outlined future development trends for new power transmission systems in tractors, proposing deep integration in three major directions: global energy efficiency utilization, full-scenario self-adaptive compatibility, and modular multi-functional expansion. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 75

Main heading: Environmental technology

Controlled terms: Agricultural machinery? - ?Agriculture? - ?Electric drives? - ?Electric machine control? - ?Electric power transmission? - ?Energy efficiency? - ?Engineering research? - ?Hybrid power? - ?Modernization? - ?Power transmission ? - ?Research and development management? - ?Sustainable development? - ?Transmissions

Uncontrolled terms: Diesel-electric hybrid power? - ?Electric drive system? - ?Hybrid power? - ?Hydrogen-electric hybrid power? - ?Methane-electric hybrid power? - ?Power transmission systems? - ?Pure electric drive system? - ?Tractor

Classification code: 601.3 Mechanisms? - ?602.1 Mechanical Drives? - ?602.2 Mechanical Transmissions? - ?702 Electric Batteries and Fuel Cells? - ?705.1 Electric Machinery? - ?706.1.1 Electric Power Transmission? - ?731.2 Control System Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?901 Engineering Profession? - ?901.3 Engineering Research? - ?912.1 Industrial Engineering? - ?912.2 Management? - ?1009 Energy Management? - ?1501.1 Sustainable Development? - ?1501.1.1 Sustainable Transport? - ?1502 Environmental Engineering

DOI: 10.6041/j.issn.1000-1298.2025.12.002

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

19. Watermelon Breeding System Based on Machine Vision and Hyperspectral Imaging

Accession number: 20255119745663

Title of translation: 基于机器视觉与高光谱成像的西瓜考种系统研究

Authors: Zhao, Zehua (1, 2); Wang, Qingyan (2, 3); Chen, Junjie (2, 3); Huang, Wenqian (2, 3)

Author affiliation: (1) Mechanical and Electronic Engineering Institute, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (3) National Research Center of Intelligent Equipment for Agriculture, Beijing; 100097, China

Corresponding author: Huang, Wenqian(huangwq@nercita.org.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 450-459

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The watermelon breed testing system combining machine vision and hyperspectral imaging was developed to enhance efficiency, reduce labor, and improve consistency in quality evaluation. The system included an automatic image acquisition device, featuring a Gige camera and a weighing platform, to capture watermelon phenotypic data. It used hyperspectral imaging on selected regions of interest to model SSC distribution within the watermelon, with measurements of transverse and longitudinal diameters achieved through minimum external rectangle fitting and rind thickness estimated using Canny edge detection. Convolutional smoothing (SGS) algorithm was used to preprocess the spectral data by combining three algorithms, namely multivariate scattering correction (MSC), standard normal transform (SNV), and unit vector normalisation (UVN), respectively, and then the best preprocessed spectral data were filtered by competitive adaptive reweighting algorithm (CARS), successive projection algorithm (SPA), and one-time combined dimensionality reduction algorithm (CARS+SPA) for feature wavelength screening, and finally the screened spectral data were used to build PLSR models and analyzed for comparison. The results showed that the system had the highest accuracy of 98.68%, 98.82% and 93.81% for the measured values of transverse diameter, longitudinal diameter and rind thickness of watermelon, respectively, with the root mean square error of 2.43 mm, 2.08 mm and 1.63 mm, respectively, as compared with the manual measurements. The best model for predicting watermelon brix was (SGS+UVN)-CARS-PLSR, with prediction correlation coefficients and of 0.920 4 and 0.912 7, root mean square errors RMSEC and RMSEP of 0.376 0° Brix and 0.466 8° Brix, respectively, and a relative analytical error of prediction RPD of 2.49. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Hyperspectral imaging

Controlled terms: Computer vision? - ?Dimensionality reduction? - ?Edge detection? - ?Errors? - ?Image acquisition? - ?Machine vision? - ?Mathematical transformations? - ?Mean square error? - ?Prediction models? - ?Screening ? - ?Strain measurement

Uncontrolled terms: Brix visualization? - ?HyperSpectral? - ?Machine-vision? - ?Phenotypic data? - ?Root mean square errors? - ?Spectral data? - ?Successive projections algorithm? - ?Unit vectors? - ?Vector normalization? - ?Watermelon breeding

Classification code: 731.1.1 Error Handling? - ?746 Imaging Techniques? - ?802.3 Chemical Operations? - ?941.5 Mechanical Variables Measurements? - ?1101 Artificial Intelligence? - ?1101.2 Machine Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision? - ?1201.3 Mathematical Transformations? - ?1202.2 Mathematical Statistics

Numerical data indexing: Percentage 9.381E+01%, Percentage 9.868E+01%, Percentage 9.882E+01%, Size 1.63E-03m, Size 2.08E-03m, Size 2.43E-03m

DOI: 10.6041/j.issn.1000-1298.2025.12.041

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

20. Bioavailability of Fluoride in Sediments and Its Effect on Surface Water Fluoride Pollution in Ningxia Section of Yellow River Basin

Accession number: 20255119732028

Title of translation: 黄河流域宁夏段沉积物氟形态生物有效性及其对地表水氟污染的影响

Authors: Zhao, Zengfeng (1); Qiu, Xiaocong (2); Yin, Juan (1); Zhao, Ruizhi (3)

Author affiliation: (1) School of Civil and Hydraulic Engineering, Ningxia Vniversity, Yinchuan; 750021, China; (2) School of Life Science, Ningxia University, Yinchuan; 750021, China; (3) Ningxia Environment Monitoring Center, Yinchuan; 750002, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 697-706

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In the spring (April), summer (July), and autumn (October) of 2019 and 2021, samples were colleeted six times from 99 points in the Ningxia section of the Yellow River Basin. These 99 points were categorized into eight hydrological networks; the main stream of the Yellow River (Sl), Qingshui River (S2), Kushui River (S3), drainage diteh on the north bank of the Yellow River in the Weining section (S4), drainage ditch on the south bank of the Yellow River in the Weining section (S5), drainage ditch on the west bank of the Yellow River in the Qingshi section (S6), drainage ditch on the east bank of the Yellow River in the Qingshi section (S7), and urban landscape rivers and lakes (S8) . The spatial and temporal distribution characteristics of fluorine in Sediments were analyzed, the ecological risk of sedimentary fluorine was evaluated, and its impact on fluorine pollution in surface water was discussed. The results showed that the average Contents of water-soluble fluorine (Ws — F), exchangeable fluorine (Ex — F), total fluorine (T — F) in Sediments from the Ningxia section of the Yellow River Basin were 9. 42 mg/kg, 3. 23 mg/kg, and 517 mg/kg, respectively. The evaluation results of ERI K, and ERbl can better reflect the actual ecological risk. The Contents of Ws — F, Ex —F, and T —F in the Sediments of S3, S2 and S7 and the ecological risk of fluorine were all high, while those of Sl were low. Ws — F was an important factor that directly affected the F ~ content in surface water. T — F indirectly affected the F content of surface water by transforming into Ws — F. The strong release capacity of fluoride in Sediments of S3, S2 and S7 promoted the increase of fluoride content in surface water, which should be taken as the key control area. The dilution effect of Sl and the weak release ability of fluoride in Sediments of S6 reduced the fluoride content in surface water. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Sediments

Controlled terms: Catchments? - ?Drainage? - ?Fluoride minerals? - ?Fluorine? - ?Lakes? - ?River pollution? - ?Rivers? - ?Sedimentology? - ?Tellurium compounds? - ?Watersheds

Uncontrolled terms: Drainage ditches? - ?Ecological risks? - ?Fluoride? - ?Fluoride content? - ?Fluoride pollution? - ?Ningxium? - ?Total fluorine? - ?Watersoluble? - ?Yellow river? - ?Yellow River basin

Classification code: 407 Maritime and Port Structures; Rivers and Other Waterways? - ?444 Water Resources? - ?444.1 Surface Water? - ?481.1 Geology? - ?482.1 Minerals? - ?483 Soil Mechanics and Foundations? - ?804 Chemical Products? - ?804.1 Organic Compounds? - ?804.2 Inorganic Compounds? - ?1502.1.1.2 Water Pollution? - ?1502.3 Hydrology

Numerical data indexing: Mass 2.30E-05kg, Mass 4.20E-05kg, Mass 5.17E-04kg

DOI: 10.6041/j.issn.1000-1298.2025.12.064

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

21. Adaptive Energy-saving Control for Four-motor Dual-coupled Drive Electric Tractors in Load Traction

Accession number: 20255119745628

Title of translation: 基于牵引作业负载匹配的四电机双耦合电动拖拉机多驱动模式节能控制研究

Authors: Zhao, Zihao (1, 2); Xie, Bin (1, 2); Wen, Changkai (1, 2); Niu, Zezhong (1, 2); Zhao, Junjie (1, 2); Liu, Mengnan (3); Jia, Fang (4); Mei, Hebo (5)

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) YTO Group Corporation, Luoyang; 471039, China; (4) Luoyang Xiyuan Vehicle and Power Inspection Institute Co., Ltd., Luoyang; 471000, China; (5) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Science, Beijing; 100097, China

Corresponding author: Xie, Bin(xiebincau@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 87-98

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address issues such as low energy utilization efficiency and insufficient speed stability in electric tractor traction operations, an energy-saving control method was proposed based on a four-motor dual-coupled power system (FDPS). The FDPS combined the characteristics of distributed drive for front and rear axles with coupled drive for single axles, supporting single-motor, dual-motor, triple-motor, and quad-motor drive modes. A longitudinal dynamics model for the working unit and a tire-soil interaction model were established, along with motor and transmission system models that characterized the efficiency and dynamic properties of the FDPS. A multi-drive-mode energy-saving control architecture matching traction workload was proposed. The upper layer employed a hybrid penalty function particle swarm algorithm to offline generate FDPS drive mode switching and multi-motor optimal torque distribution rules based on varying demand driving forces and operating speeds. The lower layer integrated a fuzzy PID algorithm to online identify the machine’s demand driving force with precision while tracking target operating speeds. A 900-second energy-saving control bench test was conducted by using field-measured traction resistance data. Test results demonstrated that the proposed method reduced energy consumption by 3.76% and lowered the root mean square speed error by 11.1% compared with the average torque distribution control strategy, enhancing the machine’s operational economy and speed stability. The proposed power system can serve as a universal power platform, and the energy-saving control method can provide a reference for multi-power-source drive control research in electric tractors. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Traction control

Controlled terms: Automobile testing? - ?Drive axles? - ?Electric drives? - ?Electric machine control? - ?Electric power system control? - ?Electric power system stability? - ?Electric power transmission? - ?Electric power transmission networks? - ?Electric traction? - ?Electric vehicles ? - ?Energy efficiency? - ?Front axles? - ?Power control? - ?Speed control? - ?Traction (friction)? - ?Traction motors? - ?Tractors (agricultural)? - ?Tractors (truck)

Uncontrolled terms: Control methods? - ?Coupled drives? - ?Coupled power? - ?Drive mode? - ?Electric tractors? - ?Energy-saving control? - ?Multi-drive? - ?Multi-drive mode? - ?Speed stability? - ?Traction operation

Classification code: 433 Rail Transportation? - ?601.3 Mechanisms? - ?602.1 Mechanical Drives? - ?662 Automobiles and Smaller Vehicles? - ?662.1 Automobiles? - ?662.3 Automobile Components and Materials? - ?663.1 Heavy Duty Motor Vehicles? - ?663.2 Heavy Duty Motor Vehicle Components? - ?705.1 Electric Machinery? - ?705.3 Electric Motors? - ?706.1 Electric Power Systems? - ?706.1.1 Electric Power Transmission? - ?731.2 Control System Applications? - ?731.3 Specific Variables Control? - ?821.2 Agricultural Machinery and Equipment? - ?1009 Energy Management? - ?1301.1.1 Mechanics? - ?1501.1.1 Sustainable Transport

Numerical data indexing: Percentage 1.11E+01%, Percentage 3.76E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.007

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

22. Navigation Line Extractionin in Pear Orchard Based on MLKA and Temporal RANSAC Fusion

Accession number: 20255119732491

Title of translation: 基于MLKA与时序RANSAC融合的梨园导航线提取方法

Authors: Zhou, Jianjun (1); Liu, Quanle (1); Cao, Lei (1); Fan, Lin (1); Qiu, Quan (2)

Author affiliation: (1) College of Information Engineering, Beijing Institute of Petrochemical Technology, Beijing; 102617, China; (2) College of Intelligent Science and Engineering, Beijing University of Agriculture, Beijing; 102206, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 657-665

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: T r a d i t i o n a l Visual navigation m e t h o d s struggle to h a n d l e i n t e r f e r e n c e from varying lighting eonditions and weed occlusion in complex pear orchard environments. An improved navigation line extraction method was proposed based on YOLO v8 to address this challenge. The process integrated a multi-scale large kernel attention (MLKA) module into the YOLO v8 model to enhance the perception of trunk features. A multi-frame feature point fusion mechanism was designed. By recording and utilizing feature points detected in five consecutive frames, this mechanism effectively compensated for the problem of insufficient feature points in single-frame detection. Additionally, the random sample consensus (RANSAC) algorithm was introduced to denoise the feature points of the left and right tree rows, respectively, and the least Squares method was used for the two side tree rows ‘ line fitting. The navigation line was ultimately generated by calculating the angle bisector of the fitted lines from both sides of the tree rows. Experimental results showed that the improved model achieved a precision of 89. 8%, a recall of 79. 9%, and a mean average precision (mAP50 - 9 5) of 55. 1% in tree trunk detection tasks under various lighting eonditions and weed occlusion scenarios. The navigation line generated by combining multi-frame feature point fusion with RANSAC denoising exhibited an average angular deviation of only 1. 17° from the manually annotated reference navigation line, an average position deviation of 20. 40 pixels, and an average root mean Square deviation of 0. 27. The research result can provide a low-cost and highly adaptable technical Solution for visual navigation in pear orchard environments. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Least squares approximations

Controlled terms: Automatic guidance (agricultural machinery)? - ?Electromagnetic wave attenuation? - ?Extraction? - ?Forestry? - ?Fruits? - ?Lighting? - ?Navigation? - ?Orchards? - ?Robots? - ?Trees (mathematics) ? - ?Vision

Uncontrolled terms: Automatic navigation? - ?Consensus algorithms? - ?Frame features? - ?Multi-frame? - ?Multi-frame feature point fusion? - ?Multi-scale large kernel attention? - ?Multi-scales? - ?Pear orchard? - ?Random sample consensus? - ?Random sample consensus algorithm ? - ?YOLO v8

Classification code: 101.5 Ergonomics and Human Factors Engineering? - ?435.1 Navigation? - ?707 Illuminating Engineering? - ?711.1 Electromagnetic Waves in Different Media? - ?731.5 Robotics? - ?741.2 Vision? - ?802.3 Chemical Operations? - ?821.1 Woodlands and Forestry? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1201.7 Optimization Techniques? - ?1201.8 Discrete Mathematics and Combinatorics, Includes Graph Theory, Set Theory

Numerical data indexing: Percentage 1.00E00%, Percentage 8.00E+00%, Percentage 9.00E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.060

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

23. Straw Particle Size Correction Method Based on Near-infrared Spectral Characteristic Signals

Accession number: 20255119745593

Title of translation: 基于近红外光谱特征信号的秸秆粒径校正方法研究

Authors: Zhu, Liqiang (1); Guo, Jiantao (1); Yang, Zengling (1); Liu, Xian (1); Han, Lujia (1)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China

Corresponding author: Liu, Xian(lx@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 460-469

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Near-infrared spectroscopy has been widely used for the rapid analysis of the physical and chemical properties of straw, offering advantages such as fast detection speed, high efficiency, and non-destructive testing. However, in practical applications, differences in straw particle size can reduce the detection accuracy and stability of the model. For rice straw samples with varying geometric particle sizes, near-infrared spectra were obtained in the 10 000~4 000 cm-1 wavelength range. Polynomial fitting (PF) was employed to remove background signals from the spectral data of the straw samples. A one-way analysis of variance (ANOVA) was used to perform statistical testing (P -1 of the geometric particle size straw samples exhibited extremely significant differences (P ≤ 0.05, P ≤ 0.01, P≤0.001) and showed a highly significant correlation with particle size (Pearson’s r was 0.96). The quadratic polynomial mathematical model performed optimally, with an average coefficient of determination R2 and root mean square error (RMSE) of 0.53 and 0.002 1, respectively. PSRCM effectively corrected the spectral differences caused by characteristic signals at 6 824 cm-1, 5 360 cm-1, and 5 180 cm-1, with correction effects significantly superior to those of standard normal variate transformation (SNV) and multiplicative scatter correction (MSC). The research result can provide a theoretical basis for the transfer correction method of straw near-infrared spectroscopy models, which can be applied without the need for standard samples. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Near infrared spectroscopy

Controlled terms: Analysis of variance (ANOVA)? - ?Chemical detection? - ?Correlation methods? - ?Electromagnetic wave attenuation? - ?Infrared devices? - ?Mean square error? - ?Nondestructive examination? - ?Particle size? - ?Particle size analysis? - ?Polynomial regression ? - ?Polynomials? - ?Principal component analysis? - ?Signal analysis? - ?Spectrum analysis? - ?Statistical tests

Uncontrolled terms: Characteristic signal? - ?Correction method? - ?Geometric particle size? - ?Infrared: spectroscopy? - ?Near Infrared? - ?Near-infrared? - ?Particles sizes? - ?Rice straws? - ?Spectral characteristic signal? - ?Spectral characteristics ? - ?Spectral differences

Classification code: 215.2.1 Non-mechanical Properties Testing Equipment and Methods? - ?703 Electric Circuits? - ?711.1 Electromagnetic Waves in Different Media? - ?716.1 Information Theory and Signal Processing? - ?741.3 Optical Devices and Systems? - ?802 Chemical Apparatus and Plants; Unit Operations; Unit Processes? - ?805 Chemical Engineering? - ?941.5 Mechanical Variables Measurements? - ?1101.2 Machine Learning? - ?1201.1 Algebra and Number Theory? - ?1202 Statistical Methods? - ?1202.2 Mathematical Statistics? - ?1301.1.2 Physical Properties of Gases, Liquids and Solids? - ?1301.1.3.1 Spectroscopy

Numerical data indexing: Size 0.00E00m, Size 1.80E+00m, Size 3.60E+00m, Size 8.24E+00m

DOI: 10.6041/j.issn.1000-1298.2025.12.042

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

24. Crop Yields and Soil Responses to Biochar and Humic Acid Based on Meta-analysis

Accession number: 20255119732317

Title of translation: 基于Meta的作物产量与土壤对生物炭和腐殖酸响应研究

Authors: Zhu, Yan (1, 2); Huang, Tianyu (1, 2); Guo, Chunmei (1, 3); Lu, Yuhang (1, 3); He, Jing (1, 4); Song, Libing (1, 2)

Author affiliation: (1) College of Water Resources and Architectural Engineering, Shihezi University, Shihezi; 832000, China; (2) Key Laboratory oj Modern Water-saving Irrigation of Xinjiang Production and Construction Croup, Shihezi; 832000, China; (3) Technology Innovation Center for Agricultural Water and Fcrtilizer Efficiency Equipment of Xinjiang Production and Construction Croup, Shihezi; 832000, China; (4) Key Laboratory of Northwest Oasis Water-saving Agriculture, Ministry of Agriculture and Rural Affairs, Shihezi; 832000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 727-737

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: This Meta-analysis integrated 102 published domestic and international studies on biochar and humic acid application from 2019 to 2024. It examined their effects on crop yield and physicochemical-biological indicators of the 0 - 2 0 cm soil layer across three dimensions: application type (X1 ) , application rate (X2), and application duration (X3 ) . Results indicated that biochar and humic acid application significantly increased crop yield, soil pH value, porosity, total nitrogen content, organic matter content, and alkali-hydrolyzable nitrogen content (P 2 > X3 > X,. The most pronounced yield increase occurred at application rates exceeding 40 t/hm and application durations exceeding 4 years, with respective yield increases of 2 0 . 4 3 % and 1 8 . 4 % . Application rates of 0 ~ 20 t/hm significantly increased available phosphorus, alkali-hydrolyzable nitrogen, urease content, and catalase activity by 28. 29% , 10. 01% ,12. 37% , and 2. 69% , respectively. Application rates of 20 - 40 t/hm” increased pH value (3. 77% ) and nitrate nitrogen content (47. 85% ) ; application rates exceeding 40 t/hm” significantly reduced bulk density (8. 66% ) , while increasing porosity ( 15. 75% ) , total nitrogen content (20. 31% ) , and organic matter content (40.51%). Application duration of 0 - 2 years significantly reduced electrical conductivity ( 17. 92% ) and ammonium nitrogen (2.70% ), but increased soil organic matter content (33. 60% ) , available phosphorus content (26. 07% ) , nitrate nitrogen content (6. 88% ) , and catalase activity (4. 51% ) ; Application duration of 2 ~ 4 years increased soil pH value ( 16. 80% ) , porosity (4. 92% ) , and urease activity (17. 43% ) ; Application periods exceeding 4 years significantly increased alkali-hydrolyzable nitrogen content (22. ! 39% ) and total nitrogen content (22. 49% ) (P ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 39

Main heading: Porosity

Controlled terms: Biological materials? - ?Bulk Density? - ?Crops? - ?Electric conductivity? - ?Nitrates? - ?Nitrogen? - ?Phosphorus? - ?Physicochemical properties? - ?Phytochemistry? - ?Quality control ? - ?Soils

Uncontrolled terms: Application amount? - ?Application rates? - ?Biochar? - ?Crop yield? - ?Humic acid? - ?Nitrogen content? - ?Property? - ?Soil physioochemical property? - ?Year of application? - ?Yield

Classification code: 203 Biomaterials? - ?483.1 Soils and Soil Mechanics? - ?701.1 Electricity: Basic Concepts and Phenomena? - ?801.1 Biochemistry? - ?801.3 Physical Chemistry? - ?804 Chemical Products? - ?804.2 Inorganic Compounds? - ?821.5 Agricultural Products? - ?913.3 Quality Assurance and Control? - ?1301.1.2 Physical Properties of Gases, Liquids and Solids

Numerical data indexing: Age 0.00E00yr to 2.00E+00yr, Age 2.00E+00yr to 4.00E+00yr, Age 4.00E+00yr, Percentage 1.00E00%, Percentage 2.70E+00%, Percentage 2.90E+01%, Percentage 3.00E+00%, Percentage 3.10E+01%, Percentage 3.70E+01%, Percentage 3.90E+01%, Percentage 4.00E+00%, Percentage 4.051E+01%, Percentage 4.30E+01%, Percentage 4.90E+01%, Percentage 5.10E+01%, Percentage 6.00E+01%, Percentage 6.60E+01%, Percentage 6.90E+01%, Percentage 7.00E+00%, Percentage 7.50E+01%, Percentage 7.70E+01%, Percentage 8.00E+01%, Percentage 8.50E+01%, Percentage 8.80E+01%, Percentage 9.20E+01%, Size 0.00E00m

DOI: 10.6041/j.issn.1000-1298.2025.12.067

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

25. Optimization of Tractor HMCVT Parameters Based on Whole Life Speed Usage Rate

Accession number: 20255119732305

Title of translation: 基于全生命周期速度使用率的拖拉机HMCVT参数优化

Authors: Zhu, Zhen (2); Hou, Rui (1); Zhang, Hongwei (2); Yang, Ji (1); Wang, Dehai (2); Chen, Long (1)

Author affiliation: (1) Automotive Engineering Research Institute, Jiangsu University, Zhenjiang; 212013, China; (2) National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology, Baotou; 014030, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 790-798

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The design parameters of the transmission directly affect the dynamics and fuel economy of the vehicle, due to the complexity of the tractor’s working conditions and a variety of operating modes, so in the optimization of the design parameters of the tractor transmission cannot be directly borrowed from the automobile based on the optimization of the Standard cycle of working conditions. An independently designed hydro-mechanical continuously variable transmission (HMCVT) was taken as the research object, and a transmission design parameter optimization method based on the whole life cycle speed usage rate of the tractor was proposed, and a multi-objective genetic algorithm (MOGA) was used for optimization and Solution. Fuel consumption rate and climbing ability were used as the optimization objective functions, and parameters significantly affecting the optimization objectives were selected as design variables. Constraints were determined, and a multi-objective optimization model for the transmission device was established by using modeFrontier, combining MOGA based on Pareto optimal principles and experimental design, to perform a global search for optimization, resulting in Pareto optimal Solutions. The research results obtained the optimal Solutions under the constraints, reflecting the contradictory characteristics between dynamic Performance and fuel economy. The design variables of the Pareto optimal Solutions obtained through optimization iterations well met the matching requirements of the transmission device. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Tractors (truck)

Controlled terms: Automobile transmissions? - ?Fuel consumption? - ?Fuel economy? - ?Genetic algorithms? - ?Global optimization? - ?Iterative methods? - ?Life cycle? - ?Multiobjective optimization? - ?Optimal systems? - ?Pareto principle ? - ?Powertrains? - ?Tractors (agricultural)

Uncontrolled terms: Condition? - ?Continuously variable transmission? - ?Design parameters? - ?Hydro-mechanical? - ?Hydro-mechanical continuously variable transmission? - ?Multi-objectives genetic algorithms? - ?Optimisations? - ?Pareto optimal solutions? - ?Tractor? - ?Usage rate

Classification code: 522 Fuels? - ?602.2 Mechanical Transmissions? - ?661.1 Automotive Engines and Components? - ?662.3 Automobile Components and Materials? - ?663.1 Heavy Duty Motor Vehicles? - ?663.2 Heavy Duty Motor Vehicle Components? - ?821.2 Agricultural Machinery and Equipment? - ?913.1 Production Engineering? - ?961 Systems Science? - ?1009.1 Energy Conservation? - ?1009.2 Energy Consumption? - ?1106 Computer Software, Data Handling and Applications? - ?1201.7 Optimization Techniques? - ?1201.9 Numerical Methods

DOI: 10.6041/j.issn.1000-1298.2025.12.073

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

26. YOLO v8-based Intelligent Recognition of Live Cnaphalocrocis medinalis Using Optimized Targeted Trapping Device

Accession number: 20255119745577

Title of translation: 基于优化靶向诱捕器的 YOLO v8 活体稻纵卷叶螟智能识别方法

Authors: Liu, Shuangxi (1, 2); Wang, Liuxihang (1); Wang, Jinxing (1, 3); Hu, Xianliang (4); Yang, Shengjie (1); Ma, Pan (5)

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) Shandong Key Laboratory of Intelligent Production Technology and Equipment for Facility Horticulture, Taian; 271018, China; (4) Shandong Xiangchen Technology Group Co., Ltd. Co., Ltd., Ji’nan; 251400, China; (5) Jinan Academy of Agricultural Sciences, Ji’nan; 251400, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 499-509

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issues of small target size, varying pest postures, and low detection efficiency, and suboptimal performance of trapping devices during live rice pest identification, an intelligent recognition method was proposed based on an improved YOLO von model integrated with a one-to-three live targeted trapping device. By optimizing the structural design of the traditional targeted recognition equipment, a one-to-three live targeted trapping device was developed to enhance operational efficiency. For the construction of the dataset required for intelligent recognition, a frame-by-frame image clarity comparison and sorting method was proposed to improve data quality. Additionally, an adaptive module was introduced into the improved CBAM attention mechanism to enhance the model’s focus on target regions, and a high-resolution P2 layer was added to the AFPN structure to improve small target recognition capability. Comparative experiments demonstrated that the improved YOLO v8n model achieved a mean average precision (mAP@ 0.5) of 95.65% on the rice leaf folder dataset. Ablation experiments further verified that the enhanced CBAM module and the introduction of the P2 layer in the AFPN structure significantly improved model performance, resulting in optimal overall recognition capability. Field trials confirmed the practical effectiveness of the improved YOLO v8n model, achieving a recognition rate of over 90% for rice leaf folder pests across 60 mu (approximately 4 hectares) of rice fields when combined with the targeted identification device, demonstrating good robustness and stability. In summary, the intelligent recognition method for live rice pests based on YOLO von the improved model proposed effectively enhanced recognition accuracy and efficiency, providing a scientific basis for precise pest identification and control in rice fields, with strong practical application value and promotion potential. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 36

Main heading: Efficiency

Controlled terms: Agricultural machinery? - ?Architectural design? - ?Structural design? - ?Structural optimization

Uncontrolled terms: AFPN? - ?CBAM? - ?Intelligent recognition? - ?One-to-three live targeted trapping device? - ?Recognition methods? - ?Rice fields? - ?Rice leaves? - ?Rice pests? - ?Small targets? - ?Trapping devices

Classification code: 408 Structural Design? - ?409.1 Architecture? - ?821.2 Agricultural Machinery and Equipment? - ?904 Design? - ?913.1 Production Engineering? - ?1201.7 Optimization Techniques

Numerical data indexing: Area 4.00E+04m2, Percentage 9.00E+01%, Percentage 9.565E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.046

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

27. Evaluation Method of Tractor Dynamic Models Based on Time Response Error and Grey Relational Analysis

Accession number: 20255119745630

Title of translation: 基于时间响应误差与灰色关联度的拖拉机动力学模型评价方法

Authors: Lu, Liquan (1); Zhu, Zhongxiang (1, 2); Song, Zhenghe (1, 2); Zhai, Zhiqiang (1, 2); Wang, Jianhua (3); Zhang, Chuanchuan (3)

Corresponding author: Zhu, Zhongxiang(zhuzhonxiang@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 158-169

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issues of missing accuracy evaluation for tractor dynamic models and the lack of systematic, standardized assessment methods, an accuracy evaluation approach was proposed based on time-response error and grey relational analysis, grounded in the verification, validation, and accreditation (VV&A) theory of model simulation systems. A hierarchical validation index system comprising phase error, amplitude error, and shape error was constructed, and the grey relational degree method was applied for segmental evaluation of dynamic response curves. Four sets of idealized test cases with defined error components were designed and analyzed by using both the proposed method and traditional numerical error analysis techniques. The results demonstrated that the proposed method effectively decoupled and accurately identified multiple error characteristics in each test case, precisely reflecting the sources and distribution of errors, while its comprehensive evaluation accuracy outperformed traditional methods. Furthermore, taking a self-developed longitudinal dynamic model of a power-shift tractor as an application case, real vehicle data were collected under five road conditions: tilled field, untilled field, stubble field, concrete surface, and mixed road surface. The proposed method was used to compare and analyze simulation results against real vehicle data under various working conditions. The results indicated that the mean comprehensive accuracy score of the model was 90.95. Under high-speed and complex road conditions, scores for various error characteristics decreased significantly, with comprehensive results in some extreme conditions falling below 88, reflecting certain limitations of the model under different working conditions, which aligned with objective reality and verified the effectiveness and comprehensiveness of the proposed evaluation method. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Roads and streets

Controlled terms: Automobile testing? - ?Dynamic models? - ?Error analysis? - ?Hierarchical systems? - ?Safety testing? - ?Tractors (agricultural)? - ?Tractors (truck)

Uncontrolled terms: Accuracy evaluation? - ?Dynamics models? - ?Error characteristics? - ?Evaluation methods? - ?Grey relational analysis? - ?Real vehicles? - ?Response error? - ?Test case? - ?Time response error? - ?Tractor dynamic model

Classification code: 406.2 Roads and Streets? - ?662 Automobiles and Smaller Vehicles? - ?663.1 Heavy Duty Motor Vehicles? - ?731.1.1 Error Handling? - ?821.2 Agricultural Machinery and Equipment? - ?914.1 Accidents and Accident Prevention? - ?961 Systems Science? - ?1301.7 Statistical and Nonlinear Physics

DOI: 10.6041/j.issn.1000-1298.2025.12.014

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

28. Quality Grading Model of Base Wines of Xiaoqu Clear-flavored Chinese Baijiu Based on PSO RBF

Accession number: 20255119732010

Title of translation: 基于PSO-RBF的小曲清香型白酒基酒品质分级模型研究

Authors: Lu, Shaokun (1); Liao, Qian (1); Wu, Honggang (2); Ji, Yuanxia (3); Yang, Runling (1); Zhou, Tao (4); Lang, Yunwen (1)

Author affiliation: (1) College of Big Data, Yunnan Agricultural University, Kunming; 650000, China; (2) Archiven Yunnan University of Finance and Economics, Kunming; 650000, China; (3) College of Science, Yunnan Agricultural University, Kunming; 650000, China; (4) Yunnan Chishui Liquor Co. , Ltd., Zhaotong; 657000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 761-768 and 818

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The traditional wine making process of grading and storage is a crucial link that affects t h e quality of Chinese baijiu blending and finished wine, but the grading and storage process of Chinese baijiu are mainly relied on workers experience in traditional winemaking factories, causing difficulties in many characteristic quantification and form scientific basis for grading storage. Based on deep learning technology, a gas Chromatograph was used to quantitatively detect and analyse the content of flavour components in the base wine of small-curve clear-flavoured Chinese baijiu, and a regression model for the quality grading of the base wine was established using PLSR based on the content of the components detected in the base wine, Screening the first eight components that have the most significant impact on the quality grading of the base wine; ethyl acetate, ethyl lactate, ethyl valerate, isobutyl alcohol, ethyl caprylate, ethylene acetal, ethyl acetate, sec-butanol, n-propanol, and then the PSO - RBF neural network-based base wine quality Classification model was explored. Finally, according to the predicted Outputs of the test samples, our algorithm achieved 9 8 . 6 % accuracy in base wine Classification, which was significantly better than the 94. 3% of the traditional RBF neural network. As a result, the base wine Classification grading model was successfully constructed. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Blending

Controlled terms: Ethylene? - ?Food storage? - ?Grading? - ?Regression analysis? - ?Screening? - ?Wine

Uncontrolled terms: Base wine classification quality grading? - ?Classification quality? - ?Ethyl-acetate? - ?Grading model? - ?P S O - R B F? - ?PLSR? - ?Quality grading? - ?RBF Neural Network? - ?Wine classification? - ?Xiaoqu clear-flavored chinese baijiu

Classification code: 694.2 Storage? - ?802.3 Chemical Operations? - ?804.1 Organic Compounds? - ?822.1 Food Products Plants and Equipment? - ?822.3 Food Products? - ?1202.2 Mathematical Statistics

Numerical data indexing: Percentage 3.00E+00%, Percentage 6.00E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.070

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

29. Design of Adjustable Center of Gravity Tracked Vehicles and Study on Slope Stability

Accession number: 20255119732439

Title of translation: 重心可调式履带车辆设计与坡地稳定性研究

Authors: Mu, Xiaodong (1, 2); Yin, Yaowen (1); Zhou, Junrui (1, 2); Liu, Zhijie (1, 2); Liu, Yong (3); Ding, Xiaobing (4); Yang, Fuzeng (1, 2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Scientific Observation and Experimcntal Station of Agricultural Equipmcnt for the Northern China, Ministrj of Agriculture and Rural Affairs, Shaanxi, Yangling; 712100, China; (3) Sichuan Chuanlong Tractor Manufacturing Co. , Ltd., Chengdu; 610511, China; (4) Chongqing Xinyuan Agricultural Machinery Co. , Ltd., Chongqing; 401329, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 777-789

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the problems of steep slopes and narrow roads, complex terrain and landforms, poor applioability of existing models on sloping land, and lack of design theory for mountain power machinery in hilly and mountainous areas, this paper proposes a “lateral Swing longitudinal shift” center of gravity adjustment crawler tractor scheme suitable for hilly and mountainous areas. In order to reduce research and development costs and shorten the research and development cycle, a “ lateral Swing longitudinal shift” center of gravity adjustable remote control crawler proportional prototype is specially created for feasibility verification and slope stability research of the scheme. A mathematical model and force analysis were conducted for slope driving before and after adjusting the center of gravity, and a stability index that considers both lateral and longitudinal directions — the uniform distribution coefficient of track contact pressure — was proposed. Grounding pressure and passability tests were conducted, and the results showed that the “lateral Swing longitudinal shift” center of gravity adjustable scheme proposed in this paper can greatly improve the uniformity of grounding pressure distribution for two tracks traveling on slopes; Under the slope eonditions of 5 °, 1 0 °, 1 5 °, and 2 0 °, after adjusting the center of gravity of the whole machine longitudinally and laterally, the maximum traction force of the vehicle when inclined 45° uphill is 398. 70 N, 339. 41 N, 265. 67 N, and 222. 32 N, respectively. The maximum traction force has increased by 13. 9%, 18. 1%, 27. 3%, and 50. 5% compared to before regulation. A maximum rollover test was conducted, and the results showed that when the longitudinal distanee of the upper body extended to a maximum of 150 mm, the static longitudinal maximum rollover angle increased from 39° to 4 6 °, an increase of 17. 9% compared to before the center of gravity adjustment; When the upper body sway angle is adjusted to the maximum value of 2 5 °, the static lateral limit tilt angle is increased from 40. 0° to 43. 5°, an increase of 8. 8% compared to before regulation; When passing obstacles on a slope, adjusting the horizontal or vertical center of gravity will increase the dynamic tipping coefficient of the vehicle on the slope, and the lifting effect will weaken with the increase of slope. Prove that the proposed Solution is feasible and can significantly improve the driving stability and anti rollover ability of tracked vehicles on slopes, providing theoretical and data support for Performance analysis and structural optimization design of tracked vehicles. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Convergence of numerical methods

Controlled terms: Geomorphology? - ?Gravitation? - ?Landforms? - ?Longitudinal control? - ?Machine design? - ?Pressure distribution? - ?Remote control? - ?Slope protection? - ?Slope stability? - ?Traction (friction) ? - ?Tractors (agricultural)

Uncontrolled terms: Adjustable center of gravity? - ?Center of gravity? - ?Hilly and mountainous areas? - ?Hilly mountainous terrain? - ?Maximum tractions? - ?Mountainous terrain? - ?Research and development? - ?Tipping? - ?Traction forces? - ?Upper bodies

Classification code: 406.2 Roads and Streets? - ?407.1 Maritime Structures? - ?481.1 Geology? - ?481.1.1 Geomorphology? - ?483.1 Soils and Soil Mechanics? - ?601 Mechanical Design? - ?731.1 Control Systems? - ?731.3 Specific Variables Control? - ?821.2 Agricultural Machinery and Equipment? - ?904 Design? - ?1201.9 Numerical Methods? - ?1301.1.1 Mechanics? - ?1301.1.5 Gravitation, Relativity and String Theory

Numerical data indexing: Force 3.20E+01N, Force 4.10E+01N, Force 6.70E+01N, Force 7.00E+01N, Percentage 1.00E00%, Percentage 3.00E+00%, Percentage 5.00E+00%, Percentage 8.00E+00%, Percentage 9.00E+00%, Size 1.50E-01m

DOI: 10.6041/j.issn.1000-1298.2025.12.072

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

30. Research Status and Development Suggestions of New Energy Power Equipment for Agriculture

Accession number: 20255119745660

Title of translation: 农业新能源动力装备研究现状与发展建议

Authors: Ouyang, An (1); Wen, Changkai (2); Fan, Chenlong (3); Song, Zhenghe (2)

Author affiliation: (1) Ministry of Industry and Information Technology Equipment Industry Development Center, Beijing; 100846, China; (2) College of Engineering, China Agricultural University, Beijing; 100083, China; (3) College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing; 210037, China

Corresponding author: Song, Zhenghe(songzhenghe@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 41-58

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The development of new energy power equipment for agriculture is of great significance for promoting the green and low-carbon transformation of agriculture, ensuring national food security and achieving agricultural modernization. A systematic review of domestic and international research progress in new power equipment for agricultural was provided. It focused on analyzing the current status and development trends of four major categories of equipment: new energy tractors, new energy micro-tiller, new energy work platforms, and new energy agricultural low-altitude aircraft. In the field of new energy agricultural machinery, tractors are developing in parallel toward pure electric, hybrid, and clean fuel options; new energy micro-tiller are evolving from “pure electric dominance” to “electric and hybrid parallel development and intelligent self-propulsion”. New energy work platforms are advancing along a technical path characterized by “electric drive as the main power source, supplemented by hydrogen/biofuels, and multi-form coordination of wheels, tracks, and wheeled legs”. New energy agricultural low-altitude aircraft are developing along a technical route featuring “electric drive as the main power source, hydrogen energy for extended range”. However, the new energy agricultural equipment industry is currently facing challenges such as inadequate adaptation of core technologies, an incomplete standard testing system, weak industrial chain coordination, lagging infrastructure, and an incomplete market service system. To this end, it was proposed that future efforts should be coordinated across multiple fronts: top-level policy design and standard testing, breakthroughs in key “three-electric” technologies and specialized chassis systems, industrial chain collaboration and pilot-scale validation, energy-supply infrastructure such as fast charging, battery swapping, and hydrogen fuel, and the completion of scenario-based demonstration and service systems. It was suggested to enhance the adaptability and reliability of new energy agricultural machinery to promote the application of electric agricultural machinery. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 62

Main heading: Tractors (agricultural)

Controlled terms: Agricultural implements? - ?Aircraft? - ?Carbon? - ?Electric drives? - ?Food security? - ?Food supply? - ?Hydrogen? - ?Hydrogen fuels? - ?Tillage? - ?Tractors (truck)

Uncontrolled terms: Agricultural drone? - ?Electric micro-till? - ?Energy equipments? - ?Green carbons? - ?Low carbon? - ?New energies? - ?New energy equipment of agricultural? - ?New energy tractor? - ?Power equipment

Classification code: 522.1 Gas Fuels? - ?601.3 Mechanisms? - ?602.1 Mechanical Drives? - ?652.1 Aircraft? - ?663.1 Heavy Duty Motor Vehicles? - ?705.1 Electric Machinery? - ?804 Chemical Products? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?822 Food Technology? - ?822.3 Food Products

DOI: 10.6041/j.issn.1000-1298.2025.12.003

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

31. Rice Seedling Counting Method Based on Multi-column Convolutional Network Integrating Multi-scale Features

Accession number: 20255119745612

Title of translation: 融合多尺度特征与多列卷积网络的水稻苗无人机遥感计数方法

Authors: Pan, Yi (1); Su, Haoran (1); Qin, Linlin (1); Wu, Gang (1); Shi, Chun (1); Wang, Yikun (2); Hua, Sheng (2)

Author affiliation: (1) Department of Automation, University of Science and Technology of China, Hefei; 230026, China; (2) Anhui Xiyangyang Agricultural Technology Co., Ltd., Hefei; 231521, China

Corresponding author: Qin, Linlin(qinll@ustc.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 560-567 and 580

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The planting density of rice in the early seedling stage is closely related to yield estimation and field management. With the development of computer vision technology, the use of drone image recognition technology to automatically count rice is gradually replacing traditional manual sampling and counting methods. However, images taken by drones have problems such as irregular rice seedling shapes, overlapping rice seedlings, scale changes, and background occlusion, which lead to deviations in feature learning, which in turn affects the accurate estimation of rice density and the efficiency of computational prediction. Significant relative size differences among rice seedlings will also become another important factor affecting counting accuracy. In response to these problems, a rice seedling counting algorithm (rice counting network, RCN) was proposed based on an improved multi-column convolutional neural network. Based on the size and shape of the target, an improved Gaussian density kernel was proposed, which combined the similarity information of the rice image and the RGB image of the center point to make the density kernel more suitable for the texture of the rice seedlings. The number of rice ears of different sizes and shapes was quantified, and the scales were divided finely to calculate the receptive field sizes of different features that needed to be fused. The fusion expansion convolution module was used to increase the receptive field size and enhance the model’s multi-scale capabilities. On this basis, appropriate attention mechanisms were added to the pathways at different scales to enhance attention to reasonable information about rice seedlings at different scales. It showed obvious effectiveness in scenes with complex backgrounds, multiscales and dense occlusions. On the RSD2023 data set captured at a height of 5 m, RCN’s mean absolute error MAE = 3.10 holes/m2 and mean square error MSE = 4.03 holes2/m4, which were better than that of the mainstream algorithms such as MCNN, CSRNet, SCAR and TasselNetV2. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Image enhancement

Controlled terms: Computational efficiency? - ?Computer vision? - ?Convolution? - ?Convolutional neural networks? - ?Drones? - ?Germination? - ?Remote sensing? - ?Textures

Uncontrolled terms: Convolutional networks? - ?Counting? - ?Density maps? - ?Multi-column neural network? - ?Multi-scale features? - ?Neural-networks? - ?Receptive field sizes? - ?Rice seedlings? - ?Size and shape? - ?UAV remote sensing

Classification code: 214 Materials Science? - ?652.1.2 Military Aircraft? - ?716.1 Information Theory and Signal Processing? - ?731.1 Control Systems? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1101.2.1 Deep Learning? - ?1102.1 Computer Theory, Includes Computational Logic, Automata Theory, Switching Theory, Programming Theory? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision

Numerical data indexing: Size 5.00E+00m

DOI: 10.6041/j.issn.1000-1298.2025.12.051

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

32. Estimation of Aboveground Biomass of Maize Based on Multisource Remote Sensing and Meteorological Parameters

Accession number: 20255119745677

Title of translation: 基于无人机多源遥感与气象参数的大田玉米地上生物量估算研究

Authors: Shao, Guomin (1); Han, Wenting (2); Zhou, Beibei (1); Wang, Yi (3); Lin, Guanghua (4)

Author affiliation: (1) State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an; 710048, China; (2) Institute of Water-saving Agriculture in Arid Areas, Northwest A&F University, Shaanxi, Yangling; 712100, China; (3) College of Information, Xi’an University of Finance and Economics, Xi’an; 710100, China; (4) Wuqi Oil Production Plant, Yanchang Oil Field Co., Ltd., Yan’an; 717600, China

Corresponding author: Han, Wenting(hanwt2000@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 436-449

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurately and rapidly monitoring the spatio-temporal distribution of aboveground biomass in crops is crucial for assessing growth conditions and managing precision irrigation in agricultural fields. Spectral indices have been widely utilized for estimating aboveground biomass; however, the spectral saturation effect under high coverage significantly impacts model performance. Furthermore, the effectiveness of integrating complementary and synergistic effects of spectral, temperature, and texture information from UAV remote sensing for estimating maize aboveground biomass across different growth stages and irrigation treatments at the farmland scale remains unclear. Additionally, the influence of meteorological factors on the interannual performance of remote sensing models for aboveground biomass estimation requires further investigation. Based on data from experimental sites in Inner Mongolia in 2018, 2019, and 2021, the spectral indices, temperature indices, and texture information obtained from UAV-based multisource remote sensing system, along with meteorological parameters such as reference evapotranspiration and vapor pressure deficit, were used as input features. Five modeling methods-stepwise regression, random forest regression, adaptive boosting regression, support vector regression, and one-dimensional convolutional neural network regression-were employed to establish a multisource feature fusion remote sensing estimation model for aboveground biomass of maize in large fields. The results showed that compared with single-type remote sensing information, the aboveground biomass estimation model integrating spectral, temperature, and texture information had better accuracy. Among them, the one-dimensional convolutional neural network regression model had relatively better accuracy (R2 = 0.87, RMSE = 295.77 g/m2). After introducing meteorological parameters, there was no significant improvement in the accuracy of the aboveground biomass estimation model by using drone multisource remote sensing information, indicating redundancy between meteorological parameters and drone multisource remote sensing information. Considering the cost of drone-mounted equipment and the operation efficiency, the aboveground biomass estimation model based on spectral indices and meteorological parameters using random forest regression also had satisfactory accuracy (R2 = 0.85, RMSE = 296.74 g/m2), suggesting that meteorological parameters can serve as a supplement to spectral indices. The performance of the one-dimensional convolutional neural network model for aboveground biomass estimation varied across different growth stages, indicating that the accuracy and reliability of the model need to be comprehensively assessed based on the crop growth stage. The research result can provide technical support for promoting the application of drone multisource remote sensing technology in precision irrigation management in farmlands. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 46

Main heading: Biomass

Controlled terms: Atmospheric temperature? - ?Convolution? - ?Convolutional neural networks? - ?Crops? - ?Digital storage? - ?Drones? - ?Evapotranspiration? - ?Grain (agricultural product)? - ?Irrigation? - ?Parameter estimation ? - ?Regression analysis? - ?Textures

Uncontrolled terms: Aboveground biomass? - ?Biomass estimation? - ?Maize? - ?Meteorological parameters? - ?Multi-Sources? - ?Reference evapotranspiration? - ?Remote-sensing? - ?Spectral indices? - ?Texture information? - ?UAV multisource remote sensing

Classification code: 214 Materials Science? - ?443.1 Atmospheric Properties? - ?444 Water Resources? - ?652.1.2 Military Aircraft? - ?716.1 Information Theory and Signal Processing? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1008 Renewable Energy? - ?1008.7 Bioenergy and Biomass Energy Conversion? - ?1101.2.1 Deep Learning? - ?1103.1 Data Storage, Equipment and Techniques? - ?1201 Mathematics? - ?1202 Statistical Methods? - ?1202.2 Mathematical Statistics? - ?1502.3 Hydrology

Numerical data indexing: Linear density 2.9577E-01kg/m, Linear density 2.9674E-01kg/m

DOI: 10.6041/j.issn.1000-1298.2025.12.040

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

33. Segmentation and Phenotypic Quantitative Analysis of Pigment Glands in Cotton Leaves Based on Gland - MSConNet Model

Accession number: 20255119745642

Title of translation: 基于 Gland - MSConNet 模型的棉花叶片色素腺体分割与表型量化分析

Authors: Shao, Limin (1, 2); Geng, Yuhong (1); Xu, Yaxuan (1); Wang, Guoning (3); Yan, Geng (1); Zhang, Yi (1)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding; 071001, China; (2) Technology Innovation Center of Intelligent Agricultural Equipment of Hebei Province, Baoding; 071001, China; (3) College of Agronomy, Hebei Agricultural University, Baoding; 071001, China

Corresponding author: Shao, Limin(shaolimin@hebau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 510-521

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Gossypol, a toxic compound unique to the Gossypium species, holds significant research value in agriculture and pharmaceuticals. Pigment glands, the primary carriers of gossypol, exhibit phenotypic traits that strongly correlate with gossypol content, making them effective indicators for its evaluation. However, the detection of pigment glands primarily relies on manual analysis, which is both time-consuming and inefficient. To address these limitations, Gland - MSConNet, a novel model designed for the accurate segmentation of cotton leaf pigment glands in complex backgrounds was proposed. The model integrated the convolutional bidirectional Mamba (ConBimamba) and multi-scale attention aggregation (MSAA) modules, significantly enhancing its ability to capture multi-scale features and improving robustness in challenging scenarios. Additionally, the incorporation of sub-pixel convolution facilitated efficient upsampling, preserving fine-grained details. Experimental results demonstrated that Gland - MSConNet achieved a segmentation mloU of 89.83% and a recall rate of 95.03%, representing improvements of 4.66 percentage points and 5.78 percentage points, respectively, over the U - Net model. These findings highlighted the model’s high segmentation accuracy and robustness. The Gland - MSConNet model provided a strong technical foundation for the segmentation and phenotypic quantification of cotton leaf pigment glands, offering a reliable basis for the automated evaluation of gossypol content. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 40

Main heading: Cotton

Controlled terms: Convolution? - ?Forestry? - ?Latent semantic analysis? - ?Pigments? - ?Plants (botany)? - ?Semantic Segmentation? - ?Semantics

Uncontrolled terms: Cotton leaf? - ?Gossypium? - ?Gossypol? - ?ITS evaluation? - ?Leaf pigments? - ?Percentage points? - ?Phenotypic traits? - ?Pigment gland? - ?Semantic segmentation? - ?Toxic compounds

Classification code: 103 Biology? - ?716.1 Information Theory and Signal Processing? - ?804 Chemical Products? - ?804.2 Inorganic Compounds? - ?821.1 Woodlands and Forestry? - ?821.5 Agricultural Products? - ?903.2 Information Dissemination? - ?1106.7 Computational Linguistics? - ?1106.8 Computer Vision

Numerical data indexing: Percentage 8.983E+01%, Percentage 9.503E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.047

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

34. Design and Experiment of Handheld Crop NDVI Sensor Based on Active Light Source

Accession number: 20255119745662

Title of translation: 基于主动光源的手持式作物 NDVI 传感器设计与试验

Authors: Sheng, Wenyi (1, 2); Wu, Fan (1, 2); Hu, Xuan (1, 2); Ni, Wenfeng (1, 2); Qiu, Ruicheng (1, 2); Zhang, Man (1, 2)

Author affiliation: (1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Smart Agriculture Systems Integration, Ministry of Education, China Agricultural University, Beijing; 100083, China

Corresponding author: Zhang, Man(cauzm@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 301-310

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the needs of modern agriculture in monitoring the overall crop growth status and developmental trends across various growth stages, and enable rapid, non-destructive crop assessment, a handheld crop normalized difference vegetation index (NDVI) sensor based on an active light source was developed. The sensor integrated narrow-band LEDs at 650 and 850 nm, along with Si PIN photodetectors, ensuring stable light output and precise signal acquisition. NDVI values were measured by using signal modulation and demodulation techniques across 60 wheat canopies subjected to four different fertilization levels. Experimental results demonstrated excellent light source stability, with standard deviations at both wavelengths maintained within 0.9 mV. In optical calibration experiments conducted at varying measurement heights, the results exhibited a strong linear relationship to the calibration parameters, with correlation coefficients (R2) exceeding 0.97. When the measurement height ranged from 20 cm to 40 cm, NDVI outputs remained largely stable, with root mean square errors (RMSE) of 0.025 and 0.015, respectively. Moreover, the sensor effectively mitigated the influence of ambient light fluctuations, ensuring consistent measurement results. A comparative analysis with a reference instrument demonstrated strong agreement in NDVI measurements, with R2 of 0.79 and RMSE of just 0.031. These results confirmed that the developed handheld crop growth sensor delivered high reliability and accuracy in practical applications, providing robust technical support for crop growth monitoring and a sound scientific foundation for modern agricultural production management. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Nondestructive examination

Controlled terms: Calibration? - ?Crops? - ?Light sources? - ?Optical correlation? - ?Optical variables measurement? - ?Vegetation

Uncontrolled terms: Active light source? - ?Crop growth? - ?Hand-held sensor? - ?Handhelds? - ?Infrared: spectroscopy? - ?Near Infrared? - ?Near-infrared? - ?Non destructive testing? - ?Normalized difference vegetation index? - ?Root mean square errors

Classification code: 103 Biology? - ?215.2.1 Non-mechanical Properties Testing Equipment and Methods? - ?707 Illuminating Engineering? - ?741.1 Light/Optics? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.5 Agricultural Products? - ?941.2 Optical Variables Measurements

Numerical data indexing: Size 2.00E-01m to 4.00E-01m, Size 6.50E-07m, Size 8.50E-07m, Voltage 9.00E-04V

DOI: 10.6041/j.issn.1000-1298.2025.12.027

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

35. Design and Experiment of Integrated Machine for Cotton Stalk Crushing and Residual Film Recycling and Baling

Accession number: 20255119745608

Title of translation: 棉秆粉碎与残膜回收打包一体机设计与试验

Authors: Shi, Mingwei (1); Wang, Minggang (1); Wang, Wei (2); Li, Zhiguo (1); Wang, Lei (2); Zhang, Haijuan (3)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Xi’an Yuhengheyue Agricultural Machinery Equipment Co., Ltd., Xi’an; 710065, China; (3) Xi’an Agricultural Machinery Supervision and Extension General Station, Xi’an; 710065, China

Corresponding author: Li, Zhiguo(lizhiguo0821@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 397-406

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In recent years, film mulching technology has been widely used in agriculture. After cotton harvest, large amounts of residual film need to be recycled, simultaneously, cotton stalks crushing needs to be carried out, in Xinjiang, China. The existing integrated machine for straw crushing and residual film recycling in China can be mainly divided into drum-type and chain teeth type. Considering the current drum-type integrated machine, which has a low residual film recovery rate, and high impurity content in the residual film, the rubbing-type residual film baling mechanism was prone to throw out the residual film and was easy to deform the baling belt and other problems, an integrated machine for straw crushing and residual film recycling and baling was developed. Through principle analysis and calculation, the key parameters of the hammer blade straw crushing mechanism and the screw conveying mechanism were determined; the residual film picking mechanism and the wheel drive mechanism were improved, and the dimensions and rotation speed of the film pick-up drum, the transmission ratio between the wheel and the film pick-up drum, the dimensions of the film pick-up teeth and the space between adjacent film pick-up teeth were determined; through theoretical analysis, the structural parameters and operating parameters of the screw impurity removal mechanism and the film removal mechanism were determined; by analyzing the process of residual film baling, the parameters such as the angle between the baling belt and the horizontal plane, the linear speed of the baling belt, and the number and space of the support rollers were determined. The field test demonstrated that the optimal operating parameters of the machine were as follows: the machine’s advancing velocity was 10 km/h, the depth of the film-picking teeth was 25 mm, and the height of the stubble was 10 cm. Validation test results demonstrated that under the aforementioned optimal operating parameters, the film pickup rate was 89.78%, the soil content was 11.15%, and the pass rate of crushed straw was 94.79%. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 17

Main heading: Plastic films

Controlled terms: Agricultural machinery? - ?Belts? - ?Cotton? - ?Crushing? - ?Optimal systems? - ?Pickups? - ?Plastic recycling? - ?Removal? - ?Screws? - ?Wheels

Uncontrolled terms: Cotton stalk? - ?Cotton stalk crushing? - ?Integrated machines? - ?Operating parameters? - ?Optimal design? - ?Plastic-film? - ?Residual film baling? - ?Residual film recycling? - ?Residual films

Classification code: 207.1 Polymer Products? - ?214 Materials Science? - ?601.2 Machine Components? - ?602.2 Mechanical Transmissions? - ?605.2 Small Tools, Unpowered? - ?752 Sound Devices, Equipment and Systems? - ?802.3 Chemical Operations? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?961 Systems Science? - ?1501.3.1 Recycling Waste

Numerical data indexing: Percentage 1.115E+01%, Percentage 8.978E+01%, Percentage 9.479E+01%, Size 1.00E+04m, Size 1.00E-01m, Size 2.50E-02m

DOI: 10.6041/j.issn.1000-1298.2025.12.036

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

36. Individual Identification Method of Dairy Cows in Cowsheds under Wide Field of View Based on DAM - ResNet

Accession number: 20255119745615

Title of translation: 基于 DAM-ResNet 的广视野下牛舍奶牛个体识别方法

Authors: Si, Yongsheng (1, 2); Lu, Wenke (1, 2); Wang, Kejian (1, 2); Ma, Yabin (3); Yuan, Ming (3); Wang, Bin (1, 2); Wang, Zhencun (4)

Author affiliation: (1) College of Information Science and Technology, Hebei Agricultural University, Baoding; 071001, China; (2) Key Laboratory of Agricultural Big Data of Hebei Province, Baoding; 071001, China; (3) Hebei Provincial Station for Livestock Varieties Producing and Spreading, Shijiazhuang; 050061, China; (4) Tangshan Jincheng Animal Husbandry Co., Ltd., Tangshan; 064000, China

Corresponding author: Ma, Yabin(dhimyb@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 581-590 and 602

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems such as occlusion and large deformation of cow images in the cowshed under a wide field of view, which cause difficulties in individual identification, a method for individual identification of cows in the cowshed under a wide field of view based on the DAM - ResNet model was proposed. The Mask R - CNN model was used to segment four types of dairy cow parts: the back, the left side of the trunk, the right side of the trunk and the buttocks. Based on the ResNet34 residual network, the second-generation deformable convolution was introduced to enhance the extraction of deformed image features of cow patterns in the segmentation results. Integrating the AFF attention feature fusion module into the residual structure to achieve accurate recognition of images of small target cows at a distance. The fine-grained classification loss function, interchannel loss (MC - Loss), was adopted to improve the recognition accuracy of the model for cows with similar patterns. The multi-part dataset of dairy cows was constructed by using the segmented images of dairy cows, and the DAM - ResNet model was trained. Individual cow recognition tests were conducted on a dataset of 12 864 images of 57 dairy cows. The results showed that the recognition accuracy rates of the back, left trunk, right trunk and buttocks of dairy cows were 96.13%, 96.56%, 96.94% and 93.14%, respectively, which were 2.76, 2.88, 2.92 and 4.25 percentage points higher than those of the original ResNet model. The recognition accuracy rates of the method proposed within the ranges of 10 ~ 20 m, 20 ~ 30 m and 30 ~ 40 m were 97.54%, 90.72% and 82.17%, respectively. The research results can provide technical support for intelligent dairy cow breeding. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 33

Main heading: Convolution

Controlled terms: Classification (of information)? - ?Dairies? - ?Dams? - ?Image enhancement? - ?Image segmentation? - ?Livestock? - ?Statistical tests

Uncontrolled terms: Attentional feature fusion? - ?Cow individual identification? - ?Dairy cow? - ?Deformable convolution? - ?Features fusions? - ?Fine grained? - ?Fine-grained classification? - ?Individual identification? - ?Wide field-ofview? - ?Wide-field

Classification code: 407.1.1 Hydrotechnical Engineering Structures? - ?441.1 Dams? - ?716.1 Information Theory and Signal Processing? - ?821.5 Agricultural Products? - ?822.1 Food Products Plants and Equipment? - ?903.1 Information Sources and Analysis? - ?1106.3.1 Image Processing? - ?1202.2 Mathematical Statistics

Numerical data indexing: Percentage 8.217E+01%, Percentage 9.072E+01%, Percentage 9.314E+01%, Percentage 9.613E+01%, Percentage 9.656E+01%, Percentage 9.694E+01%, Percentage 9.754E+01%, Size 1.00E+01m to 2.00E+01m, Size 2.00E+01m to 3.00E+01m, Size 3.00E+01m to 4.00E+01m

DOI: 10.6041/j.issn.1000-1298.2025.12.053

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

37. Design and Test of Tractor Tillage Depth Control System Based on Optimal Draft-position Comprehensive Degree

Accession number: 20255119745667

Title of translation: 基于最优力位综合度的拖拉机耕深控制系统设计与试验

Authors: Sun, Xiaoxu (1); Lü, Huawei (1); Qian, Jin (1); Song, Yue (1); Lu, Zhixiong (1)

Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China

Corresponding author: Lu, Zhixiong(luzx@njau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 180-189

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem that the artificial setting of comprehensive coefficient is difficult to adapt to the complex and changeable working environment of soil conditions in the process of tractor electro-hydraulic suspension tillage depth control, a tillage depth control method based on optimal draft-position comprehensive coefficient was proposed. Firstly, the test platform of tractor electro-hydraulic suspension draft-position integrated tillage depth control and loading system was built and the system was modeled by system identification method. Then aiming at the problem of uncertain parameters of the equivalent transfer function of the system, a global sliding mode control algorithm was designed, and an arc-tangent function was introduced to reduce the chattering of the system. The full factor sample test was designed, and the comprehensive operation evaluation index was established by compromise programming method. The expected draft-position comprehensive coefficient under different working conditions was obtained, and the optimal draft-position comprehensive model was established based on the least squares support vector machine optimized by particle swarm optimization algorithm (PSO-LSSVM). Finally, the effect of the control system was verified by using the built control system test platform. The results showed that the proposed algorithm achieved a rise time of 1.06 s without noticeable chattering. Compared with the fixed weight-depth control method with a comprehensive coefficient of 0.5, the proposed method reduced the depth deviation rate by 19.5% and 13.9% at target depths of 140 mm and 220 mm, respectively, while improving depth uniformity by 16.6% and 11.2%. This method can realize the adaptive adjustment of the comprehensive coefficient according to the soil specific resistance and tillage depth, and was more adaptable to the complex field operation environment, which provided a reference for the research of tillage depth control method. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Parameter estimation

Controlled terms: Hydraulic machinery? - ?Least squares approximations? - ?Particle swarm optimization (PSO)? - ?Sliding mode control? - ?Soil testing? - ?Support vector machines? - ?Tillage? - ?Tractors (agricultural)? - ?Tractors (truck)

Uncontrolled terms: Control methods? - ?Depth control? - ?Depth control system? - ?Electro-hydraulics? - ?Global sliding mode control? - ?Optimal draft-position comprehensive degree? - ?Parameters identification? - ?PSO-LSSVM? - ?Test platforms? - ?Tillage depth control system

Classification code: 483.1 Soils and Soil Mechanics? - ?663.1 Heavy Duty Motor Vehicles? - ?731.1 Control Systems? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?1101.2 Machine Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1201 Mathematics? - ?1201.7 Optimization Techniques? - ?1202 Statistical Methods? - ?1401.2 Hydraulic Equipment and Machinery? - ?1502.1.1.4.3 Soil Pollution Control

Numerical data indexing: Percentage 1.12E+01%, Percentage 1.39E+01%, Percentage 1.66E+01%, Percentage 1.95E+01%, Size 1.40E-01m, Size 2.20E-01m, Time 1.06E+00s

DOI: 10.6041/j.issn.1000-1298.2025.12.016

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

38. Prediction Method of Tractor Ploughing Resistance Based on Multisource Heterogeneous Sensor Data

Accession number: 20255119745601

Title of translation: 基于多源异构传感器数据的拖拉机犁耕阻力预测方法

Authors: Sun, Xiaoxu (1); Song, Yue (1); Zhang, Kai (1); Wang, Zheng (1); Lu, Zhixiong (1)

Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China

Corresponding author: Lu, Zhixiong(luzx@njau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 131-139

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to realize the precise control of ploughing resistance and improve the traction efficiency of tractor in ploughing operation, a prediction method of ploughing resistance was proposed. A plowing resistance perception model based on the upper pull rod force was proposed, and the experimental verification was carried out. In view of the problem that the measurement results were unstable by only sensing the ploughing resistance through the upper pull rod force in the actual field operation, a ploughing operation parameter test platform was built, and the multi-source heterogeneous sensor data based on tillage depth, upper pull rod force, vehicle speed and wheel speed were obtained and the prediction samples were constructed. The wavelet threshold denoising (WTD) and sparrow search algorithm (SSA) were introduced into the least squares support vector machine (LSSVM), and the combined prediction model of ploughing resistance based on WTD - SSA - LSSVM was established and the model performance was verified. The results showed that the model prediction method had higher accuracy than that of the upper pull rod force. In addition, different prediction methods were compared. The R2, MAE, RMSE and MAPE of the test set obtained by the combined prediction model method were 0.97, 118.1 N, 151.4 N and 2.2%, respectively. Compared with prediction models of LSSVM and SSA - LSSVM, R2 was increased by 8.9% and 5.4%, respectively. MAE was decreased by 49.7% and 42.2%, respectively. RMSE was decreased by 46.7% and 39.1%, respectively. MAPE was decreased by 56.8% and 48.8%, respectively. Therefore, the method proposed had better prediction performance and was more suitable for the prediction of tractor plough resistance. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Tractors (truck)

Controlled terms: Automobile testing? - ?Cultivation? - ?Forecasting? - ?Prediction models? - ?Support vector machines? - ?Traction control? - ?Tractors (agricultural)? - ?Vehicle wheels? - ?Wavelet analysis

Uncontrolled terms: Heterogeneous sensors? - ?Least square support vector machines? - ?Model prediction? - ?Multi-source heterogeneous sensor data? - ?Multi-Sources? - ?Plowing resistance? - ?Prediction methods? - ?Pull rod? - ?Sensors data? - ?Tractor

Classification code: 601.2 Machine Components? - ?662 Automobiles and Smaller Vehicles? - ?663.1 Heavy Duty Motor Vehicles? - ?731.2 Control System Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?1101 Artificial Intelligence? - ?1101.2 Machine Learning? - ?1106.3 Digital Signal Processing? - ?1201.3 Mathematical Transformations? - ?1202 Statistical Methods

Numerical data indexing: Force 1.181E+02N, Force 1.514E+02N, Percentage 2.20E+00%, Percentage 3.91E+01%, Percentage 4.22E+01%, Percentage 4.67E+01%, Percentage 4.88E+01%, Percentage 4.97E+01%, Percentage 5.40E+00%, Percentage 5.68E+01%, Percentage 8.90E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.011

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

39. Individual Identification Method of Simmental Cattle Based on Improved YOLO v8 Keypoint Detection

Accession number: 20255119745614

Title of translation: 基于改进 YOLO v8 关键点检测的西门塔尔牛只个体识别方法

Authors: Tian, Zhenjiang (1); Han, Cheng (1); Zhang, Chao (1); Li, Yueying (1); Yu, Fudong (2); Zhong, Xinhui (2)

Author affiliation: (1) School of Computer Science and Technology, Changchun University of Science and Technology, Changchun; 130012, China; (2) Jilin Sino Agri Sunshine Data Co., Ltd., Changchun; 130022, China

Corresponding author: Han, Cheng(hancheng@cust.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 591-602

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: With the intelligent development of animal husbandry, computer-vision-based individual cattle recognition is playing an increasingly important role in modern cattle farming. However, in practical applications, the rapid changes in the angles of cattle faces, frequent fluctuations in the number of cattle, and limitations in model recognition speed severely affect the accuracy and efficiency of recognition. To address these challenges, an individual recognition method for Simmental cattle was proposed based on improved YOLO v8 keypoint detection. The method consisted of two stages: in the cattle face detection stage, the improved YOLO v8 model automatically detected keypoints in cattle face images and performed correction alignment and background cropping to make the angles of the cattle face images more consistent. In the cattle face recognition stage, depthwise separable convolution was firstly introduced to reduce the number of parameters, and then residual connections and attention mechanisms were utilized to enhance the model’s feature extraction capabilities, thereby improving recognition accuracy and speed. To validate the effectiveness of the method, a dataset of cattle face images containing 159 Simmental cattle was constructed. Experimental results showed that the proposed model had significant improvements in the number of parameters and inference speed, with processing time for a single image reduced to within 39 ms and a recognition accuracy of 95.8%, an average improvement of 4.8 percentage points compared with that of other models. Additionally, the proposed method supported real-time updates to the cattle database, maintaining high accuracy even after adding new cattle face images. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Computer vision

Controlled terms: Agriculture? - ?Face recognition? - ?Feature extraction? - ?Image enhancement

Uncontrolled terms: Cattles? - ?Cow face recognition? - ?Face images? - ?Key point detection? - ?Keypoint detection? - ?Keypoints? - ?Point detection? - ?Recognition accuracy? - ?Recognition speed? - ?YOLO v8

Classification code: 821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?1101.2 Machine Learning? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision

Numerical data indexing: Percentage 9.58E+01%, Time 3.90E-02s

DOI: 10.6041/j.issn.1000-1298.2025.12.054

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

40. Association Analysis of Crop Diseases Based on Multi-source Heterogeneous Data and Knowledge Graph

Accession number: 20255119745632

Title of translation: 基于多源异构数据和知识图谱的作物病害关联分析

Authors: Wang, Bo (1); Ding, Junqi (1); Wu, Qifeng (2); Zhang, Lingxian (1)

Author affiliation: (1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China; (2) Xinjiang Acadamy of Agricultural and Reclamation Sciences, Urumqi; 832003, China

Corresponding author: Zhang, Lingxian(zhanglx@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 546-559

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The integration of multi-source heterogeneous agricultural information not only help understanding and unveiling the pathways of diseases infection and prevention but also offers vital data support for research on diseases prescription recommendations. Aiming at the problems of fusion, alignment and heterogeneity in the analysis of multi-source heterogeneous agricultural data such as electronic medical records, the knowledge graph of crop diseases prescription was constructed, and the diseases association on this basis was visually analyzed. Initially, starting from the principle of the disease triangle, the critical roles of pathogens, hosts, and environment in the process of disease infection and control were analyzed, constructing the ontology layer of the crop diseases prescription knowledge graph with 18 ontology concepts, 17 relationships, and 6 attribute edges based on data characteristics. Subsequently, the entity layer of the knowledge graph was built by integrating rule-matching and deep-learning knowledge extraction methods, encompassing 1 121 entity instances and 8 292 relationship instances. Lastly, identification of Top20 key nodes based on degree and betweenness centrality, along with Top5 disease-prevention product association predictions using the Adamic - Adar index, were conducted to visually analyze the associations between key entities and attributes, including diseases, symptoms, and prevention products. Six rules were established to enhance the recommendation and information retrieval functions of disease prevention products from three perspectives: prevention scheme selection, green subsidy filtering, and related information inquiry. The research result can provide reference for electronic medical record data mining and association analysis of crop diseases. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 37

Main heading: Ontology

Controlled terms: Crops? - ?Data mining? - ?Disease control? - ?Extraction? - ?Information retrieval? - ?Knowledge graph? - ?Learning systems? - ?Medical computing? - ?Medical problems

Uncontrolled terms: Association analysis? - ?Crop disease? - ?Disease prevention? - ?Disease triangle principle? - ?Electronic medical record? - ?Heterogeneous data? - ?Knowledge graphs? - ?Medical record? - ?Multi-source heterogeneous data? - ?Multi-Sources

Classification code: 101.1 Biomedical Engineering? - ?102.1.2 Health Science? - ?802.3 Chemical Operations? - ?821.5 Agricultural Products? - ?903.3 Information Retrieval and Use? - ?1101.2 Machine Learning? - ?1106.2 Data Handling and Data Processing? - ?1106.2.1 Data Mining? - ?1106.5 Computer Applications? - ?1106.7 Computational Linguistics

DOI: 10.6041/j.issn.1000-1298.2025.12.050

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

41. Multi Behavior Detection and Statistical Method for Beef Cattle Based on Local Perception

Accession number: 20255119745624

Title of translation: 基于局部感知的肉牛多行为检测与统计方法

Authors: Wang, Fang (1, 2); Liu, Xingyu (1, 2); Ren, Lisheng (1, 2); Fu, Chenfu (1, 2); Jia, Huixuan (1, 2)

Corresponding author: Ren, Lisheng(rls60683@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 603-614

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Given the current research on beef cattle behavior, which mainly focused on basic behavior recognition and lacked local perception of complex behaviors, the identification of fine behaviors under basic behaviors of beef cattle was researched. A multi-behavior detection and statistical method based on YOLO v8 for beef cattle was proposed. Cattle behavior images were collected by cameras to build a comprehensive dataset that included fundamental behaviors such as standing, lying down, feeding, and drinking, as well as fine behaviors like licking, walking, searching, and tail flicking. YOLO v8n - P2 was selected as the basic model to enhance the ability of the model to detect calves; the feature extraction structure of C2F - PPA was designed; the YOLO v8 detection head was improved by interactive strategy, and the TDADH was constructed. MPDIoU loss function was used to address limitations associated with CIoU. Subsequently, statistical analysis of cattle behaviors based on detection results throughout the day was conducted; these results were visually displayed for various occlusion environments. The experimental results showed that the PTPM - YOLO von model achieved precision rate of 91.0%, a recall rate of 87.9%, and a mAP @ 0.5 score of 94.3% in recognizing all eight behaviors tested. Compared with the original model YOLO v8n, the mAP@ 0.5 of PTPM - YOLO v8n was increased by 3.0 percentage points, and the parameter number was decreased by 21.9%. which identified all behaviors and basic behaviors, the mAP @ 0.5 was increased by 3.0 and 2.4 percentage points, respectively. The method presented can accurately identify fine behaviors of beef cattle under farming conditions, providing a reference for multi-behavior monitoring of beef cattle. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Object detection

Controlled terms: Agriculture? - ?Beef? - ?Behavioral research? - ?Feature extraction? - ?Object recognition? - ?Statistical methods

Uncontrolled terms: ‘current? - ?Beef cattle? - ?Behavior detection? - ?Behavioral statistic? - ?Behaviour recognition? - ?Cattles? - ?Multi behavior recognition? - ?Objects detection? - ?Percentage points? - ?YOLO v8

Classification code: 101.5 Ergonomics and Human Factors Engineering? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?822.3 Food Products? - ?971 Social Sciences? - ?1101.2 Machine Learning? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision? - ?1202.2 Mathematical Statistics

Numerical data indexing: Percentage 9.43E+01%, Percentage 2.19E+01%, Percentage 8.79E+01%, Percentage 9.10E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.055

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

42. Life Cycle Costs of Series Hybrid Tractors

Accession number: 20255119745673

Title of translation: 串联式混合动力拖拉机全生命周期成本研究

Authors: Wang, Jian (1); He, Dongsheng (1); Zhu, Yahui (2); Yin, Bifeng (1); Huang, Youlin (3)

Author affiliation: (1) School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang; 212013, China; (2) Jiangsu Wode Agricultural Machinery Co., Ltd., Zhenjiang; 212300, China; (3) Guangxi Yuchai Machinery Co., Ltd., Yulin; 537000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 99-109

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to investigate the impact of battery capacity configuration on system efficiency and life cycle cost (LCC) for high-horsepower hybrid tractors, thereby addressing the research gap in battery capacity optimization design for hybrid tractors, taking a 190 kW series hybrid tractor as the research object, an LCC evaluation system encompassing equipment procurement, battery replacement, and fuel consumption was established. A two-level battery capacity optimization method combining enumeration and dynamic programming (DP) was proposed: the outer layer investigated the influence of battery capacity on LCC under time-varying weights of energy and battery prices through global search via enumeration method, while the inner layer employed DP algorithm for optimal control of energy management strategies in hybrid tractors. A tractor simulation platform was developed by using Matlab/Simulink to quantitatively analyze the coupling mechanism between battery capacity and energy management strategies on system efficiency throughout the tractor’s lifecycle. Simulation results indicated that within the 2.2~110 A·h battery capacity range, increasing battery capacity benefited fuel consumption reduction and battery lifespan extension; the 24.2 A·h configuration represented the fuel consumption inflection point, beyond which capacity increase yielded minimal efficiency improvement; when battery capacity reached 52.8 A·h, no replacement was required based on cycle life, but the nonlinear battery capacity-LCC relationship showed 22 A·h configuration minimized LCC to 3.909 3 million yuan. The proposed “ technical parameters-life cycle cost” optimization framework established theoretical paradigms and provided valuable references for hybrid system design in agricultural machinery. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Dynamic programming

Controlled terms: Agriculture? - ?Battery management systems? - ?Costs? - ?Ecodesign? - ?Energy efficiency? - ?Hybrid systems? - ?Life cycle? - ?Machine design? - ?MATLAB? - ?Optimal control systems ? - ?Secondary batteries? - ?Simulation platform? - ?Tractors (agricultural)? - ?Tractors (truck)

Uncontrolled terms: Battery capacity? - ?Battery capacity configuration? - ?Capacity optimization? - ?Energy? - ?Energy management strategy? - ?Hybrid tractor? - ?Life cycle cost? - ?Management strategies? - ?Series hybrids? - ?System efficiency

Classification code: 601 Mechanical Design? - ?663.1 Heavy Duty Motor Vehicles? - ?702.1.2 Secondary Batteries? - ?731.1 Control Systems? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?904 Design? - ?911 Cost and Value Engineering; Industrial Economics? - ?913.1 Production Engineering? - ?1009 Energy Management? - ?1106.5 Computer Applications? - ?1201.5 Computational Mathematics? - ?1201.7 Optimization Techniques? - ?1201.12 Modeling and Simulation? - ?1501.1 Sustainable Development

Numerical data indexing: Electric current 2.20E+00A to 1.10E+02A, Electric current 2.20E+01A, Electric current 2.42E+01A, Electric current 5.28E+01A, Power 1.90E+05W

DOI: 10.6041/j.issn.1000-1298.2025.12.008

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

43. Design and Experiment of Electric Unmanned Agricultural Power Equipment

Accession number: 20255119745596

Title of translation: 电驱无人农用动力装备设计与试验

Authors: Wang, Linze (1, 2); Li, Qingmin (3); Zhou, Kunlei (4); Wen, Changkai (1, 2); Li, Xiaoyu (1, 2); Song, Zhenghe (1, 2); Du, Yuefeng (1, 2)

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) School of Automotive Engineering, Weifang Vocational College, Weifang; 262737, China; (4) Beijing Tsun Greatwall Hydraulic R&D Co., Ltd., Beijing; 100083, China

Corresponding author: Du, Yuefeng(dyf@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 110-120

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of poor terrain adaptability, inflexible movement and insufficient environmental friendliness of the current power equipment, a four-wheel multi-mode steering electric unmanned agricultural power equipment with an articulated frame and an independently driven steering wheel set was proposed to meet the operational needs of sowing, tillage, plant protection, transportation and other links in facility horticultural agricultural production. Firstly, the overall structure of the power equipment consisted of an articulated frame, an independently driven steering wheel set, a central suspension device and an electronic control system. It supported multiple steering modes, including two-wheel steering, four-wheel steering, on-the-spot steering and crab steering. Next, matching calculations were performed on key components of the power system, such as the drive motor, steering motor, PTO motor, and power battery. Subsequently, the dynamic motion characteristics of the agricultural power equipment under various steering modes were analyzed, and a multi-mode dynamic model was established. Finally, a hierarchical drive control method was applied in the mechatronic control system, and multiple field tests were carried out with driving speed, steering performance, climbing performance, stability of tillage depth, and endurance performance as evaluation indices. The test results showed that the equipment achieved an average driving speed of 9.67 km/h, the minimum turning radius of 1 715.5 mm under four-wheel Ackerman steering, the maximum climbing grade was 15°, the coefficient of the tillage depth stability was 94.62%, and the battery runtime was 2.18~2.77 h. The equipment demonstrated excellent steering characteristics, passability, and operational stability, providing theoretical and technical support for the design of advanced small-and medium-sized intelligent agricultural machinery equipment. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Four wheel steering

Controlled terms: Agricultural machinery? - ?All wheel drive vehicles? - ?Automobile steering equipment? - ?Control system stability? - ?Control systems? - ?Cultivation? - ?Electric control equipment? - ?Electric equipment protection? - ?Electric machine control? - ?Electric power system protection ? - ?Machine design? - ?Power control? - ?Secondary batteries? - ?Tillage? - ?Wheels

Uncontrolled terms: Articulated frame? - ?Drive control? - ?Four-wheel drives? - ?Four-wheel steering? - ?Multi-mode drive control? - ?Multimodes? - ?Power equipment? - ?Steering wheel? - ?Wheel-driven power equipment? - ?Wheelsets

Classification code: 601 Mechanical Design? - ?601.2 Machine Components? - ?662.1 Automobiles? - ?662.3 Automobile Components and Materials? - ?702.1.2 Secondary Batteries? - ?704.2 Electric Equipment? - ?706.1 Electric Power Systems? - ?731.1 Control Systems? - ?731.2 Control System Applications? - ?731.3 Specific Variables Control? - ?731.4 Control System Stability? - ?732.1 Control Equipment? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?904 Design

Numerical data indexing: Percentage 9.462E+01%, Size 7.155E-01m, Size 9.67E+03m, Time 7.848E+03s to 9.972E+03s

DOI: 10.6041/j.issn.1000-1298.2025.12.009

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

44. Full-coverage Path Planning Algorithm for Dual-helix Driven Robot in Convex Polygonal Farmlands

Accession number: 20255119732556

Title of translation: 双螺旋驱动式机器人全覆盖作业路径规划算法研究

Authors: Wang, Pei (1); Luo, Jialong (1); Xie, Jiasheng (1); Wang, Jiatao (1); Luo, Hao (2); Ning, Jintai (1); Hu, Lian (1); He, Jie (1)

Author affiliation: (1) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) School of International Education, 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: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 645-656

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the core challenges faced by agricultural robots in autonomous navigation and path planning under complex farmland environments—particularly in irregul?r plots and soft, sticky paddy fields where common issues included low coverage rate, excessive turning redundancy, and poor path continuity, a full-coverage path planning algorithm tailored for convex polygonal farmlands and compatible with dual-helix driven agricultural robots was proposed. The algorithm integrated both the geometric characteristics of the farmland and the kinematic constraints of the robot. The working area was initially divided into a central parallel-working zone and a peripheral contour-following zone, corresponding respectively to strip-based traversal paths and boundary-parallel strip traversal paths. The complete path was further segmented into working and non-working paths, including center-region connection paths, inter-region transitions, contour-parallel region transitions, and entry/exit paths. The methodology for generating each type of path was detailed. An optimal working direction was determined via the “long-side-first” principle for the central region, and the Warnsdorff rule was applied to optimize the sequence of strip traversal. Dubins and Reeds — Shepp path models were introduced to enhance continuity and feasibility during turns. Considering metrics such as path length, computation time, and coverage rate, the algorithm was implemented on a dual-helix driven robot and tested in simulations and field experiments across four typical farmland types : rectangular, trapezoidal, irregul?r quadrilateral, and irregul?r polygonal plots. Experimental results demonstrated that the proposed algorithm achieved a coverage rate between 96. 6 9 % and 97. 8 0 %, with a path overlap rate controlled within 1. 7 7 % ~ 2 . 3 0 % . The generated paths were continuous and boundary-safe, indicating strong execution stability and environmental adaptability. The research result can provide a robust and adaptable path planning Solution for agricultural robots operating in complex environments, with promising engineering feasibility and applieation potential. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Motion planning

Controlled terms: Agricultural robots? - ?Farms? - ?Geometry? - ?Navigation? - ?Robot programming

Uncontrolled terms: Agricultural robot? - ?Autonomous navigation? - ?Coverage path planning? - ?Coverage rate? - ?Dual-helix drive? - ?Full-coverage? - ?Irregular farmland? - ?Navigation and path planning? - ?Paddy fields? - ?Path-planning algorithm

Classification code: 435.1 Navigation? - ?731.5 Robotics? - ?731.6 Robot Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?1101 Artificial Intelligence? - ?1106.1 Computer Programming? - ?1201.14 Geometry and Topology

Numerical data indexing: Percentage 0.00E00%, Percentage 7.00E+00%, Percentage 9.00E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.059

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

45. Online Identification of Hybrid Tractor Tire-soil Interaction Model Based on Multiple Filtering Joint Observation

Accession number: 20255119745610

Title of translation: 基于多重滤波联合观测的混动拖拉机轮土模型在线辨识

Authors: Wang, Shilong (1, 2); Zhao, Jinghui (2); Wu, Xiuheng (1, 2); Zhu, Mingjie (1, 2); Zhao, Xueyan (1, 2); Song, Zhenghe (1, 2)

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

Corresponding author: Wu, Xiuheng(wxh599@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 140-149

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Accurate tire-soil models are fundamental to optimizing the traction force control of hybrid tractors, thereby improving overall energy efficiency. Among these, precise estimation of the longitudinal and vertical forces is crucial for ensuring model identification accuracy. However, during operation, terrain variations and the unknown load changes caused by the interaction between the plow body and the soil lead to significant fluctuations in the longitudinal and vertical forces on each tire, which increases the difficulty of accurate estimation. To address this, a tire-soil interaction model identification method based on the fusion of multiple filters and joint observation was proposed, taking the distributed hybrid electric tractor (DHET) as research object. Firstly, the longitudinal force of the tire was estimated by using the Kalman filter (KF), and the vertical force was estimated by using the cubature Kalman filter (CKF) algorithm combined with the dynamic model. Then, based on the Brixius model and the vehicle’s longitudinal dynamics, an online identification device for the tire-soil model was constructed by using the unscented particle filter (UPF). The unscented transformation (UT) was used to design the particle proposal distribution, preserving higher-order information in the nonlinear tire-soil model, and the particle filter (PF) algorithm was applied to update the estimated parameters, completing the model ‘s online identification. Hardware-in-the-loop (HIL) test results showed that the method can quickly and accurately achieve identification under varying terrain conditions, with a root mean square error not exceeding 1.2. Experimental results indicated that, under two types of soil conditions, the identification model’s boundary traction coefficient error was within ± 0.015, with the front wheel test data distribution accounting for 84.45% and 88.16%, respectively, and the rear wheel data for 86.72% and 85.38%, verifying that this method maintained high accuracy and robustness under different soil conditions. The research findings can provide theoretical support for the optimal drive force distribution strategy of tractors and contribute to improving traction efficiency and fuel economy. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Mean square error

Controlled terms: Automobile testing? - ?Energy efficiency? - ?Fuel economy? - ?Kalman filters? - ?Mathematical transformations? - ?Soil testing? - ?Soils? - ?Traction (friction)? - ?Traction control? - ?Tractors (agricultural) ? - ?Tractors (truck)? - ?Wheels

Uncontrolled terms: Cubature kalman filtering? - ?Electric tractors? - ?Force estimation? - ?Hybrid electric tractor? - ?Interaction modeling? - ?Kalman-filtering? - ?Particle Filtering? - ?Tire-soil interaction? - ?Tire-soil interaction model? - ?Tyre-soil interactions ? - ?Unscented particle filtering? - ?Wheel force estimation

Classification code: 483.1 Soils and Soil Mechanics? - ?522 Fuels? - ?601.2 Machine Components? - ?662 Automobiles and Smaller Vehicles? - ?663.1 Heavy Duty Motor Vehicles? - ?716.1 Information Theory and Signal Processing? - ?731.2 Control System Applications? - ?821.2 Agricultural Machinery and Equipment? - ?1009 Energy Management? - ?1009.1 Energy Conservation? - ?1009.2 Energy Consumption? - ?1201.3 Mathematical Transformations? - ?1202.2 Mathematical Statistics? - ?1301.1.1 Mechanics? - ?1502.1.1.4.3 Soil Pollution Control

Numerical data indexing: Percentage 8.445E+01%, Percentage 8.538E+01%, Percentage 8.672E+01%, Percentage 8.816E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.012

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

46. Frequency Matching Method and Experiment of Variable Stiffness Vibration Energy Feedback Device for Electric Tractor

Accession number: 20255119745578

Title of translation: 电动拖拉机变刚度振动馈能装置频率匹配方法与试验

Authors: Wang, Wei (1); Li, Ziqiang (1); Han, Jialu (1); Zhao, Jie (1)

Author affiliation: (1) College of Mechanical and Electronic 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: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 121-130 and 246

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In allusion to the efficient vibration energy recovery problem of a wheeled electric tractor, a variable stiffness spring was innovatively integrates into the research team’s existing vibration energy feedback device and a method was proposed to match the device’s resonance frequency with the road surface excitation frequency, thereby improving energy capture performance. Firstly, the range of road excitation frequency was analyzed based on the road grade and vehicle speed of the electric tractor. Subsequently, a nonlinear 10-degree-of-freedom dynamic model of the variable stiffness vibration energy feedback device was formulated. With the QR decomposition, implicit restart Arnoldi method (IRAM) and adaptive cross approximation algorithm (ACA), the modal frequencies of the device were solved, and the modal evolution law was analyzed by combining these methods with the finite element method. On this basis, the stiffness coefficient of variable stiffness spring was determined, and the frequency matching method for the variable stiffness vibration energy feedback device was proposed. Finally, fixed-frequency and swept-frequency bench tests were conducted to compare the energy capture performance of the fixed and variable stiffness vibration energy feedback devices. The results demonstrated that the variable stiffness spring structure significantly broadened the resonance band of the device, increased the maximum instantaneous output voltage to 52.2 V, and boosted the average output power and electricity generation by 34.4% and 42.8%, respectively, at the same time, it met the vibration reduction requirement for the battery pack. The above research can provide theoretical and technical support for the power supply of electric tractors and it was of great significance to promote the development of its energy-saving technology. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Approximation algorithms

Controlled terms: Battery Pack? - ?Degrees of freedom (mechanics)? - ?Electric excitation? - ?Energy conservation? - ?Evolutionary algorithms? - ?Feedback? - ?Finite element method? - ?Modal analysis? - ?Roads and streets? - ?Springs (components) ? - ?Stiffness? - ?Tractors (agricultural)? - ?Tractors (truck)? - ?Vibrations (mechanical)

Uncontrolled terms: Electric tractors? - ?Energy capture? - ?Energy feedbacks? - ?Feedback device? - ?Frequency matching? - ?Matching methods? - ?Variable stiffness? - ?Variable stiffness spring? - ?Vibration energies? - ?Vibration energy capture

Classification code: 214 Materials Science? - ?406.2 Roads and Streets? - ?601.2 Machine Components? - ?663.1 Heavy Duty Motor Vehicles? - ?701.1 Electricity: Basic Concepts and Phenomena? - ?702.1.2 Secondary Batteries? - ?731 Automatic Control Principles and Applications? - ?821.2 Agricultural Machinery and Equipment? - ?1009.1 Energy Conservation? - ?1106.1 Computer Programming? - ?1201.5 Computational Mathematics? - ?1201.9 Numerical Methods? - ?1301.1.1 Mechanics

Numerical data indexing: Percentage 3.44E+01%, Percentage 4.28E+01%, Voltage 5.22E+01V

DOI: 10.6041/j.issn.1000-1298.2025.12.010

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

47. Design and Experiment of a Hydraulic Control Depth Wheel with Terrain-Following Feature for No-till Seeders in Stubble Field

Accession number: 20255119745617

Title of translation: 原茬地免耕播种机液控式仿形限深地轮设计与试验

Authors: Wang, Xing (1); Tang, Hongguang (1); Liu, Xinhao (1); Chen, Haitao (1, 2)

Author affiliation: (1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) College of Mechanical and Electronic Engineering, East University of Heilongjiang, Harbin; 150066, China

Corresponding author: Chen, Haitao(htchen@neau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 211-222

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address issues with traditional mechanical adjustment methods for no-till precision planters in stubble fields, such as the ground wheel assembly’s inability to adapt to terrain changes, leading to unstable residue clearing performance and increased wheel slip, a hydraulically controlled terrain-following depth-limiting ground wheel assembly was designed. Its hydraulic system enabled rapid adjustment of wheel height while maintaining a constant position, ensuring stable furrow opener depth. The cushioning spring reduced ground-induced impacts transmitted to the planter, enhancing the stability of the residue clearing device. Through theoretical analysis, the main structural parameters of the terrain-following depth-limiting ground wheel assembly were determined. Simulation tests identified the optimal stiffness of the cushioning spring as 1.2×105 N/m. Comparative field trials demonstrated that the hydraulically controlled terrain-following depth-limiting ground wheel assembly operated stably with lower slip rates. When the furrow opener depth qualification criterion was set at (50±10) mm, the qualification rates for opener soil penetration depth were 62% and 82% for the mechanically-adjusted ground wheel assembly and hydraulic-controlled terrain-following depth-control wheel assembly, respectively. The hydraulic assembly exhibited a 20 percentage point higher qualification rate than the mechanical assembly. Furthermore, the hydraulic terrain-following wheel demonstrated significantly lower slip rates. While both adjustment methods showed increasing slip rates with the rise of operating speeds, the hydraulic terrain-following wheel exhibited a smaller rate of increase. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Landforms

Controlled terms: Agricultural machinery? - ?Agriculture? - ?Hydraulic equipment? - ?Hydraulic machinery? - ?Vehicle wheels

Uncontrolled terms: Adjustment method? - ?Furrow openers? - ?Ground wheels? - ?Hydraulic control? - ?No-till? - ?No-tillage planter? - ?Slip rates? - ?Terrain following? - ?Wheel assembly? - ?Wheel with terrain-following feature

Classification code: 481.1 Geology? - ?601.2 Machine Components? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?1401.2 Hydraulic Equipment and Machinery

Numerical data indexing: Percentage 6.20E+01%, Percentage 8.20E+01%, Surface tension 1.20E+05N/m

DOI: 10.6041/j.issn.1000-1298.2025.12.019

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

48. Review of Key Technologies in Hybrid Tractor

Accession number: 20255119745639

Title of translation: 混合动力拖拉机关键技术研究综述

Authors: Wen, Changkai (1, 2); Zhao, Zihao (1); Xie, Bin (1, 2); Xiang, Shunan (3); Du, Yuefeng (1, 2); Wu, Xiuheng (1, 2); Peng, Peng (3); Song, Zhenghe (1, 2)

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) China Agricultural Mechanization Center, Ministry of Agriculture and Rural Affairs, Beijing; 100122, China

Corresponding author: Song, Zhenghe(songzhenghe@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 1-23

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Energy saving and emission reduction is the key to improve quality and efficiency, transformation and upgrading of intelligent agricultural machinery and equipment. Hybrid tractor is the key model for the development of the global new energy agricultural machinery and equipment industry, and it is also the key technology path to accelerate the transformation of Chinese agricultural machinery to high-end, intelligent and green. In recent years, domestic and foreign combined with local agricultural production characteristics, market demand-oriented, continued to spawn, iterative new technology and new products, and through multi-scene, multi-level demonstration and application, a complete technology research and development and application system was gradually formed, which accelerated the promotion of product maturity. On the basis of outlining the development history and development characteristics of hybrid tractors, the development status of key technologies in this field was summarized and analyzed from four aspects: design and development, power control, intelligence and test verification, which focused on analyzing the technological differences between domestic and foreign models, and the key issues restricting the development of the field were pointed out. Finally, under the background of policy guidance and technological innovation synergy, it looked forward to the development direction of the hybrid tractor industry from the perspective of agricultural modernization empowered by artificial intelligence, big data and other emerging technologies, and puted forward its future development trend in the optimized design of the whole machine, collaborative optimization and control, special performance test equipment, intelligent operation control and other aspects. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 126

Main heading: Tractors (agricultural)

Controlled terms: Agriculture? - ?Energy conservation? - ?Equipment testing? - ?Iterative methods? - ?Modernization? - ?Smart agriculture

Uncontrolled terms: Agricultural productions? - ?Energy-saving and emission reductions? - ?Equipment industries? - ?Experimental validations? - ?Hybrid tractor? - ?Key models? - ?Key technologies? - ?Machinery industry? - ?New energies? - ?Research and application

Classification code: 821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?901 Engineering Profession? - ?942.2.1 Testing Devices and Equipment? - ?1009.1 Energy Conservation? - ?1201.9 Numerical Methods

DOI: 10.6041/j.issn.1000-1298.2025.12.001

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

49. Counting and Spatial Distribution of Camellia oleifera Fruits Based on YOLO-LGC

Accession number: 20255119745606

Title of translation: 基于 YOLO-LGC 的油茶果计数及空间定位分布

Authors: Wu, Delin (1, 2); Liu, Yinghao (1); Huang, Keyue (1); Li, Gonglei (1); Jiang, Jie (1); Wang, Rongyan (1, 2)

Author affiliation: (1) College of Engineering, Anhui Agricultural University, Hefei; 230036, China; (2) Anhui Provincial Engineering Research Center for Intelligent Agricultural Machinery Equipment, Hefei; 230036, China

Corresponding author: Wang, Rongyan(wry@ahau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 568-580

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Deep learning methods are widely applied in agricultural vision tasks. Determining harvesting parameters is a primary task for the mechanized harvesting of Camellia oleifera fruits, and automated fruit detection and object counting based on deep learning are crucial for accurately setting these parameters. However, factors such as occlusion and illumination variations in complex orchard environments directly affect the efficiency and accuracy of detection methods. An efficient, lightweight model named YOLO - LGC was proposed based on YOLO 11n, aiming to enhance target detection accuracy and spatial localization capability in complex orchard environments. Firstly, the LNN ghost dynamic convolution (LGC) module was introduced into the backbone network to optimize feature extraction through adaptive kernel selection, thereby improving detection accuracy in complex environments. Secondly, the programmable gradient information (PGI) mechanism was adopted to dynamically adjust gradient propagation, addressing feature conflicts caused by occlusion and illumination changes. Finally, the Dynamic UpSample module was integrated, guided by PGI, to enhance feature retention and improve spatial localization accuracy. Combined axis-aligned bounding boxes (AABB), an inertial measurement unit (IMU), and Kalman filtering to visualize the spatial distribution of Camellia oleifera fruits at heights of 0 ~ 1.5 m, 1.5 ~1.8 m, and above 1.8 m. By analyzing the spatial relationships of the fruits, more accurate positional information was provided. Experimental results showed that compared with YOLO 11n, YOLO - LGC improved detection precision from 82.0% to 83.0%, recall from 76.4% to 78.0%, mAP@ 0.5 from 85.1% to 87.6%, and FPS from 229.8 f/s to 299.7 f/s, with computational complexity slightly increased to 6.7 × 10°. While maintaining the advantage of high inference speed, YOLO - LGC enhances detection performance, outperforming existing mainstream detection methods. The spatial distribution error rate was less than 5%, meeting practical detection requirements. The findings can provide a basis for matching mechanized harvesting parameters for Camellia oleifera fruits. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Deep learning

Controlled terms: Complex networks? - ?Convolution? - ?Feature extraction? - ?Fruits? - ?Harvesting? - ?Learning systems? - ?Object detection? - ?Orchards? - ?Spatial distribution

Uncontrolled terms: Camellia oleifera? - ?Camellia oleifera fruits? - ?Deep learning? - ?Detection methods? - ?Harvesting parameters? - ?Mechanized harvesting? - ?Object counting? - ?Orchard environment? - ?Spatial localization? - ?YOLO - LNN ghost dynamic convolution

Classification code: 716.1 Information Theory and Signal Processing? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1101.2 Machine Learning? - ?1101.2.1 Deep Learning? - ?1105 Computer Networks? - ?1106.8 Computer Vision? - ?1201 Mathematics

Numerical data indexing: Percentage 5.00E+00%, Percentage 7.64E+01% to 7.80E+01%, Percentage 8.20E+01% to 8.30E+01%, Percentage 8.51E+01% to 8.76E+01%, Size 0.00E00m to 1.50E+00m, Size 1.50E+00m to 1.80E+00m, Size 1.80E+00m

DOI: 10.6041/j.issn.1000-1298.2025.12.052

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

50. Effects of Reduced Nitrogen Fertilizer with Topdressing on Peanut Growth and Osmotic Adjustment Substances under Mulched Drip Irrigation in Sandy Areas

Accession number: 20255119732573

Title of translation: 氮肥减量追施对风沙区膜下滴灌花生生长与渗透调节物质的影响

Authors: Xia, Guimin (1); He, Shenghui (1); Xu, Zhengfei (2); Wu, Yi (1); Zheng, Junlin (1); Chi, Daocai (1)

Author affiliation: (1) College of Water Conservancy, Shenyang Agricultural University, Shenjang, 110866, China; (2) Water Conservaney Bureau of Lianjungang City, Jiang.su Provinee, Lianyungang; 222000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 687-696

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to investigate the effects of redueed nitrogen fertilizer with topdressing on growth and osmoregulatory substances in peanut under mulched drip irrigation, a split-plot experiment was conducted at the Aerxiang Irrigation Experimental Station in Liaoning Provinee from May to October in 2023 and 2024. The effects of different nitrogen application modes (NO, no nitrogen; Nl, 25% nitrogen reduetion with single application; SN1, 25% nitrogen reduetion with three times application; and N2, conventional nitrogen rate with single application) on main stem height, root morphology, osmoregulatory substances, yield, and water use efficiency of peanuts under mulched drip irrigation (IMD1) and drip irrigation (ICK) were analyzed. Results indicated that in 2023 and 2024, the IMm treatment consistently exhibited greater main stem height than I(K treatment across all nitrogen modes. SN1 obtained the highest main stem height, and followed by N2 and Nl, NO had the lowest main stem height. During the flowering and pod setting stage, the IMmSNl treatment achieved the optimal root morphology. In 2023, at the flowering stage, compared with IMD1N1 and IMD1N2 treatments, the IMD1SN1 treatment increased root length by 43. 9% and 36. 6%, respectively. In 2024, at the flowering stage, compared with the IMD1N1 and IMmN2 treatments, the IMDISN1 treatment enhanced root surface area by 52. 2% and 17. 3%, and root volume by 49.5% and 25.0%, respectively. Compared with the ICKN2 treatment, the IMDISN1 treatment increased root length and root volume by 41. 8% and 45. 5%, respectively. Under drought stress, SN1 treatment had the highest proline content, and followed by Nl and N2 treatment, the NO treatment had the lowest proline content. During the pod setting stage in 2024, compared with the IMD1N1 and IMD1N2 treatments, the IMmSNl treatment increased proline content by 18. 1% and 34.8%, respectively. During the pod setting stage in 2024, the N2 treatment had the highest soluble protein content and followed by the SN1 and Nl treatment, the NO treatment had the lowest soluble protein content, the IMD1N2 treatment had 27. 4% and 40. 6% higher soluble protein content than the IMDISN1 and IMD1N1 treatments, respectively. During the flowering stage in 2024, the SN1 treatment obtained the highest soluble sugar content, and followed by the Nl and N2 treatment, the NO treatment had the lowest soluble sugar content, compared with the IMDIN1 and IMDIN2 treatments, the IMDISN1 treatment increased soluble sugar content by 30. 3% and 40.0%, respectively. The IMm treatment had higher peanut yield than the ICK treatment, but the IMDISN1 treatment had similar peanut yield with ICKN2 treatment. Compared with the ICKN2 treatment, the IMDI SN1 treatment increased water use efficiency by 32. 3% (2023) and 41. 1% (2024), respectively. Thus, reducing nitrogen rate by 25% with three split applications under mulched drip irrigation (IMDISN1) could improve water and nitrogen utilization, enhance osmoregulation during the critical water requirement stages, and ultimately promote peanut yield. These findings could provide theoretical basis for water-saving and nitrogen reduction in peanut production in sandy regions. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Nitrogen fertilizers

Controlled terms: Drought? - ?Efficiency? - ?Morphology? - ?Nitrogen? - ?Nitrogen oxides? - ?Oilseeds? - ?Plants (botany)? - ?Subirrigation

Uncontrolled terms: Flowering stage? - ?Mulched drip irrigations? - ?Nitrogen fertilizer optimization? - ?Optimisations? - ?Osmoregulation substance? - ?Peanut? - ?Protein contents? - ?Soluble proteins? - ?Stem height? - ?Water-nitrogen coupling

Classification code: 103 Biology? - ?214 Materials Science? - ?443.3 Precipitation? - ?444 Water Resources? - ?804 Chemical Products? - ?804.2 Inorganic Compounds? - ?821.3 Agricultural Chemicals? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?913.1 Production Engineering

Numerical data indexing: Percentage 1.00E00%, Percentage 2.00E+00%, Percentage 2.50E+01%, Percentage 3.00E+00%, Percentage 3.48E+01%, Percentage 4.00E+00%, Percentage 4.00E+01%, Percentage 4.95E+01%, Percentage 5.00E+00%, Percentage 6.00E+00%, Percentage 8.00E+00%, Percentage 9.00E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.063

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

51. Quantitative Detection of Conidiophores and Sporangium of Cucumber Downy Mildew Based on Improved YOLO v8s-OBB

Accession number: 20255219795521

Authors: Zhang, Yiding (1); Qiao, Chen (2); Zhang, Lingxian (2); Han, Zonghuan (2)

Corresponding author: Qiao, Chen(649112905@qq.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 479-489

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Cucumber downy mildew is a fungal disease that severely threatens cucumber production and quality. Quantitative detection of sporangia and conidiophores is crucial for early disease prevention. However, traditional horizontal bounding box detection methods cannot accurately detect these features due to their diverse morphology and orientations. Therefore, an improved YOLO v8s-OBB detection method was proposed by introducing the convolutional block attention module (CBAM) and the lightweight shared convolution detection head (LSCD) module. The aim was to enhance the detection efficiency and accuracy of sporangia and conidiophores of cucumber downy mildew. By incorporating CBAM, the model’s ability to identify key features was enhanced, allowing it to focus more on critical regions in microscopic images and improve the detection of small targets. The LSCD integrated multi-scale features through shared convolution operations, enhancing the model’s detection performance for targets of different sizes while reducing computational costs, making it suitable for resource-constrained environments. The rotated bounding box technique accurately captured sporangia and conidiophores ‘ inclination and rotation postures. Experimental results showed that, compared with the original YOLO v8s-OBB model, the improved YOLO v8s-OBB model not only reduced the model size but also achieved superior detection performance for sporangia and conidiophores of cucumber downy mildew, with precision, recall, and mAP@ 0.5 reaching 96.0%, 90.1%, and 96.5%, respectively. The improved YOLO v8s-OBB model outperformed advanced rotated object detection models such as S2ANet, H2RBox, and R2CNN in detection accuracy. The research result can validate the effectiveness of the improved model in practical applications and provide technical support for the early diagnosis of cucumber downy mildew. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Feature extraction

Controlled terms: Coarse-grained modeling? - ?Convolution? - ?Diagnosis? - ?Morphology? - ?Object detection? - ?Plant diseases

Uncontrolled terms: Conidiophore? - ?Convolutional block attention module? - ?Cucumber downy mildews? - ?Detection accuracy? - ?Detection methods? - ?Detection performance? - ?Lightweight shared convolution detection head? - ?Quantitative detection? - ?Sporangium? - ?YOLO v8s-OBB

Classification code: 102.1 Medicine? - ?103 Biology? - ?214 Materials Science? - ?716.1 Information Theory and Signal Processing? - ?1101.2 Machine Learning? - ?1106.5 Computer Applications? - ?1106.8 Computer Vision? - ?1301.5 Condensed Matter Physics

Numerical data indexing: Percentage 9.01E+01%, Percentage 9.60E+01%, Percentage 9.65E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.044

Funding Details: Number: 62176261, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: National Natural Science Foundation of China (62176261)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

52. Effects of Irrigation Amount and Frequency on Photosynthetic Fluorescence Characteristics, Fruit Yield and Quality of Drip-irrigated Greenhouse Tomato

Accession number: 20255119732569

Title of translation: 滴灌水量和灌溉频率对温室番茄光合荧光特性与产量品质的影响

Authors: Bai, Zhentao (1); Zhang, Hongxin (1); Fan, Junliang (1); Cao, Hongxia (1); Li, Zhijun (1); Zhang, Fucang (1)

Author affiliation: (1) Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&E 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: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 677-686

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In o r d e r to optimize t h e irrigation System of tomato u n d e r film d r i p irrigation in solar greenhouse in Northwest China, two experiments in spring and autumn in 2023 were conducted, four irrigation amounts (Wl : 125% ET,,, W 2 : 100% E T,, W3 : 7 5 % E T,, W 4 : 5 0 % ET,,, ET,, is crop evapotranspiration) and three irrigation frequencies (D l; every 4 days, D2; every 7 days, D3: every 10 days) were set, and the effects of irrigation amount and irrigation frequeney on soil moisture content distribution, root arehitecture, photosynthetic fluorescence characteristics, yield quality and water productivity of tomatoes were systematically evaluated. The results showed that irrigation amount and irrigation frequency had significant effects on root arehitecture, photosynthetic fluorescence characteristics, yield quality and water productivity (P ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 39

Main heading: Fruits

Controlled terms: Crops? - ?Efficiency? - ?Fluorescence? - ?Forestry? - ?Photosynthesis? - ?Plants (botany)? - ?Quality control? - ?Soil moisture? - ?Soil quality? - ?Subirrigation

Uncontrolled terms: Comprehensive evaluation? - ?Drip irrigation? - ?Drip irrigation under film mulch? - ?Irrigation amounts? - ?Irrigation systems? - ?Root system? - ?Root system architecture? - ?Systems architecture? - ?Tomato? - ?Water productivity

Classification code: 103 Biology? - ?483.1 Soils and Soil Mechanics? - ?741.1 Light/Optics? - ?802.2 Chemical Reactions? - ?821.1 Woodlands and Forestry? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?913.1 Production Engineering? - ?913.3 Quality Assurance and Control

Numerical data indexing: Age 1.096E-02yr, Age 1.918E-02yr, Age 2.74E-02yr, Percentage 0.00E00%, Percentage 1.00E+02%, Percentage 1.25E+02%, Percentage 4.00E+00%, Percentage 5.00E+00%, Percentage 8.00E+00%, Size 0.00E00m

DOI: 10.6041/j.issn.1000-1298.2025.12.062

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

53. Study of Leveling Control System for Transplanters Based on Super-twisting Sliding Mode Active Disturbance Rejection

Accession number: 20255119745581

Title of translation: 基于超螺旋滑模自抗扰的移栽机调平控制系统研究

Authors: Chang, He (1, 2); Liu, Lijing (1, 2); Cui, Wei (1, 2); Liu, Fangjian (1, 2); Zhang, Xuedong (1, 2); Wang, Chunzhe (3)

Author affiliation: (1) Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing; 100083, China; (2) State Key Laboratory of Agricultural Equipment Technology, Beijing; 100083, China; (3) Beijing Dater Integrated Technology Co., Ltd., Beijing; 100083, China

Corresponding author: Cui, Wei(cuiwei607@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 247-258

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to enhance the operational adaptability of transplanters in hilly and mountainous terrain, as well as improve the quality and stability of their performance on slopes, a leveling control system based on super-twisting sliding mode active disturbance rejection control (STSMC-ADRC) was proposed for a previously developed transplanter. This system enabled real-time lateral leveling control of the transplanter operating along contour lines. A mathematical model of the servo-electric cylinder control was established according to the overall structure and leveling control principle of the transplanter to describe and analyze the dynamic performance indicators of the system. Based on the mathematical model of the servo-electric cylinder, which provided the driving force for leveling the transplanter, a super-twisting sliding mode active disturbance rejection controller was designed. Lyapunov stability analysis was conducted for the designed controller in combination with the established control system. A co-simulation platform using Matlab/Simulink and ADAMS was constructed to compare the performance of the proposed STSMC-ADRC with classical PID control and active disturbance rejection control (ADRC) under static conditions. The results indicated that under static leveling conditions, the leveling time with ADRC was approximately 29.5% shorter than that with PID control, while the STSMC-ADRC strategy reduced the leveling time by approximately 46.3% compared with PID control. Finally, static single-side bridge tests and field dynamic tests were conducted. The dynamic test results demonstrated that the STSMC-ADRC control algorithm performed the best in experiments conducted at speeds of 0.2 m/s, 0.3 m/s, and 0.4 m/s, with root mean square errors of 0.77°, 1.94°, and 2.32°, respectively, outperforming both ADRC and PID control algorithms. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Disturbance rejection

Controlled terms: Control system analysis? - ?Control system stability? - ?Controllers? - ?Cylinders (shapes)? - ?Electric machine control? - ?Leveling (machinery)? - ?MATLAB? - ?Proportional control systems? - ?Quality control? - ?Simulation platform ? - ?Sliding mode control

Uncontrolled terms: Active disturbances rejection controls? - ?Automatic leveling? - ?Hilly terrains? - ?Leveling control systems? - ?Levelings? - ?Mountainous terrain? - ?Sliding modes? - ?Super- twisting? - ?Super-twisting sliding mode active disturbance rejection control? - ?Transplanter

Classification code: 408.1 Structural Members and Shapes? - ?731 Automatic Control Principles and Applications? - ?731.1 Control Systems? - ?731.2 Control System Applications? - ?731.4 Control System Stability? - ?732.1 Control Equipment? - ?913.3 Quality Assurance and Control? - ?1106.5 Computer Applications? - ?1201.5 Computational Mathematics? - ?1201.12 Modeling and Simulation

Numerical data indexing: Percentage 2.95E+01%, Percentage 4.63E+01%, Velocity 2.00E-01m/s, Velocity 3.00E-01m/s, Velocity 4.00E-01m/s

DOI: 10.6041/j.issn.1000-1298.2025.12.022

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

54. Design and Testing of Cutting and Squeezing Combination Peanut Digging and Harvesting Device for Saline Soils

Accession number: 20255119745605

Title of translation: 盐碱地土壤切挤组合式花生挖掘收获装置设计与试验

Authors: Chang, Zengcun (1); Wang, Dongwei (2); Zhao, Zelong (3); Xi, Chuanzhi (4); Liu, Zeqi (4); Hou, Jialin (1)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Shandong Agricultural University, Tai’an; 271018, China; (2) Yellow River Delta Intelligent Agricultural Machinery Equipment Industry Academy, Dongying; 257300, China; (3) Qingdao Agricultural Machinery Production and Distribution Association, Qingdao; 266109, China; (4) College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao; 266109, China

Corresponding author: Hou, Jialin(jlhou@sdau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 331-342

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the saline peanut harvesting process in the traditional shovel pole type excavation and harvesting device exists in the soil crushing effect is poor, the root and pod part of the soil content rate is high, the excavation operation resistance is large and has other problems. Combining saline soil characteristics and peanut planting agronomic requirements, a cutting and squeezing combined excavation device was designed. A mechanical model for the cutting and squeezing forces of the digging device and a mechanical model for the fragmentation and separation of the peanut root-pod-soil aggregates were established. The main factors affecting the operational performance of the digging device were identified as the blade surface inclination angle of the digging shovel, the blade edge angle of the digging shovel, and the radius of the squeezing roller. The value ranges for these parameters were analyzed and determined. Simulation experiments were conducted by using EDEM software to investigate the dynamic changes in peanut root-pod-soil aggregates during the operation of the digging device. Single-factor experiments were used to determine the influence level of each factor on operational resistance and the soil adhesion rate on the root-pod system. Using operational resistance and soil adhesion rate as evaluation indicators, a quadratic regression orthogonal rotational composite experiment was carried out by employing the central composite design (CCD) method. The optimal operational parameter combination was determined as digging shovel blade surface inclination angle of 22°, digging shovel blade edge angle of 50°, and squeezing roller radius of 110 mm. Under these parameters, the soil adhesion rate on the root-pod system was 48.86%, and the machine operational resistance was 15 696.3 N. Field trial results demonstrated that the cutting-squeezing combined peanut digging device achieved a post-operation soil adhesion rate on the root-pod system of 53.61% and an operational resistance of 15 965.57 N. Compared with the original digging device, this represented a reduction of 21.58 percentage points in the soil adhesion rate on the harvested root-pod system and a reduction of 5.57% in operational resistance, indicating superior performance. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Oilseeds

Controlled terms: Adhesion? - ?Aggregates? - ?Computer software? - ?Excavation? - ?Harvesting? - ?Plants (botany)? - ?Rollers (machine components)? - ?Soils

Uncontrolled terms: Adhesion rate? - ?Combination cutting and extrusion? - ?Digging and harvesting device? - ?Digging shovels? - ?EDEM? - ?Field trial? - ?Harvesting devices? - ?Peanut harvester? - ?Saline soil? - ?Soil adhesion

Classification code: 103 Biology? - ?214 Materials Science? - ?217.2.2 Concrete Reinforcements? - ?405.2 Construction Methods? - ?483.1 Soils and Soil Mechanics? - ?601.2 Machine Components? - ?605.2 Small Tools, Unpowered? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1106.9 Computer Software

Numerical data indexing: Force 6.963E+02N, Force 9.6557E+02N, Percentage 4.886E+01%, Percentage 5.361E+01%, Percentage 5.57E+00%, Size 1.10E-01m

DOI: 10.6041/j.issn.1000-1298.2025.12.030

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

55. Non-destructive Detection of Pomelo Granulation Disease Based on Near-infrared Transmission Spectroscopy and Convolutional Neural Networks

Accession number: 20255119745627

Title of translation: 基于近红外透射光谱与卷积神经网络的蜜柚枯水病无损检测方法

Authors: Chen, Junjie (1, 2); Zhu, Wenjie (1, 2); Zhao, Zehua (2); Li, Jiaqi (2); Wang, Qingyan (2, 3); Huang, Wenqian (2, 3)

Author affiliation: (1) School of Agricultural Engineering, Jiangsu University, Zhenjiang; 212013, China; (2) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Science, Beijing; 100097, China; (3) National Research Center of Intelligent Equipment for Agriculture, Beijing; 100097, China

Corresponding author: Huang, Wenqian(huangwq@nercita.org.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 470-478

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Granulation is a common post-harvest disease of citrus fruits, particularly in pomelos. When this disease occurs, it will affect the taste of pomelo fruits and even make them lose their edible value. Pomelos are large, thick-skinned fruits which are difficult to visually detect their internal granulation. The rapid, non-destructive detection of granulation of pomelos was explored by using near-infrared transmission spectroscopy combined with one-dimensional convolutional neural networks. A self-developed visible-near-infrared full-transmission spectroscopy measurement system was used to collect data from red-flashed pomelos. Data were collected in the 562.03 ~ 1 110.16 nm range under short integration mode. Without spectral preprocessing, the Kennard - Stones algorithm divided samples into training and testing sets. Subsequently, a one-dimensional convolutional neural network model for pomelo dryness identification was established. The network had a seven-layer structure. Testing showed that the model achieved a classification accuracy of 98.15% for granulation levels. Compared with traditional models such as backpropagation neural network (BPNN), kernel extreme learning machine (K-ELM), and extreme gradient boosting tree (XGBoost), which used raw spectral data and polynomial smoothing processing (SG) and competitive adaptive reweighted sampling (CARS) to extract feature variables. Finally, data augmentation further validated the model’s stability. The proposed convolutional neural network model effectively identified internal granulation without complex preprocessing. It can select effective information during the spectral processing, greatly improving the model identification efficiency. The researh provided a reference for the application of deep learning methods to achieve rapid and accurate non-destructive identification of the internal granulation level of pomelo. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Granulation

Controlled terms: Backpropagation? - ?Citrus fruits? - ?Convolution? - ?Convolutional neural networks? - ?Data handling? - ?Deep learning? - ?Infrared devices? - ?Infrared transmission? - ?Learning systems? - ?Near infrared spectroscopy ? - ?Network layers

Uncontrolled terms: Convolutional neural network? - ?Infrared: spectroscopy? - ?Near Infrared? - ?Near-infrared? - ?Near-infrared transmission spectroscopy? - ?Nondestructive detection? - ?One dimension? - ?One-dimension convolutional neural network? - ?One-dimensional? - ?Red-fleshed honey pomelo

Classification code: 716.1 Information Theory and Signal Processing? - ?741 Light, Optics and Optical Devices? - ?741.3 Optical Devices and Systems? - ?802.3 Chemical Operations? - ?821.5 Agricultural Products? - ?1101.2 Machine Learning? - ?1101.2.1 Deep Learning? - ?1105 Computer Networks? - ?1106.2 Data Handling and Data Processing? - ?1301.1.3.1 Spectroscopy

Numerical data indexing: Percentage 9.815E+01%, Size 1.1016E-07m

DOI: 10.6041/j.issn.1000-1298.2025.12.043

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

56. Parameter Calibration and Experiment Verification of Shrimp Feed Pellet Based on Discrete Element Method

Accession number: 20255119731904

Title of translation: 基于离散元仿真的颗粒虾饲料参数标定与试验

Authors: Chen, Leilei (1); Shen, Kaiqi (1); Li, Jun (1); Wan, Hongxiang (2); Cao, Chang (2); Hu, Qingsong (1); Li, Zhijian (1)

Author affiliation: (1) College of Engineering Seienee and Technology, Shanghai Ocean University, Shanghai; 201306, China; (2) Foreign Economic Cooperation Center, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 750-760

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to improve the Performance and aecuraey of discrete element method Simulation optimization in the processes of blanking, conveying, and mechanical spreading of the shrimp feed pellet, the intrinsic parameters of the shrimp feed pellet, the contact parameters between feed, the contact Parameters between feed and equipment were systematically calibrated. Taking Tongwei’s columnar sinking shrimp feed pellet as research objeet, the DEM Simulation parameters of the shrimp feed pellet were calibrated by combining physical and Simulation experiments. Firstly, by using the physical test method, the density, Poisson’s ratio, elastic modulus and shear modulus of the shrimp pelleted feed were measured to be 1 177. 68 kg/m, 0. 2 6, 114. 77 MPa and 45. 58 MPa, respectively through instruments such as high precision digital calipers, electronic balances and pressure testing machines. Through inclined plane method and rebound method, the static friction coefficient, rolling friction coefficient, and restitution coefficient between the shrimp feed pellet and 304 stainless steel were determined to be 0. 607, 0. 097 and 0. 35, respectively. The average stacking angle of the shrimp feed pellet was found to be 2 6 . 9 3 °, and the feed’s area coverage on a steel plate was 1 3 . 3 2 % through stacking tests. Secondly, based on the Plackett — Burman experiment, the factors significantly affecting the physieal stacking angle and area proportion were screened out to be the static friction eoefficient between feed, the rolling friction coeffieient between feed, and the static friction eoefficient between feed and 304 stainless steel. Based on this foundation, the steepest ascent experiment was applied to converge the optimization r?nge, and the parameter optimization was carried out by fitting the regression equation between the significant influencing factors and the response values through the Box — Behnken Design experiment. The optimal Parameters combination were obtained as follows; the static friction eoefficient between feed was 0. 207, the rolling friction eoefficient between feed was 0. 150, and the static friction eoefficient between feed and 304 stainless steel was 0. 607. Finally, the reliability of the parameters was verified through stacking tests and spiral blanking tests. The findings revealed that the simulated stacking test results were statistically indistinguishable from the physieal counterparts, as confirmed by a double-sample ?-test. Furthermore, the correlation eoefficient between the simulated and physieal tests for the discharge amount line under varying speeds was an impressive 0. 997, signifying a highly consistent trend with a discrepancy in discharge amount of less than 3% across all speeds. These results underscored the reliability of the calibrated DEM parameters for shrimp pellet feed, thereby establishing a solid data foundation and scientific rationale for investigating the motion meohanisms of shrimp feed pellets and optimizing equipment designs within DEM simulations. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Shellfish

Controlled terms: Calibration? - ?Conveying? - ?Digital instruments? - ?Elastic moduli? - ?Electronic equipment testing? - ?Instrument testing? - ?Pelletizing? - ?Steel testing? - ?Stiction? - ?Tribology

Uncontrolled terms: 304 stainless steel? - ?Contact parameters? - ?DEM Simulation? - ?Discrete dement method? - ?Parameters calibrations? - ?Rolling friction? - ?Shrimp feed pellet? - ?Stacking test? - ?Stackings? - ?Static friction

Classification code: 103 Biology? - ?202.5.3 Steel? - ?214.1.3 Elasticity, Plasticity, Creep and Deformation? - ?601 Mechanical Design? - ?606 Lubrication and Tribology? - ?692.1 Conveyors? - ?802.3 Chemical Operations? - ?942.1 Instruments? - ?942.2.1 Testing Devices and Equipment

Numerical data indexing: Linear density 6.80E+01kg/m, Percentage 2.00E+00%, Percentage 3.00E+00%, Pressure 5.80E+07Pa, Pressure 7.70E+07Pa

DOI: 10.6041/j.issn.1000-1298.2025.12.069

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

57. Research of Prescription Map-based Variable Rate Fertilization System for Rice and Wheat with Spatio-temporal Coupling Compensation Method

Accession number: 20255119745669

Title of translation: 基于时空耦合补偿的处方图式稻麦变量施肥系统研究

Authors: Ding, Youqiang (1); Qi, Bing (1); Wang, Yunxia (1); Deng, Yue (1); Amantayev, Maxat (1, 2); Zhang, Wenyi (1)

Author affiliation: (1) Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing; 210014, China; (2) Akhmet Baitursynuly Kostanay Regional University, Kostanay; 110000, Kazakhstan

Corresponding author: Zhang, Wenyi(zwy-yxkj@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 279-288 and 300

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issues of resource waste and environmental pollution caused by uniform fertilization in traditional methods, as well as the inadequate adaptability of existing variable-rate fertilization systems’lag compensation approaches, a prescription map-based variable-rate fertilization system for rice and wheat featuring spatio-temporal coupling compensation function was designed. The system employed an STM32F407 chip and CAN bus architecture for the control unit and central processor. Integrated with ArcMap GIS platform, it proposed a digital prescription map generation method based on agronomic expert decisions. The developed human-machine interface software supported GPS message reception/parsing, prescription map loading, and high-efficiency retrieval. Innovatively, a spatio-temporally coupled calibration model for fertilizer application adjustment was established through dynamic outlet positioning modeling and lag time self-learning algorithm, enabling automatic field calibration and dynamic compensation of system response time. Bench tests demonstrated that the self-learning algorithm achieved over 90.5% accuracy across working speeds (4~8 km/h) and fertilization gradients (0~450 kg/hm2, 0~750 kg/hm2, 450~750 kg/hm2). Field trials showed that with spatio-temporal calibration enabled, the average fertilization accuracy reached 97.4% within 50-meter segments-an 8.0 percentage points improvement over non-calibrated status-while maintaining only 2.5 percentage points accuracy fluctuation at 8 km/h. This system provided a high-precision, low-cost intelligent solution for variable-rate fertilization in rice/wheat cultivation, offering technical support for China’s national policy of reducing fertilizer use while increasing efficiency. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Control systems

Controlled terms: Agricultural machinery? - ?Calibration? - ?Cultivation? - ?Fertilizers? - ?Learning algorithms? - ?Learning systems? - ?Man machine systems

Uncontrolled terms: Arcmap? - ?Fertilisation? - ?Percentage points? - ?Prescription map? - ?Self learning algorithms? - ?Spatio-temporal? - ?Spatio-temporal coupling compensation? - ?Temporal coupling? - ?Variable rate fertilization? - ?Variable rate fertilization for rice and wheat

Classification code: 731.1 Control Systems? - ?821.2 Agricultural Machinery and Equipment? - ?821.3 Agricultural Chemicals? - ?821.4 Agricultural Methods? - ?1101.2 Machine Learning? - ?1107 Human-Machine Systems? - ?1502.1.1.3 Soil Pollution

Numerical data indexing: Mass 0.00E00kg to 4.50E+02kg, Mass 0.00E00kg to 7.50E+02kg, Mass 4.50E+02kg to 7.50E+02kg, Percentage 9.05E+01%, Percentage 9.74E+01%, Size 4.00E+03m to 8.00E+03m, Size 8.00E+03m

DOI: 10.6041/j.issn.1000-1298.2025.12.025

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

58. Design and Experiment of Banana De-handing End Effector Based on Opening-closing Cutter

Accession number: 20255119745619

Title of translation: 基于张合式刀具的香蕉落梳末端执行器设计与试验

Authors: Duan, Jieli (1); Mo, Xingkang (1); Huang, Chaowei (1); Liu, Bocheng (1); Yang, Zhou (1, 2); Zou, Xiangjun (1, 3)

Author affiliation: (1) College of Engineering, South China Agricultural University, Guangzhou; 510640, China; (2) College of Mechanical Engineering, Guangdong Ocean University, Zhanjiang; 524088, China; (3) Foshan-Zhongke Innovation Research Institute of Intelligent Agriculture, Foshan; 528200, China

Corresponding author: Yang, Zhou(yangzhou@scau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 376-385

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 adaptability of the tool to the banana crown and the low success rate of the banana in the process of intelligent de-handing, a type of end effector was designed according to the morphological parameters of the banana bunch and the crown and the production requirements of the de-handing. The cutting arc of the adjustable opening-closing de-handing tool was used to adapt to different sizes of the banana crown to achieve continuous banana de-handing. The key parameters and main structure of the de-handing end effector were designed. The mechanical analysis model of the process of cutting banana crown by the de-handing tool was established, and the strength simulation was carried out. The results showed that the maximum stress of the de-handing tool during the de-handing process was 58.147 MPa, which was less than the yield strength of the tool material 205 MPa. The test platform of robot de-handing was built, and the significant factors affecting the de-handing effect were sorted as the cutting angle of de-handing, the blade angle and the de-handing speed. In order to obtain the optimal parameter combination, taking the peak cutting force and incision quality as the evaluation indices, the combination test of three-factors and three-levels were carried out by using Design-Expert software, and the mathematical regression model between the experimental factors and the evaluation indexes was obtained. The multi-objective optimization of the regression model was carried out, and the optimal parameter combination was obtained as follows: the de-handing speed was 2 m/s, the cutting angle of de-handing was 5.77°, and the blade angle was 5°. The results of the optimal parameter combination verification test showed that the peak cutting force was 31.49 N, the incision quality was 84 points, the relative error with the prediction results of the regression model was less than 5%, and the success rate of the de-handing was 92%, indicating that the opening-closing end effector of banana de-handing can effectively adapt to the banana crown’s morphology and obtain better incision quality. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 22

Main heading: End effectors

Controlled terms: Cutting? - ?Cutting tools? - ?Multiobjective optimization? - ?Quality control? - ?Regression analysis? - ?Software quality? - ?Software testing

Uncontrolled terms: Banana? - ?Blade angle? - ?Cutting angles? - ?Cutting forces? - ?De-handing robot? - ?Evaluation index? - ?Morphological parameters? - ?Opening-closing cutter? - ?Optimal parameter combinations? - ?Regression modelling

Classification code: 603.1 Machine Tool Accessories? - ?604.1 Metal Cutting? - ?731.5 Robotics? - ?821.5 Agricultural Products? - ?913.3 Quality Assurance and Control? - ?1106.9 Computer Software? - ?1201.7 Optimization Techniques? - ?1202.2 Mathematical Statistics

Numerical data indexing: Force 3.149E+01N, Percentage 5.00E+00%, Percentage 9.20E+01%, Pressure 2.05E+08Pa, Pressure 5.8147E+07Pa, Velocity 2.00E+00m/s

DOI: 10.6041/j.issn.1000-1298.2025.12.034

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

59. Design and Test of Crawler Self-propelled Semi-automatic Tobacco Harvester Chassis for Hilly Region

Accession number: 20255119745600

Title of translation: 丘陵山区履带自走式烟叶半自动采收机底盘设计与试验

Authors: Fu, Shenghui (1, 2); Tang, Ruqi (1); Shao, Mingxi (3); Gu, Shuowen (4); Ren, Naixu (1); Zhang, Wen (1, 2)

Author affiliation: (1) College of Engineering and Electronic, Shandong Agricultural University, Taian; 271018, China; (2) Shandong Key Laboratory of Intelligent Production Technology and Equipment for Facility Horticulture, Shandong Agricultural University, Taian; 271018, China; (3) School of Mechanical Engineering, Qinghai University, Xining; 810016, China; (4) Shandong Wuzheng Group Co., Ltd., Rizhao; 262300, China

Corresponding author: Zhang, Wen(wenzhang098@sdau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 407-416

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the challenges of high labor intensity, low operational efficiency, severe tobacco leaf damage, and lack of suitable harvesting equipment in tobacco-growing areas such as Yunnan, Guizhou, and Hunan provinces, an optimized chassis for a tracked self-propelled semi-automatic tobacco harvester was designed, specifically for hilly regions. The machine featured a gantry frame that enabled simultaneous harvesting three rows of tobacco. To reduce mechanical damage to the tobacco leaves and meet the needs of stable operation at low-speed, a dual-motor independent drive system and a mechanical automatic row-following device were designed. Additionally, based on CAN bus technology, an integrated vehicle control system combing manual and remote control was developed to meet control needs in various scenarios. Stability analysis and performance testing of the machine were carried out. The results showed that the maximum speed of the harvester chassis was 5 km/h with minimum turning radius of 903 mm. And it could handle slopes with up to 23°, and the lateral ultimate tipping angle was 24.7°. There was no side-slip or rollover when operating on contour lines with a lateral tilt angle of 15° ~ 20° on sloping land. Moreover, it could stop for more than 5 minutes on both upward and downward directions along longitudinal slopes ranging from 10° to 15° without any issues. During field harvesting, the machine exhibited smooth running characteristics with ample power reserves allowing free speed adjustments between 0 km/h and 4.5 km/h. This highlighted its strong adaptability to manual tobacco leaf harvesting operations. The average mechanical damage rate to tobacco leaves was 0.73 leaves per operation per hectare, and the average mechanical damage rate to tobacco plants was only 0.083 plants per operation per hectare. It showed that the developed tracked self-propelled semi-automatic tobacco leaf harvester chassis could meet the requirements of manual and machine-operated harvesting in narrow fields and gentle slopes, which was of significant importance for promoting the full mechanization of tobacco production. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Remote control

Controlled terms: Chassis? - ?Cigarette manufacture? - ?Control system synthesis? - ?Cultivation? - ?Harvesters? - ?Harvesting? - ?Tobacco

Uncontrolled terms: Damage rate? - ?Gantry-type frame? - ?Hilly region? - ?Mechanical? - ?Mechanical automatic row-follow system? - ?Mechanical damages? - ?Semi-automatics? - ?Tobacco harvesters? - ?Tobacco leaf? - ?Tracked self-propelled semi-automatic tobacco harvester

Classification code: 662.3 Automobile Components and Materials? - ?731.1 Control Systems? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?913.4 Manufacturing

Numerical data indexing: Size 0.00E00m, Size 4.50E+03m, Size 5.00E+03m, Size 9.03E-01m, Time 3.00E+02s

DOI: 10.6041/j.issn.1000-1298.2025.12.037

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

60. Optimal Control Method for Tractor Power-shifting Process Using Time-varying Disturbance Observer

Accession number: 20255119745595

Title of translation: 考虑时变扰动观测的拖拉机动力换挡过程最优控制方法

Authors: Fu, Shenghui (1, 2); Tang, Ruqi (1); Li, Wei (3); Liu, Shuangxi (1, 2); Ren, Naixu (1); Zhang, Wen (1, 2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an; 271018, China; (2) National Engineering Research Center of Agricultural Production Machinery and Equipment, Shandong Agricultural University, Tai’an; 271018, China; (3) College of Science and Technology, The Open University of China, Beijing; 100039, China

Corresponding author: Zhang, Wen(wenzhang_098@sdau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 201-210

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Due to the complex working conditions of tractors, which are influenced by the working environment, soil conditions, and traction loads, random time-varying disturbances during power shifting process could easily cause shifting jerk and even damage the transmission. Therefore, an optimal control method for tractor power shifting process considering time-varying disturbance observer was proposed. Firstly, the dynamic characteristics of the tractor shift process were analyzed to establish the shifting process dynamics model. The shift time, sliding friction work, and shock degree were taken as the shifting quality indicators, and a quadratic index function of the shifting control system was constructed. Then a high-order disturbance observer (HDO) was introduced to estimate the time-varying disturbances and their derivatives during the shifting process, and the linear quadratic regulator (LQR) was derived and solved for the optimal control law of the shifting process based on the Hamiltonian function. Finally, a hardware-in-the-loop simulation platform for tractors was built based on dSPACE and Matlab/Simulink to verify the shifting process performance under different operating conditions. The results showed that taking the shift from 1LL gear to 1L gear as an example, the shifting times under the transportation and plowing working conditions were 0.72 s and 0.85 s respectively, which were reduced by 22.58% and 38.4% compared with that of LQR. After compensation by HDO, the maximum shifting jerks were 16.11 m/s3 and 8.51 m/s3, respectively, which were 5.29% and 2.04% higher than that of LQR, the shifting jerk difference was not obvious, but the sliding friction work control effect was significant, being only 4.61 kJ and 8.82 kJ, which were reduced by 38.04% and 59.17% compared with that of LQR. The method could effectively observe and suppress the time-varying disturbances during the shifting process, and improve the shifting comfort. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 24

Main heading: Tractors (truck)

Controlled terms: Control theory? - ?Hardware-in-the-loop simulation? - ?MATLAB? - ?Optimal control systems? - ?Process control? - ?Time varying control systems? - ?Traction (friction)? - ?Tractors (agricultural)? - ?Transmissions

Uncontrolled terms: Higher order disturbance observers? - ?Linear quadratic? - ?Linear quadratic regulator? - ?Power shift? - ?Power shift transmission? - ?Quadratic regulators? - ?Shifting process? - ?Shifting process control? - ?Shifting quality? - ?Time-varying disturbance

Classification code: 602.2 Mechanical Transmissions? - ?663.1 Heavy Duty Motor Vehicles? - ?731 Automatic Control Principles and Applications? - ?731.1 Control Systems? - ?821.2 Agricultural Machinery and Equipment? - ?913.3 Quality Assurance and Control? - ?1106.2 Data Handling and Data Processing? - ?1106.5 Computer Applications? - ?1201.5 Computational Mathematics? - ?1301.1.1 Mechanics

Numerical data indexing: Energy 4.61E+03J, Energy 8.82E+03J, Percentage 2.04E+00%, Percentage 2.258E+01%, Percentage 3.804E+01%, Percentage 3.84E+01%, Percentage 5.29E+00%, Percentage 5.917E+01%, Size 1.611E+01m, Size 3.00E+00m, Size 8.51E+00m, Time 7.20E-01s, Time 8.50E-01s, Volume 1.00E-03m3

DOI: 10.6041/j.issn.1000-1298.2025.12.018

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

61. Coupled Wheel Testing Method under Typical Driving Conditions of High-horsepower Tractors

Accession number: 20255119745640

Title of translation: 大马力拖拉机典型行驶工况轮耦合试验方法研究

Authors: Guo, Zhiqiang (1, 2); Song, Zhenghe (1); Xiang, Lingfang (3); Yang, Zihan (1, 2); Huang, Shengcao (1, 2); Lin, Hengchu (2); He, Huawei (2)

Author affiliation: (1) Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, China Agricultural University, Beijing; 100083, China; (2) Luoyang Intelligent Agricultural Equipment Research Institute Co., Ltd., Luoyang; 471000, China; (3) First Tractor Co., Ltd., Luoyang; 471000, China

Corresponding author: Song, Zhenghe(songzhenghe@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 59-68

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Tractors are the most widely used power machinery in agricultural production. Conducting durability simulations of tractors under real-world operating conditions through laboratory test benches is of great significance for improving their reliability. A four-column wheel coupling test bench was utilized to explore the whole-machine durability testing methodology for tractors. An operational load acquisition system was established to collect load data under actual working conditions. Accelerated life testing was conducted by using three different identification methods: the time-domain damage retention identification method, the time-frequency analysis-based cumulative power spectral density identification method, and the wavelet transform-based envelope identification method. The effectiveness of these acceleration methods was validated through wheel coupling bench testing. The results indicated that, within the application scenarios and iterative approaches adopted, the time-frequency analysis-based cumulative power spectral density identification method demonstrated superior performance in signal compression, achieving a reduction ratio of 36.37%. The drive load spectra for the wheel coupling test bench were iteratively derived from both the original signal and the three accelerated signals. The loading results demonstrated that when the chassis and cab were selected as test targets, the damage reproduction tendency at designated measurement points was effectively achieved. Under the same test conditions but with different acceleration identification methods, the time-frequency analysis-based cumulative power spectral density identification method showed superior consistency in reproducing chassis damage, while the time-domain damage retention identification method performed better in replicating cab damage. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Durability

Controlled terms: Agricultural machinery? - ?Agriculture? - ?Cell proliferation? - ?Chassis? - ?Compression ratio (machinery)? - ?Couplings? - ?Damage detection? - ?Iterative methods? - ?Load testing? - ?Spectral density ? - ?Time domain analysis? - ?Wavelet transforms? - ?Wheels

Uncontrolled terms: Acceleration editor? - ?Identification method? - ?Power spectral? - ?Test-bench? - ?Testing method? - ?Time domain? - ?Time-frequency Analysis? - ?Tractor? - ?Wheel coupling test? - ?Wheel couplings

Classification code: 103 Biology? - ?214 Materials Science? - ?214.1 Mechanical Properties of Materials? - ?215.1.2 Mechanical Properties Testing Methods? - ?601.2 Machine Components? - ?602.1 Mechanical Drives? - ?609.1 Compressors? - ?662.3 Automobile Components and Materials? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?913.3.1 Inspection? - ?1201 Mathematics? - ?1201.3 Mathematical Transformations? - ?1201.9 Numerical Methods? - ?1301.1.3.1 Spectroscopy

Numerical data indexing: Percentage 3.637E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.004

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

62. Wheat Disease and Pest Recognition Method Based on Lightweight Multimodal Blend-CNN Model

Accession number: 20255119745584

Title of translation: 基于轻量化多模态 Blend-CNN 模型的小麦病虫害识别方法

Authors: Hao, Xia (1); Zhou, Ziyu (1); Song, Yang (1); Li, Guangye (1); Wang, Zhijun (1); Guo, Xuchao (1)

Author affiliation: (1) College of Information Science and Engineering, Shandong Agricultural University, Taian; 271017, China

Corresponding author: Guo, Xuchao(guoxc@sdau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 490-498 and 559

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Wheat, as one of the world’s essential food crops, requires timely diagnosis and control of diseases and pests to significantly reduce yield losses, which is crucial for global food security. However, deep learning methods typically rely on large amounts of training data and high-performance computing resources, which pose limitations in scenarios with small sample sizes and limited resources. To address these issues, a knowledge-enhanced lightweight multi-modal wheat diseases and pests identification model named multi-modal blend convolutional neural network (Blend-CNN) was proposed. The model was structured around a dual-branch convolutional neural network framework. It utilized an EfficientNet backbone network to extract image features of diseases and pests and incorporated a multi-branch TextCNN backbone network to extract textual features of diseases and pests descriptions, thereby obtaining more feature information and improving identification accuracy. Additionally, an innovative convolutional network-based multi-modal fusion method was introduced, allowing the model to optimally integrate information from both modalities globally. Furthermore, to mitigate the accuracy loss common in traditional multi-modal methods, the gradient blend loss function was developed. Finally, to verify the model’s effectiveness, comparative experiments were conducted on a constructed dataset containing 880 samples. The results demonstrated that the proposed model achieved the highest identification accuracy of 96.95% on this dataset, compared with other models, it had fewer parameters, lower complexity, and it was more lightweight which was applicable for edge devices, offering theoretical support for wheat diseases and pests identification in scenarios with limited sample sizes and resources. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 51

Main heading: Deep learning

Controlled terms: Blending? - ?Convolution? - ?Convolutional neural networks? - ?Crops? - ?Diagnosis? - ?Disease control? - ?Learning systems? - ?Modal analysis? - ?Sampling

Uncontrolled terms: Back-bone network? - ?Convolutional neural network? - ?Deep learning? - ?Disease and pest identification? - ?Few-shot learning? - ?Identification accuracy? - ?Multi-modal? - ?Multi-modal fusion? - ?Multi-modal learning? - ?Wheat

Classification code: 102.1 Medicine? - ?102.1.2 Health Science? - ?716.1 Information Theory and Signal Processing? - ?802.3 Chemical Operations? - ?821.5 Agricultural Products? - ?1101.2 Machine Learning? - ?1101.2.1 Deep Learning? - ?1201.5 Computational Mathematics? - ?1202 Statistical Methods

Numerical data indexing: Percentage 9.695E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.045

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

63. Improved Obstacle Avoidance Target Detection with YOLO v5s and Millimeter Wave Radar Fusion

Accession number: 20255119745579

Title of translation: 融合改进 YOLO v5s 与毫米波雷达的避障目标检测方法

Authors: Hu, Lian (1, 2); Liang, Chuqi (1); Luo, Yaling (1); Liu, Zhaodi (1); Ruan, Qingqiang (1); Wang, Pei (1, 2); Huang, Peikui (1, 2); Wang, Pei (3); Sun, Yitian (4)

Author affiliation: (1) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) State Key Laboratory of Agricultural Equipment Technology, Beijing; 100083, China; (3) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100087, China; (4) Shandong Academy of Agricultural Machinery Sciences, Ji’nan; 250100, China

Corresponding author: Huang, Peikui(pkhuang@scau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 634-644

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to improve the accuracy of unmanned agricultural machine’s perception of obstacles in the farm environment, to solve the problem that visual detection is easily affected by light and millimeter-wave radar detection is easily affected by vehicle bumps, etc., as well as the problem that the visual target detection algorithm has a large number of parameters, a large amount of computation, and a large volume of the model under the complex field, this paper proposes an obstacle-avoidance target detection method for unmanned agricultural machines with the fusion of visual and millimeter-wave radar information. Part of the radar target data from millimeter-wave radar is first filtered, and a target tracking algorithm based on adaptive extended Kalman filtering is proposed. Then a farm environment obstacle dataset is produced and a target detection network based on improved YOLO v5s is constructed. Subsequently, the mapping of radar points into the image pixel coordinate system is realized by time-stamp alignment and coordinate transformation with direct linear calibration method. Finally, the fusion model of obstacle detection information from millimeter-wave radar and visual sensors is constructed through the decision-level fusion method and target matching strategy, and the experimental results show that the mean average accuracy of the improved YOLO v5s is 97.0%, which is similar to that of the original model, but the number of parameters, the amount of computation, and the size of the model are only 40.2%, 39.2%, and 38.2% of the original YOLO v5s model, respectively. Compared with YOLO v4 - Tiny, YOLO v7 - Tiny, YOLO v4 and YOLO v7 models, it can better balance the detection accuracy and speed. The results of multi-scene tests show that the fusion method proposed in this paper improves the recognition accuracy by 2.67 percentage points and 15.07 percentage points compared with radar and camera in daytime tests, and the fusion detection method can effectively make up for the failure of the camera in nighttime tests, and has better robustness and accuracy than the single-sensor algorithm, and the fusion obstacle avoidance system effectively realizes the parking avoidance of the unmanned agricultural machine. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Linear transformations

Controlled terms: Agricultural robots? - ?Cameras? - ?Collision avoidance? - ?Farms? - ?Information fusion? - ?Object detection? - ?Object recognition? - ?Obstacle detectors? - ?Radar target recognition? - ?Radar tracking ? - ?Sensor data fusion? - ?Target tracking? - ?Tracking radar? - ?Vehicle detection

Uncontrolled terms: Detection informations? - ?Farmland obstacle detection? - ?Millimeter-wave radar? - ?Millimetre-wave radar? - ?Objects detection? - ?Obstacles detection? - ?Targets detection? - ?Visual object detection information fusion? - ?Visual objects? - ?YOLO v5s

Classification code: 435.2 Tracking and Positioning? - ?716.2 Radar Systems and Equipment? - ?731.6 Robot Applications? - ?742.2 Photographic and Video Equipment? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?903.1 Information Sources and Analysis? - ?914.1 Accidents and Accident Prevention? - ?1106.2 Data Handling and Data Processing? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision? - ?1201.3 Mathematical Transformations

Numerical data indexing: Percentage 3.82E+01%, Percentage 3.92E+01%, Percentage 4.02E+01%, Percentage 9.70E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.058

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

64. Design and Experiment of Scion Picking Device for Fully Automatic Grafting Machine

Accession number: 20255119745588

Title of translation: 茄果类全自动嫁接机接穗取苗装置设计与优化试验

Authors: Huan, Xiaolong (1, 2); Xiong, Shengsen (1); Chen, Jiafeng (3); Zhang, Feijie (4); Tong, Junhua (1, 2)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Provincial Key Laboratory of Agricultural Intelligent Perception and Robotics, Zhejiang Province, Hangzhou; 310018, China; (3) Hangzhou Sedlin Intelligent Assembly Co., Ltd., Hangzhou; 311418, China; (4) Fuyang District Agricultural Technology Extension Centre, Hangzhou; 311400, China

Corresponding author: Tong, Junhua(jhtong@zstu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 259-266

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Most of the existing solanaceous vegetable grafting machines are semi-automatic models. Due to the significant differences in the growth morphology of seedlings, the automatic seedling picking process is difficult to achieve. Based on the working requirements of the fully automatic row grafting equipment for solanaceous vegetables, an automatic scion seedling picking device was designed. This device adopted flexible gripper hands, which had strong adaptability to the growth form of seedlings. It can automatically supply, clamp, cut and transfer the scion trays, achieving the automation of seedling extraction for grafting operations, thereby promoting the upgrading of the grafting machine from semi-automatic to fully automatic operation. In order to verify the working performance of the scion picking device, taking chili seedlings in the grafting period as the object, the success rate of picking as the test index, and the thickness of the elastic piece, the structure of the clamping hand, and the scion growth offset as factors, a three-factor and three-level orthogonal test for scion picking was carried out. The test results showed that the influence degrees of the three factors on the success rate of picking, from large to small, were as follows: gripper structure, growth offset, and elastic piece thickness. The optimal combination was gripper structure III, growth offset of 0~14 mm, and elastic piece thickness of 0.3 mm. The scion picking test was conducted under the optimal combination conditions. A total of 150 scions from three tray seedlings were selected as the seedlings, after experimental verification, the success rate of picking was 98.7%, meeting the performance requirements of the scion picking operation of the grafting machine. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 20

Main heading: Grippers

Controlled terms: Agricultural machinery? - ?Grafting (chemical)? - ?Morphology? - ?Plants (botany)? - ?Seed? - ?Structural optimization? - ?Vegetables

Uncontrolled terms: Automatic grafting machine? - ?Automatic modeling? - ?Automatic scion picking? - ?Flexible gripper hand? - ?Flexible grippers? - ?Growth form? - ?Growth morphology? - ?Optimal combination? - ?Semi-automatics? - ?Solanaceous vegetable

Classification code: 103 Biology? - ?214 Materials Science? - ?731.5 Robotics? - ?802.2 Chemical Reactions? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?1201.7 Optimization Techniques

Numerical data indexing: Percentage 9.87E+01%, Size 0.00E00m to 1.40E-02m, Size 3.00E-04m

DOI: 10.6041/j.issn.1000-1298.2025.12.023

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

65. Construction and Experiment of Discrete Element Model for Tea Garden Soil-Organic Fertilizer Mixture Based on EDEM

Accession number: 20255119745674

Title of translation: 基于 EDEM 的茶园土壤-有机肥混料离散元模型构建与试验

Authors: Huan, Xiaolong (1, 2); Feng, Mengchao (1); Wu, Chuanyu (1, 2); Jia, Jiangming (1, 2); Chen, Jianneng (1, 2)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Key Laboratory of Zhejiang Transplanting Equipment Technology, Hangzhou; 310018, China

Corresponding author: Chen, Jianneng(jiannengchen@zstu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 267-278

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to improve the simulation accuracy of the discrete element model for tea garden soil-organic fertilizer mixture, focusing on the combination of physical experiments and simulation to calibrate the parameters of tea garden soil and organic fertilizer, by using the slope method, rolling friction test, and coefficient of restitution measurement, the physical and contact parameters of soil and organic fertilizer were obtained, and the mixing angle was measured based on the cylindrical lifting method. The Plackett-Burman experiment was used to screen for significant influencing parameters, and the optimization interval was determined by combining the steepest slope test. A quadratic regression model was established by using the Box-Behnken response surface method to obtain the optimal parameter combination: soil-organic fertilizer recovery coefficient of 0.35, organic fertilizer rolling friction factor of 0.115, and organic fertilizer steel recovery coefficient of 0.606. At the same time, the applicable range of moisture content for the model (5%~10%) was clarified through experimental analysis. The verification test showed that the simulated stacking angle was 24.49°, with a relative error of 1.65% compared with the actual value. A prototype of a tea garden tillage and fertilization machine was built, field rotary tillage and fertilization experiments were conducted, and rotary tillage and fertilization experiments were simulated. The relative errors of soil coverage rate in field experiments and simulation experiments at different rotary tillage speeds (150 r/min, 200 r/min, 250 r/min, and 300 r/min) were 6.21%, 4.52%, 7.13%, and 7.72%, respectively. The soil-rganic fertilizer distribution in simulation experiments was consistent with that in field experiments, verifying the accuracy of the soil-organic fertilizer mixture discrete element model and contact parameters. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Friction

Controlled terms: Agricultural machinery? - ?Cultivation? - ?Fertilizers? - ?Plants (botany)? - ?Regression analysis? - ?Soil testing? - ?Soils? - ?Tea

Uncontrolled terms: Discrete element models? - ?Field experiment? - ?Organic fertilizers? - ?Parameters calibrations? - ?Rolling friction? - ?Rotary tillages? - ?Soil fertilizers? - ?Soil-organic fertilizer mixture? - ?Tea garden soils? - ?Tea gardens

Classification code: 103 Biology? - ?483.1 Soils and Soil Mechanics? - ?821.2 Agricultural Machinery and Equipment? - ?821.3 Agricultural Chemicals? - ?821.4 Agricultural Methods? - ?822.3 Food Products? - ?1202.2 Mathematical Statistics? - ?1301.1.1 Mechanics? - ?1502.1.1.3 Soil Pollution? - ?1502.1.1.4.3 Soil Pollution Control

Numerical data indexing: Angular velocity 2.505E+00rad/s, Angular velocity 3.34E+00rad/s, Angular velocity 4.175E+00rad/s, Angular velocity 5.01E+00rad/s, Percentage 1.00E+01%, Percentage 1.65E+00%, Percentage 4.52E+00%, Percentage 5.00E+00%, Percentage 6.21E+00%, Percentage 7.13E+00%, Percentage 7.72E+00%

DOI: 10.6041/j.issn.1000-1298.2025.12.024

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

66. Design and Experiment of Pressure Type Online Yield Measurement System for Grain Combine Harvester

Accession number: 20255119745629

Title of translation: 谷物联合收获机压力式在线测产系统设计与试验

Authors: Huang, Peikui (1, 2); Wu, Peitian (1); Xu, Chaorui (1); Liang, Shunda (1); He, Jie (1, 2); Wang, Pei (1, 2); Zhao, Runmao (1, 2); Hu, Lian (1, 2); Wang, Pei (3); Sun, Xuantian (4)

Author affiliation: (1) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) State Key Laboratory of Agricultural Equipment Technology, Beijing; 100083, China; (3) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (4) Shandong Academy of Agricultural Machinery Sciences, Ji’nan; 250100, China

Corresponding author: Hu, Lian(lianhu@scau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 311-321

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to improve the online yield measurement accuracy of grain combine harvester and suppress the interference of body tilting and mechanical vibration during the yield measurement process, a pressure-type grain yield measurement system based on tilting angle and vibration compensation strategy was developed. The system consisted of a pressure-type grain yield measurement device, a GNSS positioning module, a data processor and a host computer. Firstly, a mathematical model of grain yield monitoring was constructed based on the functional relationship between grain yield and sensor pressure, inclination, vibration and humidity, and a test rig for grain yield monitoring was built to optimize the structural parameters of the device through orthogonal test combined with response surface analysis. The effects of the number of pressure sensors, the mounting position of the vibration absorber and the inclination angle of the device on the measurement error were investigated, and the optimal parameter combinations were determined to be five pressure sensors, the 3rd reference position (175 mm from the left slot wall) for the vibration absorber and the 21° inclination angle of the device, respectively. The results of univariate (flow rate change) and multivariate (flow rate, inclination angle and vibration change) tests showed that the yield measurement error of 20 groups of tests under different working conditions was stably controlled within 3%; the results of field tests showed that the average yield measurement error in actual operation was 3.41%, with a maximum of no more than 4%, which verified that the system can effectively inhibit the interference of the tilting of the vehicle body and the vibration of the machinery on the accuracy of the measurement of the yield and provide an effective technical support to obtain the information of the distribution of the yield of the precision agriculture. The system can effectively suppress the interference of body tilt and mechanical vibration on yield measurement accuracy, and provide effective technical support for the acquisition of precise agricultural yield distribution information. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Pressure sensors

Controlled terms: Automobile bodies? - ?Flow rate? - ?Grain (agricultural product)? - ?Harvesters? - ?Measurement errors? - ?Precision agriculture? - ?Vibration analysis? - ?Vibration measurement? - ?Yield stress

Uncontrolled terms: Combine harvesters? - ?Grain combine harvester? - ?Grain combines? - ?Grain yield? - ?Inclination and vibration compensation? - ?Inclination angles? - ?Online yield monitoring? - ?Vibration compensation? - ?Yield measurement? - ?Yield monitoring

Classification code: 214 Materials Science? - ?301.1 Fluid Flow? - ?662.3 Automobile Components and Materials? - ?731.1.1 Error Handling? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?941.5 Mechanical Variables Measurements? - ?942.1.9 Pressure Measuring Instruments

Numerical data indexing: Percentage 3.00E+00%, Percentage 3.41E+00%, Percentage 4.00E+00%, Size 1.75E-01m

DOI: 10.6041/j.issn.1000-1298.2025.12.028

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

67. Evaluation of Suitability of Abandoned Cultivated Land for Recultivation Based on AHP-CRITIC-TOPSIS

Accession number: 20255119745676

Title of translation: 基于 AHP-CRITIC-TOPSIS 的撂荒耕地复耕适宜性评价

Authors: Jiang, Hailing (1); Feng, Xinhui (1); Zhang, Shuhan (1); Yu, Hailin (1); Zhang, Jingyi (1)

Author affiliation: (1) College of Geography and Tourism, Jilin Normal University, Siping; 136000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 417-424

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to explore the suitability of abandoned cultivated land for recultivation and improve the utilization rate of cultivated land, taking Lishu County, Jilin Province as the study area, firstly based on the Google Earth Engine platform and the 2022 Sentinel-2 image data of Lishu County, a total of 46 features such as spectral features, vegetation features, texture features, and terrain features were calculated, and random forest algorithm was used to construct the optimal feature set, and finally 39 features were screened to participate in the classification, so as to obtain the scope of abandoned cultivated land. Then the AHP-CRITIC-TOPSIS model was used to construct an evaluation model of the suitability of abandoned cultivated land for recultivation from three dimensions: natural, soil and socio-economic conditions, and the suitability was divided into four grades: highly suitable, moderately suitable, barely suitable and unsuitable, so as to put forward a feasible scheme for the rehabilitation of abandoned cultivated land. The results showed that the accuracy of the classification results of land use types in Lishu County in 2022 was relatively accurate, and the overall classification accuracy and Kappa coefficient were above 95%, indicating that the classification results were consistent with the actual land types and the overall classification effect was good. The area of abandoned cultivated land not suitable for recultivation in Lishu County was 1 673.73 hm2, which was mainly located in the southeast of the study area, and the area of abandoned cultivated land suitable for recultivation was 1 071.67 hm2, which was mainly located in the low-altitude plain area in the northwest of the study area. At present, the implementation of the national cultivated land protection policy indeed improved the use of cultivated land in rural areas, but the problems of abandonment and low utilization efficiency of rural cultivated land were still prominent, and the results can provide a scientific basis for improving the quality of cultivated land and ensuring food security in Lishu County and surrounding areas. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Hierarchical systems

Controlled terms: Analytic hierarchy process? - ?Economics? - ?Land use? - ?Landforms? - ?Rural areas? - ?Textures

Uncontrolled terms: Abandonment of cultivated land? - ?AHP-CRITIC-TOPSIS? - ?Classification results? - ?Cultivated lands? - ?Evaluation of the suitability? - ?Google earths? - ?Jilin Province? - ?Recultivation? - ?Study areas? - ?Utilization rates

Classification code: 214 Materials Science? - ?403 Urban and Regional Planning and Development? - ?403.2 Regional Planning and Development? - ?481.1 Geology? - ?912.2 Management? - ?961 Systems Science? - ?971 Social Sciences

Numerical data indexing: Percentage 9.50E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.038

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

68. Operation Status Recognition Method and Experiment Based on Multidimensional Features of Agricultural Machinery Spatial Track

Accession number: 20255119745585

Title of translation: 基于农机运行轨迹点多维特征的作业状态辨识方法与试验

Authors: Li, Baozhong (1, 2); Wang, Weipeng (2); Zhou, Guomin (3, 4); Xu, Pei (2); Shen, Ji (2)

Author affiliation: (1) Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing; 100081, China; (2) Luoyang Smart Agricultural Equipment Institute Co., Ltd., Luoyang; 471000, China; (3) National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya; 572024, China; (4) Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing; 210014, China

Corresponding author: Zhou, Guomin(zhouguomin@caas.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 150-157

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The operation state of agricultural machinery is a key indicator for assessing the efficiency of agricultural mechanization and precise management. To realize the precise monitoring of the operation state of farm machinery by the data management platform, an operation state identification method was proposed based on the multidimensional features of the spatial track of farm machinery. Firstly, based on the big data management platform supported by the modern information technology of Internet of Things, the potential characteristics of the trajectory points in the operating space of agricultural machinery were studied, and the distribution laws of the characteristics such as speed, acceleration, steering rate and distribution density of trajectory points were analyzed. Secondly, based on the distribution characteristics of each feature and the demand for operation state recognition, a multi-strategy split-box processing method was used to quantitatively divide the features, and weight of evidence (WOE) and information value (IV) methods were introduced to quantify the influence weight of different features on the operation state of the farm machinery, so as to assess the impact on operation state the key features of the recognition ability were evaluated. Finally, based on the multidimensional key features of the spatial trajectory points of the farm machinery, the fusion algorithm of BP neural network and AdaBoost was combined to recognize the operation state of the farm machinery. The experimental results showed that the accuracy of the proposed algorithm model in the prediction of the operation state of agricultural machinery was as high as 97.3%, indicating that the recognition method based on the multidimensional features of agricultural machinery can accurately recognize the operation state of agricultural machinery. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 21

Main heading: Trajectories

Controlled terms: Agricultural machinery? - ?Agriculture? - ?Information management? - ?Neural networks? - ?State estimation

Uncontrolled terms: BP-adaboost? - ?Farm machinery? - ?Multi-strategy binning? - ?Operation state? - ?Operation status? - ?Operation status recognition? - ?Recognition methods? - ?Spatial track? - ?Status recognition? - ?Trajectory points

Classification code: 101.1 Biomedical Engineering? - ?656 Space Flight and Research? - ?731.1 Control Systems? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Machinery and Equipment? - ?903 Information Science? - ?1101 Artificial Intelligence

Numerical data indexing: Percentage 9.73E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.013

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

69. Assessment of Productivity and Carbon Footprint of Grain - Oil Intercropping Farmland under Plastic Film Mulching

Accession number: 20255119731970

Title of translation: 地膜覆盖下粮油间作农田生产力与碳足迹评估

Authors: Li, Changjian (1); Li, Xiahaoqi (2); Wang, Songhao (2); Shao, Ruxin (2); Cheng, Zhi (3); Zhao, Xining (1)

Author affiliation: (1) College of Soll and Water Conservation Scienee and Engineering, Institute of Soil and Water Conservation), Northwest A & F University, Shaanxi, Yangling; 712100, China; (2) College of Water Resources and Architectural Engineering, Northwest A & F University, Shaanxi, Yangling; 712100, China; (3) Cuizhou Agricultural Regional Economic Development Center, Cuiyang, 550003, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 666-676

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Intercropping of grains and oils, along with plastic film coverage, serves as an effective agricultural practice adapted to specific natural conditions. This practice holds significant importance in dryland agricultural production in the northern regions. The application of these measures is bound to influence the changes in the carbon cycling processes of farmland soil. However, the variations in productivity and carbon footprint under intercropping and plastic film coverage, along with the associated ecological effects, remain unclear. Totally five treatments, including maize mulching (FMM), maize without mulching (NMM), soybean monoculture (SS), maize — soybean intercropping + maize mulching (FMS), maize — soybean intercropping + maize without mulching (NMS) were set up. Based on the life cycle assessment (LCA) method, the characteristics of greenhouse gas emissions, content of soil organic carbon, com yield, and other factors from farmland soil under maize — soybean intercropping and plastic film coverage were evaluated. It also comprehensively assessed the impact of these practices on farmland productivity and carbon footprint through indicators, such as land productivity and earbon sustainability index. The results indicated that the relative yield of FMS treatment was increased by 57% to 60% compared with that of monoculture treatment, with a land equivalent ratio of 1. 08 over the past two years, effectively enhancing farmland productivity. Simultaneously, the soil organic carbon loss in the FMS treatment was reduced by 7. 8% to 46. 57% compared with that of other treatments. It exhibited the lowest carbon footprint per unit area (CFA ), carbon footprint per unit maize equivalent yield (CFMEEY ), and carbon footprint per unit total income (CFE ), effectively preserving soil organic carbon while reducing greenhouse gas emissions, thereby alleviating environmental burdens and carbon emissions. Although FMS treatment reduced some crop yield and economic benefits compared with monoculture Systems, it demonstrated relatively lower soil greenhouse gas emissions and organic carbon loss during the production process. It also had a higher carbon sustainability index compared with NMS treatment, achieving effective management of soil carbon emissions. FMS as an environmentally friendly planting model, it can realize low carbon and high yield, thus providing guidance for agricultural producers in selecting suitable planting Systems. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Carbon footprint

Controlled terms: Artificial life? - ?Carbon cycle? - ?Carbon Economy? - ?Carbon emissions? - ?Crops? - ?Farms? - ?Grain (agricultural product)? - ?Greenhouse gases? - ?Life cycle? - ?Nitrogen fixation ? - ?Organic carbon? - ?Soil conservation? - ?Soil pollution? - ?Soils

Uncontrolled terms: Carbon loss? - ?Farmland soils? - ?Film coverage? - ?Greenhouse gas emissions? - ?Maize - soybean intercropping? - ?Per unit? - ?Plastic mulching? - ?Plastic-film? - ?Soil organic carbon? - ?Sustainability index

Classification code: 483.1 Soils and Soil Mechanics? - ?802.2 Chemical Reactions? - ?804.1 Organic Compounds? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.5 Agricultural Products? - ?913.1 Production Engineering? - ?1101 Artificial Intelligence? - ?1501.2.1 Resource Conservation? - ?1502.1.1.3 Soil Pollution? - ?1502.1.2 Climate Change? - ?1502.2 Ecology and Ecosystems

Numerical data indexing: Percentage 5.70E+01%, Percentage 5.70E+01% to 6.00E+01%, Percentage 8.00E+00% to 4.60E+01%

DOI: 10.6041/j.issn.1000-1298.2025.12.061

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

70. Design and Mechanism Study of Auxiliary Plate of New High-efficiency Impurity Removal Device for Plot Harvester Based on Coanda Effect

Accession number: 20255119745589

Title of translation: 基于柯恩达效应的小区收获机高效除杂装置辅助板设计与机理研究

Authors: Li, Guoying (1, 2); Xu, Zhuxin (2); Li, Guoliang (2); Li, Xue (2, 3); Lu, Zhihao (3, 4); Yu, Runzhi (3, 4); Yang, Cheng (1, 2)

Author affiliation: (1) Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization, Qingdao; 266109, China; (2) Qingdao Plantech Mechanical Technology Co., Ltd., Qingdao; 266109, China; (3) College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao; 266109, China; (4) Qingdao Proud Electromechanical Technology Co., Ltd., Qingdao; 266109, China

Corresponding author: Yang, Cheng(ycplantech@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 343-353

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In the plot combine harvester, the impurity removal system based on the Coanda effect serves as a novel secondary cleaning device, featuring advantages of simple structure and compact spatial footprint. However, in practical applications, relying solely on the Coanda effect generated by curved surfaces can only achieve partial impurity separation, as most impurities fail to be effectively removed under airflow, resulting in suboptimal cleaning efficiency. To enhance the device’s performance, strengthen the Coanda effect intensity at the end of the curved surface, and mitigate airflow diffusion, an auxiliary plate structure was introduced to the original design. Using the CFD-DEM method, the particle deflection angles of wheat grains and husk impurities were obtained for the configuration without the auxiliary plate. These angles were then utilized to determine the variation range of the auxiliary plate’s free-end angle (4.89°~27.12°) through geometric relationships. Numerical simulations were employed to analyze the flow field structure within the Coanda effect zone of the device, identifying the height range (0.112~0.128 m) where abrupt velocity changes occurred at the end of the Coanda effect. Based on simulation results, the optimal length of the auxiliary plate and the positioning of its fixed end were further refined. Bench tests demonstrated that the highest cleaning efficiency was achieved when the auxiliary plate had a free-end angle of 25°, a length of 155 mm, and a fixed-end height of 0.122 m, and the impurity content in the grain is 0.998%, conclusively validating its significant role in improving device performance. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 24

Main heading: Efficiency

Controlled terms: Air cleaners? - ?Auxiliary equipment? - ?Cleaning? - ?Grain (agricultural product)? - ?Harvesters? - ?Impurities? - ?Plates (structural components)? - ?Removal

Uncontrolled terms: Auxiliary plate? - ?CFD-DEM? - ?CFD-DEM coupling simulation? - ?Cleaning efficiency? - ?Coanda effects? - ?Coupling simulation? - ?Curved surfaces? - ?Impurity removal? - ?Impurity removal device? - ?Plot harvesters

Classification code: 214 Materials Science? - ?408.1 Structural Members and Shapes? - ?802.3 Chemical Operations? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?901 Engineering Profession? - ?913.1 Production Engineering? - ?1502.1.1.4.1 Air Pollution Control

Numerical data indexing: Percentage 9.98E-01%, Size 1.12E-01m to 1.28E-01m, Size 1.22E-01m, Size 1.55E-01m

DOI: 10.6041/j.issn.1000-1298.2025.12.031

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

71. Intelligent Positioning System of Sugarcane Harvester Tip Cutter Based on Bimodal and Fuzzy Adaptive PID Control

Accession number: 20255119745607

Title of translation: 基于双模态与模糊自适应 PID 控制的甘蔗收获机切梢器智能定位系统研究

Authors: Li, Shangping (1, 2); Ren, Hongyu (1, 2); Mo, Yifan (1, 2); Wei, Yutong (1, 2); Wen, Chunming (1, 2); Li, Kaihua (3)

Author affiliation: (1) College of Electronic Information, Guangxi Minzu University, Nanning; 530006, China; (2) Key Laboratory of Intelligent Unmanned System and Intelligent Equipment, Nanning; 530006, China; (3) Nanning Taiying Technology Co., Ltd., Nanning; 530103, China

Corresponding author: Li, Kaihua(78281062@qq.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 366-375

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the challenge faced by sugarcane harvester operators who rely solely on visual judgment and experience to determine cane tops’ positions, making it difficult to adjust cutting height accurately and in real-time, an intelligent positioning system for sugarcane harvester top cutters was proposed based on dual-modal and fuzzy adaptive PID control. Additionally, a cluster-based knife adjustment strategy was developed based on sugarcane cluster feature recognition. The system firstly utilized the YOLO v8 instance segmentation model to detect cane tops, with a depth camera capturing depth data of sugarcane tops in real time and converting pixel coordinates into camera coordinates for height measurement. To validate the depth camera’s field performance, multiple field experiments were conducted. Results showed that within a range of 50 ~ 100 cm from the sugarcane, the average relative error of the depth camera ranged from 0.189% to 0.949%. Subsequently, fuzzy rules were designed, and a microcontroller integrated with a fuzzy adaptive PID algorithm was used to control the servo motor’s operating speed. The maximum rising response speed was approximately 289.36 mm/s, and the descending response speed was about 273.16 mm, with a measurement error within ± 1 mm. PID comparison experiments showed that fuzzy PID control, compared with traditional PID control, reduced the response time by 0.12 s, bringing it down to 1.24 s. The overshoot was decreased from 12.80 mm to 4.63 mm, the number of overshoots dropped to one, and the steady-state error stabilized within ±2 mm. Finally, dynamic tests demonstrated that the system’s average recognition time was 0.08 s, showcasing excellent real-time performance. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 18

Main heading: Three term control systems

Controlled terms: Adaptive control systems? - ?Cameras? - ?Errors? - ?Fuzzy inference? - ?Harvesters? - ?Intelligent systems? - ?Molasses? - ?Proportional control systems? - ?Sugar cane? - ?Two term control systems ? - ?Visual servoing

Uncontrolled terms: Cane top? - ?Depth camera? - ?Dual-modal? - ?Fuzzy adaptive PID control? - ?Harvester operators? - ?Intelligent positioning systems? - ?Real- time? - ?Response speed? - ?Sugarcane harvesters? - ?Tip cutter

Classification code: 731.1 Control Systems? - ?731.1.1 Error Handling? - ?731.5 Robotics? - ?742.2 Photographic and Video Equipment? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?822.3 Food Products? - ?1101 Artificial Intelligence

Numerical data indexing: Percentage 1.89E-01% to 9.49E-01%, Size 1.00E-03m, Size 1.28E-02m to 4.63E-03m, Size 2.00E-03m, Size 2.7316E-01m, Size 5.00E-01m to 1.00E00m, Time 1.20E-01s, Time 1.24E+00s, Time 8.00E-02s, Velocity 2.8936E-01m/s

DOI: 10.6041/j.issn.1000-1298.2025.12.033

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

72. Effects of Milk Fat Content and Fat Globule Structure on Perception of Astringency in Milk Tea System

Accession number: 20255119732001

Title of translation: 乳脂肪含量与脂肪球结构对乳茶体系涩感感知的影响研究

Authors: Li, Xingyi (1); Mao, Wei (1); Li, Yajuan (1); Zhou, Hui (1); Fan, Xiankang (1); Luo, Jie (1)

Author affiliation: (1) College of Food Science and Engineering, Hunan Agricultural University, Changsha; 410128, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 769-776

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Milk tea beverage is a drink widely loved by consumers. The astringency caused by the rieh tea polyphenols in the tea soup is one of the key factors affecting the sensory quality of milk tea beverage. Existing research has shown that milk components, such as milk proteins, can reduce astringency. Milk fat, an important component in cow’s milk, is composed of milk fat globules. However, the effect of its content and structure on astringency in milk tea Systems remained unclear. It was aimed to investigate the impact of milk fat content and fat globule structure on astringency in milk tea Systems. Firstly, it used descriptive sensory evaluation to explore whether milk fat and fat content affected the astringency of milk tea System. Next, three types of milk fat droplets with the same fat content but different structural characteristics were construeted by adjusting the heating intensity and homogenization pressure; milk fat droplet C, milk fat droplet T and milk fat droplet H, and the particle size, ^-potential, microscopio structure, milk fat globule membrane protein content and composition, and milk fat globule membrane phospholipid content were measured, which characterized the characteristics of milk fat globules. Then different milk fat droplets were added to the simulated milk tea System to conduet sensory evaluation of astringency intensity, and quantify astringency through fluorescence spectroscopy analysis. The results showed that when the milk fat content reached above 4 g/(100 mL), the addition of milk fat can significantly reduce the astringency level in milk tea. In addition, changing the particle size and membrane stmcture of milk fat globules also had a significant impact on the astringency of the milk tea System. Compared with the other two milk fat droplets, the fat globule size in milk fat droplet H was the smallest (0 . 4 9 p,m), the protein content per gram fat globule membrane was the highest (1 2 . 60 mg), and the astringency was the weakest. Milk fat droplet T had the largest particle size (4 . 20 u,m), the lowest protein content per gram fat globule membrane (4 . 12 mg), and a strong astringency. Therefore, milk fat content, particle size and membrane structure would affect the astringency intensity of milk tea System. Smaller milk fat globule size and more milk fat globule membrane interface proteins had the greatest effect on reducing the astringency intensity of milk tea System. It was confirmed the impact of milk fat on the perception of astringency in the milk tea System, laying a theoretical foundation for the development of green and healthy milk tea drinks with a smoother taste. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Particle size

Controlled terms: Biological membranes? - ?Dairy products? - ?Drop formation? - ?Particle size analysis? - ?Proteins? - ?Sensory analysis? - ?Sensory perception? - ?Solubility? - ?Spectrum analysis? - ?Tea

Uncontrolled terms: Astringency? - ?Fat contents? - ?Fat droplets? - ?Fat globules? - ?Globule size? - ?Milk fat globules? - ?Milk fats? - ?Milk tea system? - ?Particles sizes? - ?Protein contents

Classification code: 101.5 Ergonomics and Human Factors Engineering? - ?103 Biology? - ?703 Electric Circuits? - ?801.3 Physical Chemistry? - ?804.1 Organic Compounds? - ?805 Chemical Engineering? - ?822.3 Food Products? - ?941.5 Mechanical Variables Measurements? - ?1301.1.2 Physical Properties of Gases, Liquids and Solids? - ?1301.1.3.1 Spectroscopy

Numerical data indexing: Mass 1.20E-05kg, Mass 4.00E-03kg, Mass 6.00E-05kg, Volume 1.00E-04m3

DOI: 10.6041/j.issn.1000-1298.2025.12.071

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

73. Design and Experiment of Adaptive Threshing Gap Device for Soybean Combine Harvester

Accession number: 20255119745635

Title of translation: 大豆联合收获机脱粒间隙自适应装置设计与试验

Authors: Liu, Anwen (1, 2); Xie, Fangping (1, 2); Zhu, Lixue (1, 3); Wang, Xiushan (1, 2); Ji, Bang (1, 2); Kang, Jiaxin (4)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha; 410128, China; (2) Hunan Key Laboratory of Intelligent Agricultural Machinery Equipment, Changsha; 410128, China; (3) College of Mechanical and Electrical Engineering, Zhongkai University of Agricultre and Engineering, Guangzhou; 510225, China; (4) College of Mechanical Engineering, Hunan Institute of Engineering, Xiangtan; 411104, China

Corresponding author: Ji, Bang(jibangnongye@hunau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 322-330 and 342

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to address the issue that the threshing and separation device of traditional soybean combine harvesters cannot adjust the threshing gap in real-time, resulting in uneven material distribution in the threshing chamber and consequently high rates of soybean grain breakage, unthreshed grain loss, and entrainment loss, an adjustment system was designed based on the real-time matching of feed rate and threshing gap. Using the feed rate, threshing section gap, and separation section gap as experimental factors, and the grain breakage rate, unthreshed grain rate, and entrainment loss rate as evaluation indicators, bench tests, adaptive threshing gap adjustment tests, and comparative tests were conducted. The experimental results indicated that the average adjustment errors of the control system for the threshing and separation section gap were 0.49 mm and 0.47 mm, respectively. Under the test combinations where the feed rates were 0~2 kg/s, 2~3 kg/s, and 3~4 kg/s, with corresponding threshing section gaps of 15 mm, 23 mm and 30 mm, and separation section gaps of 15 mm, 20 mm and 27 mm, the grain breakage rate, unthreshed grain rate, and entrainment loss rate were 2.73%, 0.30% and 0.42%, respectively. Compared with the constant gap tests, these values were reduced by 0.39, 0.27 and 0.28 percentage points, respectively. All evaluation indicators from the adaptive threshing gap adjustment tests outperformed those from the comparative tests. The research result can support the development of adaptive threshing gap control systems and the intelligent of the soybean combine harvester. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Design

Controlled terms: Control systems? - ?Grain (agricultural product)

Uncontrolled terms: Adaptive? - ?Breakage rates? - ?Combine harvesters? - ?Entrainment loss? - ?Feedrate? - ?Grain breakage? - ?Loss rates? - ?Rate loss? - ?Soybean? - ?Threshing gap

Classification code: 731.1 Control Systems? - ?821.5 Agricultural Products? - ?904 Design

Numerical data indexing: Mass flow rate 0.00E00kg/s to 2.00E+00kg/s, Mass flow rate 2.00E+00kg/s to 3.00E+00kg/s, Mass flow rate 3.00E+00kg/s to 4.00E+00kg/s, Percentage 2.73E+00%, Percentage 3.00E-01%, Percentage 4.20E-01%, Size 1.50E-02m, Size 2.00E-02m, Size 2.30E-02m, Size 2.70E-02m, Size 3.00E-02m, Size 4.70E-04m, Size 4.90E-04m

DOI: 10.6041/j.issn.1000-1298.2025.12.029

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

74. Design and Experiment of Light and Simple Rice-Wheat Harvesters’ Electric Intelligent Chassis

Accession number: 20255119745580

Title of translation: 轻简型稻麦收获机电动智能底盘设计与试验

Authors: Liu, Haolu (1); Shen, Cheng (1); Cao, Guangqiao (1); Hu, Lianglong (1); Li, Shangkun (1); Ding, Xiaobing (2); Zhao, Lijun (3); Hu, Delong (4)

Author affiliation: (1) Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing; 210014, China; (2) Chongqing Shineray Agricultural Machinery Co., Ltd., Chongqing; 401329, China; (3) College of Intelligent and Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing; 402160, China; (4) Department of Agronomy and Horticulture, Jiangsu Vocational College of Agriculture and Forestry, Jurong; 212400, China

Corresponding author: Shen, Cheng(shencheng@caas.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 78-86

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Hilly and mountainous areas are important grain production bases in China. The farmlands in these regions are characterized by small plot sizes, steep slopes, and narrow roads. Traditional fuel-driven chassis have disadvantages such as slow power response, inflexible steering, and low levels of intelligence. To address these issues, an electric intelligent chassis suitable for light and simple rice and wheat harvesters was designed. This machine adopted a distributed design to achieve flexible steering and a wide track design to adapt to rice harvesting operations in hilly and mountainous areas. Motion condition analysis was conducted, and the parameter design of the electric drive system and battery system was completed, solving the problem of slow power response of fuel-powered chassis. The software and hardware design of the motion control system was carried out, enabling remote control operation or autonomous navigation of the chassis. Performance tests and operation parameter optimization tests were conducted. Taking the harvesting speed, threshing drum speed, and cleaning fan speed as test factors, and the breakage rate, impurity rate, and loss rate as evaluation indicators, a Box-Behnken test was designed. The results of the Box-Behnken test were analyzed by variance, and a regression model between the evaluation indicators and the test factors was established. With the goal of minimizing the breakage rate, impurity rate, and loss rate, the optimal solution for the harvesting speed, threshing drum speed, and cleaning fan speed was obtained: the harvester’s harvesting speed was 0.8 m/s, the threshing drum speed was 1 000 r/min, and the cleaning fan speed was 2 786.15 r/min. Field tests showed that under this condition, the breakage rate was 0.42%, the impurity rate was 4.05%, and the loss rate was 0.87%. The machine operated smoothly during the operation period, and the operation indicators met the standards for mechanized rice and wheat harvesting. The test results indicated that the designed electric intelligent chassis could meet the operational requirements of the harvester. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Chassis

Controlled terms: Cleaning? - ?Electric drives? - ?Harvesters? - ?Harvesting? - ?Motion control? - ?Regression analysis

Uncontrolled terms: Breakage rates? - ?Distributed electric drive? - ?Drum speed? - ?Electric intelligent chassi? - ?Fan speed? - ?Hilly and mountainous areas? - ?Hybrid oil-electric? - ?Impurity rates? - ?Loss rates? - ?Rice-wheat harvester

Classification code: 601.3 Mechanisms? - ?602.1 Mechanical Drives? - ?662.3 Automobile Components and Materials? - ?705.1 Electric Machinery? - ?731.1 Control Systems? - ?731.3 Specific Variables Control? - ?802.3 Chemical Operations? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?1202.2 Mathematical Statistics

Numerical data indexing: Angular velocity 0.00E00rad/s, Angular velocity 1.312871E+01rad/s, Percentage 4.05E+00%, Percentage 4.20E-01%, Percentage 8.70E-01%, Velocity 8.00E-01m/s

DOI: 10.6041/j.issn.1000-1298.2025.12.006

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

75. Kinematics and Dynamics Analysis of 2 - RRC/1 RRS Parallel Manipulator

Accession number: 20255119732421

Title of translation: 2-RRC/1-RRS并联机器人运动学与动力学分析

Authors: Liu, Shanzeng (1, 2); Zhang, Zhujun (1); Meng, Dechao (1)

Author affiliation: (1) School of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying; 257061, China; (2) King’ s College London, London; WC2R 2LS, United Kingdom

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 56

Issue: 12

Issue date: December 2025

Publication year: 2025

Pages: 811-818

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: A novel stmcture model of 2 — RRC/1 —RRS parallel manipulator mechanism was proposed for the Screening of agrieultural materials, and its kinematics and dynamic characteristics were studied. Firstly, based on the motion characteristics of each branch chain in the 2 — RRC/1 — RRS parallel manipulator mechanism, the manipulator stmcture characteristics and the coupling relationship between the motion variables were analyzed. Secondly, the kinematics of the 2 — RRC/1 — RRS parallel mechanism was deduced, and the analytical expression of the inverse kinematics of the robot was given. Then based on the discussion of kinetic energy and potential energy of the 2 — RRC/1 — RRS parallel manipulator, the dynamic equation of the manipulator was derived by Lagrange equation method of classical mechanics. Finally, the dynamic characteristics of the 2 — RRC/1 — RRS parallel manipulator mechanism, such as motion parameters, driving torque and energy consumption, were discussed by an example. The results showed that the parameters of moment of inertia in the dynamics equation of the 2 — RRC/1 —RRS parallel manipulator System were closely related to the stmcture size of the manipulator, the mass size and mass distribution of each component, and the motion configuration of the manipulator, so as to determine the kinematics and dynamics characteristics of the 2 — RRC/1 — RRS parallel manipulator. The research content was of great significance to deeply understand the kinematics and dynamic characteristics of 2 — RRC/1 — RRS parallel manipulator, as well as the structural optimization design and the high-precision control of the manipulator, which can provide an idea for the innovative design of new equipment for agrieultural material Screening. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Kinetics

Controlled terms: Equations of motion? - ?Inverse kinematics? - ?Inverse problems? - ?Kinetic energy? - ?Lagrange multipliers? - ?Manipulators? - ?Molecular physics? - ?Potential energy? - ?Structural optimization

Uncontrolled terms: Dynamics characteristic? - ?Dynamics equation? - ?Energy? - ?Kinematic characteristics? - ?Kinematics and dynamics? - ?Kinematics and dynamics analysis? - ?Lagranges equations? - ?Material screening? - ?Motion characteristics? - ?Parallel manipulators

Classification code: 301.1 Fluid Flow? - ?691.1 Materials Handling Equipment? - ?1201 Mathematics? - ?1201.2 Calculus and Analysis? - ?1201.7 Optimization Techniques? - ?1301.1.1 Mechanics? - ?1301.1.3 Atomic and Molecular Physics

DOI: 10.6041/j.issn.1000-1298.2025.12.075

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village