2025年第3期
2025年第3期共收錄51篇
1. Current Status and Prospects of Crop Phenotyping Robots
Accession number: 20251318143735
Title of translation: 作物表型機(jī)器人研究現(xiàn)狀與展望
Authors: Song, Peng (1, 2); Li, Zhengda (1); Yang, Meng (1); Cui, Jiale (1); Feng, Hui (2, 3); Zhai, Ruifang (2, 3); Yang, Wanneng (1, 2)
Author affiliation: (1) College of Plant Science and Technology, Huazhong Agricultural University, Wuhan; 430070, China; (2) National Key Laboratory of Crop Cenetic Improvement, Huazhong Agricultural University, Wuhan; 430070, China; (3) College of Informatics, Huazhong Agricultural University, Wuhan; 430070, China
Corresponding author: Yang, Wanneng([email protected])
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 1-17
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: With the rapid development of bioteehnology, the demand for phenotypic traits in crop breeding research is on the rise, and data-driven intelligent breeding is gradually emerging as a significant direction in breeding studies. High-throughput phenotyping equipment can efficiently acquire phenotypic traits throughout the entire life cycle of crops. However, it had become a key bottleneck that restricted large-scale and efficient crop breeding research. As an emerging type of agricultural robot, crop phenotyping robots became a vital direction for future crop phenotyping due to their multiple advantages. These advantages included flexible mobility, time and space-unrestricted operation, strong expandability with the capability to carry various types of sensors, high-resolution data collection from multiple perspectives close to the ground, and high degree of intelligence enabling unmanned or minimally manned operation. Currently, there were reviews on crop phenotyping technology and the development of agricultural robots, but there were relatively few reviews specifically focused on crop phenotyping robots. The current research status of crop phenotyping robots both domestically and internationally was firstly and systematically summarized. Based on this, it elaborated on the overall architecture of phenotyping robots, sorted out their system control and navigation methods, and introduced in detail the methods of obtaining and analyzing phenotypic traits based on robots. Finally, it discussed the current application status and challenges faced by phenotyping robots in agricultural production and crop breeding, and looked ahead to the future development trend of phenotyping robots. Finally, the paper discusses the current applications and challenges of phenotyping robots in agricultural production and crop breeding, while outlining future trends characterized by three key developments; Robotic diversity innovation will propel high-throughput phenotyping toward scaled implementation, artificial intelligence will reconstruct deep learning frameworks for phenotypic analysis, and next-generation phenotyping robots leveraging multimodal sensor fusion technology will spearhead paradigm shifts in phenomics research. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 105
Main heading: Agricultural robots
Controlled terms: Livestock
Uncontrolled terms: ‘current? - ?Agricultural robot? - ?Analyze? - ?Crop phenotyping? - ?High-throughput phenotyping? - ?Intelligent breeding? - ?Phenotypic traits? - ?Phenotyping? - ?Phenotyping acquisition
Classification code: 731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products
DOI: 10.6041/j.issn.1000-1298.2025.03.001
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
2. Impact of Rigid Vegetation Coverage and Growth Orientation on Slope Runoff Detachment Capacity
Accession number: 20251418174185
Title of translation: 剛性植被覆蓋與生長方向?qū)ζ旅鎻搅鞣蛛x能力的影響
Authors: Cai, Zekang (1); Lei, Fengze (2); Xie, Jiabo (1); Wang, Chenfeng (1); Wang, Jian (1, 3)
Author affiliation: (1) Institute of Soil and Water Conservation, Northwest a and F University, Shaanxi, Yangling; 712100, China; (2) Water and Soil Conservation and Ecological Construction Center of Hengshan District, Yulin, Yulin City; 719000, China; (3) Institute of Soil and Water Conservation, Chinese Academy of Sciences, Ministry of Water Resources, 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 467-475
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to investigate the effects of rigid vegetation stem coverage and growth orientation on the runoff detachment capacity ( RDC ) of slopes, a series of simulated experiments were conducted under different combinations of slope gradients (5° ~20°) , coverage levels (0 ~ 15. 89% ) , and two vegetation growth orientations (perpendicular to the slope surface (BS) and perpendicular to the horizontal plane ( BH ) ) . The results showed that slope gradient significantly influenced the distribution range of RDC (p ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 38
Main heading: Shear stress
Controlled terms: Catchments? - ?Regression analysis? - ?Rivers? - ?Runoff? - ?Shear flow
Uncontrolled terms: Condition? - ?Correlation coefficient? - ?Growth orientations? - ?Prediction modelling? - ?Rigid vegetation? - ?Runoff detachment? - ?Runoff detachment capacity? - ?Stream power? - ?Vegetation coverage? - ?Vegetation orientation
Classification code: 214.1.1 Stress and Strain? - ?301.1.5 Flow of Fluid-Like Materials? - ?407 Maritime and Port Structures; Rivers and Other Waterways? - ?444 Water Resources? - ?1202.2 Mathematical Statistics? - ?1502.3 Hydrology
Numerical data indexing: Percentage 4.40E+01%, Percentage 4.90E+01%, Percentage 5.10E+01%, Percentage 5.70E+01%, Percentage 8.70E+01%, Percentage 8.90E+01%, Percentage 9.50E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.046
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
3. Experiment on Multi-effect Dust Removal System for Grain Drying Exhaust Gas
Accession number: 20251418174158
Title of translation: 糧食烘干廢氣多效除塵系統(tǒng)設(shè)計(jì)與試驗(yàn)
Authors: Chen, Kunjie (1); Chen, Xizhuang (1); Jing, Shiliang (1); Sun, Jie (2); Zhang, Xin (2); Yu, Haiming (1); Ji, Fan (1)
Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Lianyungang Jianfeng Modern Agricultural Industry Research Institute Co. Ltd.,, 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 513-522
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the lack of effective technologies and equipment for grain drying exhaust gas treatment, which affects the development of grain drying industry, a multi-effect dust removal technology and equipment integrating centrifugal sedimentation, agglomeration, and spray action for grain drying exhaust gas was developed. Initially, through simulation experiments, the effects of spray tower airflow velocity, spray angle, and spray pressure on the droplet field were analyzed. Single-factor experiments validated the simulation results and determined the appropriate range for airflow velocity, spray angle, and pressure. Subsequently, aiming for the highest dust removal efficiency, a three-factor three-level quadratic orthogonal regression experiment was carried out to construct a regression equation and response surface. The effects of airflow velocity, spray angle, and spray pressure on dust removal efficiency were analyzed for parameter optimization. It was proven that a uniform droplet field can be achieved at airflow velocities between 0. 89 m/s and 1. 33 m/s, spray angles between - 15° and 0°, and spray pressures between 1 MPa and 1. 5 MPa. The optimal parameter combination was identified as an airflow velocity of 0. 92 m/s, a spray angle of - 8. 4° , and a spray pressure of 1. 44 MPa. Experimental results showed that after optimization, the highest dust removal efficiency could reach 96. 27% . Compared with a pulse dust collector, the average dust mass concentration of the grain drying exhaust gas treated by the multi-effect dust collector was 5. 54 mg/m , which was lower than 7. 05 mg/m produced by the pulse dust collector and significantly below the national emission standard. This demonstrates that the treated grain drying exhaust gas can meet the emission standards using the developed multi-effect dust collector. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 17
Main heading: Dust collectors
Controlled terms: Dust control? - ?Exhaust gases
Uncontrolled terms: Air flow velocity? - ?Dust removal efficiency? - ?Grain drying? - ?Grain drying exhaust gas? - ?Multi-effect? - ?Response-surface methodology? - ?Simulation? - ?Spray angle? - ?Spray pressure? - ?Technology and equipments
Classification code: 1502.1.1.1.1 Air Pollution Sources? - ?1502.1.1.4.1 Air Pollution Control
Numerical data indexing: Mass 5.00E-06kg, Mass 5.40E-05kg, Percentage 2.70E+01%, Pressure 1.00E+06Pa, Pressure 4.40E+07Pa, Pressure 5.00E+06Pa, Velocity 3.30E+01m/s, Velocity 8.90E+01m/s, Velocity 9.20E+01m/s
DOI: 10.6041/j.issn.1000-1298.2025.03.051
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
4. Classification of Degradation Films and Estimation of Degradation Rate Based on Multispectral Fusion Images
Accession number: 20251418174193
Title of translation: 基于多光譜融合影像的降解膜分類與降解率估算研究
Authors: Chen, Maoguang (1); Yin, Caixia (1); Xi, Bin (2); Jin, Tuo (2); Liu, Liyang (1); Lin, Tao (3, 4); Jiang, Ping’an (1); Shao, Yajie (1); Tang, Qiuxiang (1)
Author affiliation: (1) College of Agriculture, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Agricultural Ecology and Resource Protection Station, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (3) Institute of Cash Crops, Xinjiang Academy of Agricultural Sciences, Urumqi; 830091, China; (4) Key Laboratory of Crop Physiology Ecology and Farming in Desert Oasis,, Ministry of Agriculture and Rural Affairs, Urumqi; 830091, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 345-353 and 373
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 traditional residual film pollution investigation, such as time-consuming manual identification of mulch film, high labor intensity and larger human error, based on UAV multispectral fusion imagery, using maximum likelihood classification ( ML) , minimum distance classification (MD) and spectral angle mapper classification ( SAM) in supervised classification, the residual film images of four degradation films in cotton field were classified, and the degradation rate estimation model was constructed by combining Bayesian ridge regression ( BRR ) , support vector regression (SVR) and K nearest neighbor regression (KNNR) modeling methods, so as to realize the rapid investigation of the degradation of degradation film in cotton field. The results showed that ML had a better effect on the classification of degradable films than MD and SAM, with an average error of less than 0. 023 and a correlation coefficient higher than 0. 9 with the measured results. Combined with different machine learning algorithms to construct the model, the ML - BRR degradation rate estimation model had the best fitting effect and generalization ability, and the R of the training set and testing set were 0. 756 ~ 0. 966 and 0.823 ~ 0. 921 , respectively, and RMSE were not more than 2.698% and 3.098% , respectively. Based on UAV multispectral fusion images, the maximum likelihood classifier was used to classify residual film and soil, and the degradation rate estimation model was constructed in combination with BRR algorithm, which was feasible to realize the rapid diagnosis of degradation of degradable film in cotton field, so as to provide an idea for the rapid investigation of residual film and provide reference materials for the improvement of residual film pollution control measures. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 40
Main heading: Ability testing
Controlled terms: Air pollution control? - ?Bioremediation? - ?Health risks? - ?Image enhancement? - ?Maximum likelihood? - ?Nearest neighbor search? - ?Soil pollution control? - ?Soil testing? - ?Support vector regression? - ?Unmanned aerial vehicles (UAV)
Uncontrolled terms: Cotton fields? - ?Degradable film? - ?Degradation rate? - ?Maximum-likelihood classification? - ?Multispectral fusion? - ?Multispectral images? - ?Rate estimation? - ?Residual films? - ?Unmanned air vehicle? - ?Unmanned air vehicles
Classification code: 102.1.2.1 Health Care? - ?483.1 Soils and Soil Mechanics? - ?652.1 Aircraft? - ?912.3 Personnel? - ?1101.2 Machine Learning? - ?1106.3.1 Image Processing? - ?1201.7 Optimization Techniques? - ?1502.1 Environmental Impact and Protection? - ?1502.1.1.4.1 Air Pollution Control? - ?1502.1.1.4.3 Soil Pollution Control? - ?1502.4 Biodiversity Conservation
Numerical data indexing: Percentage 2.698E+00%, Percentage 3.098E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.034
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
5. Rice Transplanter with Double Helix Drive for Deep Muddy Paddy Fields of Hilly Regions
Accession number: 20251418174172
Title of translation: 雙螺旋驅(qū)動(dòng)式丘陵山區(qū)深泥腳水田插秧機(jī)設(shè)計(jì)與試驗(yàn)
Authors: Chen, Xingzheng (1, 2); Zhou, Hao (1, 2); Xie, Shouyong (1, 2); Song, Youtian (1, 2); Liu, Fanyi (1, 2); Xie, Xiaobin (1, 2)
Author affiliation: (1) College of Engineering Technology, Southwest University, Chongqing; 400715, China; (2) Southwest Agricultural Equipment Innovation Center, Chongqing; 400715, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 247-255
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Deep muddy paddy fields are widely spread in southern hilly regions of China. In these paddy fields, the rice transplanter is often trapped due to the poor soil bearing capacity, resulting in unnecessary interruption of rice transplanting or mechanical failure of the rice transplanter. Aiming to address these issues, a novel rice transplanter equipped with double helix drive was proposed. Firstly, the motion principle the proposed rice transplanter was analyzed and its parametric design model was constructed. Then the relationship between propulsion force and parameters of spiral structure as well as the driving direction was modeled. Finally, a prototype of the transplanter was developed and tested under different conditions. From the results of the experiments, it can be found that the proposed rice transplanter had exceptional stability and superior transplanting performance in deep muddy paddy fields. When the rotating speed of the spiral wheel was 1. 33 r/s, the working speed of the rice transplanter was 1. 02 m/s. As a result, the slip rate of the rice transplanter reached the maximum value of 3. 045% . However, the settlement of the rice transplanter was decreased with the increase of speed of spiral wheel. The maximum settlement was decreased significantly from 148.67 mm to 59.74 mm. Furthermore, in fields with a 430 mm mud depth, the transplanter’ s maximum uncontrolled linear deviation was 0. 021 m. Based on the presented work, manufacturers can easily develop a rice transplanter for deep muddy paddy fields in southern hilly regions of China, which would be a useful rice transplant equipment to overcome the unnecessary interruption of rice transplanting or mechanical failure of the rice transplanter. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 25
Main heading: Wheels
Controlled terms: Agricultural robots? - ?Bearings (machine parts)? - ?Fracture mechanics? - ?Rotating machinery
Uncontrolled terms: Deep muddy paddy field? - ?Design models? - ?Double helix? - ?Double helix drive? - ?Mechanical failures? - ?Paddy fields? - ?Parametric design? - ?Propulsion parameter? - ?Rice transplanter? - ?Soil bearing capacity
Classification code: 214.1.2 Fatigue, Cracks and Fracture? - ?601.1 Mechanical Devices? - ?601.2 Machine Components? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?1301.1.1 Mechanics
Numerical data indexing: Percentage 4.50E+01%, Size 1.4867E-01m to 5.974E-02m, Size 2.10E+01m, Size 4.30E-01m, Velocity 2.00E+00m/s
DOI: 10.6041/j.issn.1000-1298.2025.03.025
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
6. Design and Experimentation of Autonomous Navigated Citrus Phenotype Inspection Robot
Accession number: 20251418168005
Title of translation: 自主導(dǎo)航柑橘表型巡檢機(jī)器人設(shè)計(jì)與試驗(yàn)
Authors: Chen, Yaohui (1, 2); Li, Jiayi (1, 2); Bao, Zehan (3); Hao, Guoqiang (1, 2); Yu, Yonghua (1, 2); Li, Shanjun (1, 2)
Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key Laboratory of Agricultural Equipment in Mid-lower Yangtze River, Ministry of Agriculture and Rural Affairs, Wuhan; 430070, China; (3) College of Informatics, Huazhong Agricultural University, Wuhan; 430070, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 49-57
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to improve the automation level of citrus nursery, a fully automated phenotype inspection robot suitable for citrus nursery was proposed. Firstly, SLAM mapping of the nursery environment was performed by combining 3 D LiDAR and inertial guidance information, and the obtained 3D point cloud map was preprocessed and projected to obtain a 2D map suitable for planning and navigation. Then the HDL _ localization positioning algorithm was used for accurate positioning, and combined with the Dijkstra algorithm and TEB algorithm, to achieve the optimization of local paths while global path planning, plan the ideal inspection route, and ensure the reliability and safety of inspection. During the inspection process, the YOLO v8 network running on the industrial computer continuously processed the images from the depth cameras on both sides of the robot, recognized the citrus seedlings in the images, calculated the plant height, and uploaded these data to the network database in real time. Three different methods were proposed and compared for citrus seedling plant height calculation. The experiments proved that the localization of the inspection robot on autopilot had an average localization error of 5. 6 cm and a maximum localization error of 17. 5 cm compared with the true value obtained from high-precision RTK localization, and the height of the citrus seedlings obtained by using the optimal computation method had an average absolute error of 1. 88 cm, a maximum absolute error of 7 cm, and a mean-square error of 5. 93 cm compared with the true value of the manual measurements. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Mean square error
Controlled terms: Citrus fruits? - ?Cloud seeding? - ?Industrial robots? - ?Inertial navigation systems? - ?Interpolation? - ?Motion planning? - ?Robot programming? - ?SLAM robotics
Uncontrolled terms: Automation levels? - ?Citrus nursery? - ?Driverless? - ?Fully automated? - ?Inspection robots? - ?Localisation? - ?Localization errors? - ?Phenotype? - ?Plant height? - ?YOLO v8
Classification code: 435.1 Navigation? - ?443.3 Precipitation? - ?731.5 Robotics? - ?731.6 Robot Applications? - ?821.5 Agricultural Products? - ?1101 Artificial Intelligence? - ?1106.1 Computer Programming? - ?1201.9 Numerical Methods? - ?1202.2 Mathematical Statistics
Numerical data indexing: Size 5.00E-02m, Size 6.00E-02m, Size 7.00E-02m, Size 8.80E-01m, Size 9.30E-01m
DOI: 10.6041/j.issn.1000-1298.2025.03.005
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
7. Design and Experiment of Static Mixer for Direct Injection Inline Mixing System
Accession number: 20251418174152
Title of translation: 直接注入式在線混藥系統(tǒng)靜態(tài)混藥器設(shè)計(jì)與試驗(yàn)
Authors: Chen, Yu (1); Chen, Yuxiang (1); Guo, Peijie (1); Zhang, Shuo (1); Jin, Hongling (1); Chen, Jun (1)
Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest a and 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 301-311
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In-line pesticide mixing technology offers an effective solution to challenges such as health threats to operators, environmental pollution, and the wastage of pesticide solutions associated with traditional premix methods. Focusing on the design of a static mixer intended for use in an in-line pesticide mixing system, to verify optimal performance, the mixing characteristics of the in-line flow field were investigated through computational fluid dynamics (CFD) simulations. Single-factor test, Plackett - Burman test, and Box - Behnken center combination test were employed to evaluate the static mixer pressure drop and mixing uniformity. The impacts of parameters such as tilt spoiler angle, center through-hole diameter, mixing unit spacing, and flow-through hole diameter on the evaluation indexes were analyzed by using the response surface method. On this basis, multi-objective optimization, targeting low-pressure drop and high mixing uniformity was conducted through a genetic algorithm. The optimal structural parameters were determined as follows; spoiler inclination of 55. 38°, mixing unit spacing of 22.64 mm, and pore size of 1.64 mm. Bench tests for pressure drop and mixing uniformity were conducted under specific conditions; electric control valve opening for liquid pesticide injection at 33% , continuous operation of the pesticide pump, and variable working gears for the water pump. The results indicated an increasing trend in pressure drop within the Reynolds number range of 5 984 ~ 13 286 and the pressure drop factor was less than 106. 7. The coefficient of variation for mixing uniformity exhibited a decreasing trend, and it was less than 0. 008 5 , indicating the reliable performance of the static mixer. The research results can provide reference for the development and structure optimization of static mixer in China. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Reynolds number
Controlled terms: Bioremediation? - ?Linear programming? - ?Mixers (machinery)? - ?Multiobjective optimization? - ?Pesticides? - ?Pressure drop? - ?Safety valves? - ?Shape optimization? - ?Structural optimization
Uncontrolled terms: Hole diameter? - ?In-line mixing? - ?In-line pesticide mixing? - ?Mixing system? - ?Mixing uniformities? - ?Mixing units? - ?Plant protection? - ?Plant protection sprayer? - ?Static mixers? - ?Through hole
Classification code: 301.1 Fluid Flow? - ?601.1 Mechanical Devices? - ?610.1.1 Pipe Accessories? - ?802.1 Chemical Plants and Equipment? - ?821.3 Agricultural Chemicals? - ?914.1 Accidents and Accident Prevention? - ?1201.7 Optimization Techniques? - ?1502.1 Environmental Impact and Protection? - ?1502.1.1.3 Soil Pollution? - ?1502.4 Biodiversity Conservation
Numerical data indexing: Percentage 3.30E+01%, Size 1.64E-03m, Size 2.264E-02m
DOI: 10.6041/j.issn.1000-1298.2025.03.030
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
8. Three-dimensional Reconstruction and Phenotypic Parameters Acquisition of Leafy Vegetables Based on Kinect V3 Sensor
Accession number: 20251418174150
Title of translation: 基于Kinect V3傳感器的葉菜類作物三維重建與表型參數(shù)獲取
Authors: Chen, Yunlin (1); Lan, Yubin (1, 2); Han, Xin (1, 2); Wang, Juan (1); Wang, Huizheng (1, 2); Fu, Liang (3)
Author affiliation: (1) College of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo; 255049, China; (2) Shandong University OfTechnology, Academy of Ecological Unmanned Farm, Zibo; 255049, China; (3) Shandong Siyuan Agricultural Development Co., Ltd.,, Zibo; 255400, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 101-110 and 197
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Crop three-dimensional reconstruction is an effective means to realize crop phenotype quantification and accurate acquisition, and can provide basic data support for breeding and cultivation. A nondestructive acquisition method for three-dimensional reconstruction and phenotypic parameters of leafy vegetable crops were presented based on Kinect V3 sensor. Firstly, a low-cost three-dimensional reconstruction platform that can realize rapid acquisition of multi-view point clouds of crops was designed. The loading surface of the platform was designed as multiple calibration points, and the table surface information can be used for point cloud horizontal calibration. Secondly, the multi-view point clouds obtained were registered and spliced by combining the carrier platform restoration and the generalized iterative closest point (GICP) algorithm to realize the three-dimensional reconstruction of leafy vegetable crops. Finally, through effective phenotypic parameter measurement, the accurate acquisition of phenotypic parameters such as plant height, leaf length, leaf width , and leaf area of leafy vegetable crops was achieved. To evaluate the similarity of this method, seedling plants of Malabar spinach, cabbage, eggplant, and purple back sunflower were selected as test objects and compared with the SFM - MVS method. The test results showed that the average distance errors between the point clouds of Malabar spinach, cabbage, eggplant, and purple back sunflower were 0.381 cm, 0.340 cm, 0. 195 cm, and 0.270 cm respectively, and the three-dimensional reconstruction results of the two had high similarity. Compared with the manual measured values, the determination coefficients of plant height, leaf length, leaf width, and leaf area of Malabar spinach and purple back sunflower extracted by this method were not less than 0. 903 , and the average absolute percentage error was not higher than 9. 759% . The root mean square errors of plant height, leaf length, leaf width, and leaf area of Malabar spinach and purple back sunflower were 0.366 cm, 0.203 cm, 0.290 cm, 3.182 cm and 0.496 cm, 0.344 cm, 0.282 cm, 0.825 cm , respectively, indicating that it had high measurement accuracy. The above method can provide a fast and efficient way for crop phenotype acquisition for facility agriculture breeding and cultivation. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 25
Main heading: Vegetables
Controlled terms: Seed? - ?Strain measurement? - ?Velocity measurement
Uncontrolled terms: Kinect v3 sensor? - ?Leaf length? - ?Leafy vegetable crop? - ?Leafy vegetables? - ?Phenotypic parameter? - ?Plant height? - ?Point-clouds? - ?Similarity? - ?Three-dimensional reconstruction? - ?Vegetable crops
Classification code: 821.5 Agricultural Products? - ?941.5 Mechanical Variables Measurements????? - ?942.1.7 Special Purpose Instruments
Numerical data indexing: Percentage 7.59E+02%, Size 1.95E+00m, Size 2.03E-03m, Size 2.70E-03m, Size 2.82E-03m, Size 2.90E-03m, Size 3.182E-02m, Size 3.40E-03m, Size 3.44E-03m, Size 3.66E-03m, Size 3.81E-03m, Size 4.96E-03m, Size 8.25E-03m
DOI: 10.6041/j.issn.1000-1298.2025.03.010
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
9. Comparison on Mechanical Simulation and Performance Testing for Adaptive Litchi Pitting
Accession number: 20251418174187
Title of translation: 自適應(yīng)荔枝果去核力學(xué)仿真與性能試驗(yàn)
Authors: Chen, Zhen (1); Peng, Zhikang (1); Xu, Fengying (1); Li, Changyou (1); Jiang, Zhuo (1); Luo, Juchuan (1)
Author affiliation: (1) Key Laboratory of Key Technology on Agricultural Machine and Equipment, South China Agricultural University, Ministry of Education, 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 503-512 and 530
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Pitting is an essential step for producing litchi lantern flesh, while the variable pit size poses a challenge for efficient and successful mechanical pitting. To solve this problem, an adaptive pitting tool and mechanism was designed by measuring the physical properties of litchi fruit, and the spatiotemporal changes of equivalent stress and cutting stress during the pitting process of litchi at three different rotational speeds were investigated, based on the LS - DYNA dynamic simulation and bench tests. Furthermore, it quantified and compared the success rates and pulp loss rates of adaptive pitting for litchi fruit with variable pit sizes at different rotational speeds, and evaluated the overall pitting performance. Lychee fruit and kernel sphericity coefficients of 0.95 and 0.74 were obtained, and their three-dimensional radial dimensions showed normal distributions. The simulation results indicated the effects of rotational speed on the distribution of effective stress and the extreme values of cutting stress in litchi fruit was consistent with the bench test results. As rotational speed increased, both the maximum equivalent stress and maximum cutting stress in the litchi were decreased, leading to improved success rates for adaptive pitting of litchi with variable pit size. Among the three tested rotation speeds (feed with speeds of 100 mm/min and 20 mm depth ) , pitting at 292 r/min demonstrated the best overall pitting performance, with a 100% success rate and a pulp loss rate of 22.4% , respectively. The revealed adaptive pitting mechanism were significant for developing high-quality and efficient pitting devices for stone fruits, including but not limited to litchi. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 20
Main heading: Rotation rate
Uncontrolled terms: Adaptive? - ?Bench tests? - ?Dynamics simulation? - ?Equivalent stress? - ?Litchi fruit? - ?LS - DYNA dynamic simulation? - ?LS-DYNA? - ?Pittings? - ?Rotational speed? - ?Variable pit size
Classification code: 1301.1.1 Mechanics
Numerical data indexing: Percentage 1.00E+02%, Percentage 2.24E+01%, Size 1.00E-01m, Size 2.00E-02m, Angular velocity 4.8764E+00rad/s
DOI: 10.6041/j.issn.1000-1298.2025.03.050
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
10. Design and Experiment of Precise Variable Fertilization Control System for Oilseed Rape Based on Prescription Maps
Accession number: 20251418174173
Title of translation: 基于處方圖的油菜精準(zhǔn)變量施肥調(diào)控系統(tǒng)設(shè)計(jì)與試驗(yàn)
Authors: Ding, Youchun (1, 2); Li, Haopeng (1, 2); Dong, Wanjing (1, 2); Zhang, Dongjin (1, 2); Xu, Chunbao (1, 2)
Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key Laboratory of Agricultural Equipment in Mid-lower Yangtze River, Ministry of Agriculture and Rural Affairs,, Wuhan; 430070, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 256-266 and 300
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the current reality of low accuracy of fertilizer regulation and control during the fertilizer application operation of oilseed rape direct seeding machine, and the difficulty of realizing spatiotemporal differentiated fertilizer replenishment with different soil fertility distributions, an accurate variable fertilizer application linear self-resistant regulation and control system was designed based on the prescription map for oilseed rape. A method of raster division of the fertilizer prescription map based on the cloud-based high-precision map planning operation path was proposed, which provided a guiding fertilizer amount for the machine fertilizer application. A linear self-immunity control algorithm for fertilizer dischargers was constructed. Matlab simulation determined the key parameters, and comparison with the PID control algorithm showed that the linear self-immunity control algorithm improved the anti-interference, overshooting amount, and steady-state error by 39.08% , 91.77% , and 86.96% , respectively, compared with the latter. The results of the bench test showed that the average control accuracy of the fertilizer dispenser’s granular fertilizer discharge was 98. 06% under the set fertilizer application rate and operating speed of the fertiliser application regulation system. The road test results indicated that the prescription map-based variable fertilization control system, after compensating for lag distance during variable fertilization operations, achieved an average fertilization position lag distance of 0. 28 m, with the control accuracy of fertilizer application volume exceeding 95.67% across different positions. The results of the field test showed that the linear self-immunity control algorithm had a control accuracy of no less than 95. 21% of the fertilizer amount in different grid areas, which was better than the PID control algorithm. The research result can provide an effective reference for accurate variable fertilizer application based on soil nutrients in oilseed rape production. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 31
Main heading: MATLAB
Controlled terms: Agricultural robots? - ?Automobile testing? - ?Bioremediation? - ?Disturbance rejection? - ?Elastin? - ?Fertilizers? - ?Three term control systems
Uncontrolled terms: Control accuracy? - ?Fertilizer applications? - ?Fertilizer prescription map? - ?Linear active disturbance rejection controls? - ?Oil seed rape? - ?PID control algorithm? - ?Prescription map? - ?Regulation and control? - ?Self-immunity? - ?Variable fertilizations
Classification code: 203 Biomaterials? - ?662 Automobiles and Smaller Vehicles? - ?731 Automatic Control Principles and Applications? - ?731.1 Control Systems? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.3 Agricultural Chemicals? - ?1106.5 Computer Applications? - ?1201.5 Computational Mathematics? - ?1502.1 Environmental Impact and Protection? - ?1502.1.1.3 Soil Pollution? - ?1502.4 Biodiversity Conservation
Numerical data indexing: Percentage 2.10E+01%, Percentage 3.908E+01%, Percentage 6.00E+00%, Percentage 8.696E+01%, Percentage 9.177E+01%, Percentage 9.567E+01%, Size 2.80E+01m
DOI: 10.6041/j.issn.1000-1298.2025.03.026
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
11. Three Dimensional Reconstruction and Phenotype Extraction of Wheat Root Syste Based on SFM and Optical Correction
Accession number: 20251418174111
Title of translation: 基于SFM +光學(xué)校正的小麥根系三維重建與表型提取方法
Authors: Duan, Lingfeng (1); Wang, Xinyi (1); Wei, Hanzhi (1); Wang, Xusheng (1); Yang, Wanneng (2)
Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) National Key Laboratory of Crop Cenetic Improvement, Huazhong Agricultural University, Wuhan; 430070, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 18-26
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Wheat is one of the most important food crops in the world, and its root system serves as a key organ for water and nutrient absorption. Its phenotypic characteristics are of great significance for understanding the growth status of wheat and soil environment. However, the underground growth characteristics of the root system pose challenges for its observation. A wheat aquatic cultivation device, a flexible liquid exchange device based on siphon principle, and a root image acquisition system were developed. An image refraction correction method was developed for the system. Then a three-dimensional point cloud model of the root system was constructed by using SFM algorithm, and relevant surface features were extracted. Experimental results showed that the flexible liquid exchange device increased the similarity of root image structure before and after liquid exchange to 0. 98. The refraction correction method reduced image errors by 62%. Furthermore, the proposed device and method were utilized to investigate the influence of nitrogen environment on the growth and development of wheat roots. The research results indicated that under low nitrogen conditions, wheat roots exhibited a deeper and more densely distributed growth trend. In addition, compared with nitrogen efficient varieties, nitrogen inefficient varieties were more sensitive to changes in nitrogen environment. The device and method proposed can contribute to high-throughput three-dimensional phenotype analysis of plant roots, opening up a perspective for root research in the development of smart agriculture driven by big data. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Siphons
Controlled terms: Phytoplankton
Uncontrolled terms: Correction method? - ?Images processing? - ?Liquid exchange? - ?Phenotype extraction? - ?Refraction correction? - ?Root system? - ?SFM? - ?Three-dimensional reconstruction? - ?Wheat root system? - ?Wheat roots
Classification code: 103 Biology? - ?610.1 Pipe, Piping, and Pipelines
Numerical data indexing: Percentage 6.20E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.002
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
12. High Throughput Cotton Yield Estimation Based on Multi-source Remote Sensing Data from Unmanned Aerial Vehicles and Machine Learning
Accession number: 20251418167636
Title of translation: 基于無人機(jī)多源遙感數(shù)據(jù)和機(jī)器學(xué)習(xí)的高通量棉花估產(chǎn)研究
Authors: Feng, Meichen (1); Su, Yue (1, 2); Lin, Tao (3, 4); Yu, Xun (2); Song, Yang (2); Jin, Xiuliang (2)
Author affiliation: (1) College of Agronomy, Shanxi Agricultural University, Taigu; 030801, China; (2) Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing; 100081, China; (3) Institute of Cash Crops, Xinjiang Academy of Agricultural Sciences, Urumqi; 830091, China; (4) Key Laboratory of Crop Physiology, Ecology and Cultivation in Desert Oasis, Ministry of Agriculture and Rural Affairs, Urumqi; 830091, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 169-179
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to utilize information from spectral data, canopy structure, and texture features for cotton yield estimation through unmanned aerial vehicle ( UAV) remote sensing, while systematically analyzing the contribution of these factors to yield estimation, based on the construction of a machine learning model for cotton yield estimation by using multi-source UAV data, the optimal growth stage for yield estimation was further identified and the effectiveness of multi-source sensor data in estimating cotton yield was compared. Finally, the contribution of various input features was quantified. Data were collected from three types of sensors; RGB ( red, green, blue) , multi-spectral ( MS) , and light detection and ranging ( LiDAR) . By conducting a correlation analysis between cotton spectral vegetation indices and yield, the optimal growth stage for cotton yield estimation was determined. Subsequently, yield estimation methods were developed by using three machine learning models; partial least squares regression (PLSR) , random forest regression ( RFR) , and extreme gradient boosting (XGBoost). The performance of models based on the two most commonly used sensors ( RGB and MS cameras) was evaluated. The results confirmed that the flowering stage was the optimal growth period for cotton yield estimation. Using UAV data from the flowering stage, the XGBoost model achieved the highest yield estimation accuracy ( R was 0. 70, RMSE was 611.31 kg/hm2, rRMSE was 10. 60% ) . When comparing features extracted from RGB and MS image data, the modeling results based on MS camera data were superior. Additionally, when features extracted from both RGB and MS camera data were used as inputs, the model performance exceeded that of single-sensor data. The Shapley additive explanations ( SHAP) algorithm was employed to analyze the contribution of each input feature in the machine learning models for yield estimation. It was found that the three types of feature information derived from the three sensors were all significant for yield estimation, with texture features and canopy structure demonstrating considerable potential in this regard. The research result can provide theoretical and technical support for high-throughput cotton yield estimation in smart cotton management. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 48
Main heading: Cotton
Controlled terms: Adaptive boosting? - ?Agricultural robots? - ?Decision trees? - ?Image coding? - ?Network security? - ?Photomapping? - ?Random forests? - ?Steganography? - ?Time difference of arrival? - ?Unmanned aerial vehicles (UAV)
Uncontrolled terms: Aerial vehicle? - ?Multi-source data? - ?Multi-Sources? - ?Remote-sensing? - ?Shapley? - ?Shapley additive explanation? - ?Source data? - ?Unmanned aerial vehicle remote sensing? - ?Xgboost? - ?Yield estimation
Classification code: 405.3 Surveying? - ?652.1 Aircraft? - ?716.1 Information Theory and Signal Processing? - ?731.6 Robot Applications? - ?742.1 Photography? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?961 Systems Science? - ?1101.2 Machine Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1106.3.1 Image Processing? - ?1108.2 Cryptography? - ?1201.5 Computational Mathematics? - ?1201.8 Discrete Mathematics and Combinatorics, Includes Graph Theory, Set Theory
Numerical data indexing: Mass 6.1131E+02kg, Percentage 6.00E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.017
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
13. Lateral Branch Excitation Coupled Walnut Fruit Harvesting Method and Device
Accession number: 20251418174159
Title of translation: 側(cè)枝激振耦合式核桃采果方法與裝置研究
Authors: Guo, Guanzhu (1, 2); Wang, Tong (1); Luo, Ya’nan (1, 2); Wang, Zhengguang (1); Yang, Liyang (1); Jin, Guangye (1)
Author affiliation: (1) College of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming; 650201, China; (2) Cuo Cuanzhu Expert Grassroots Research Station of Dali Rongyang Walnut Machinery Manufacturing Co. Ltd.,, Dali; 672599, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 279-290
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: For the existing portable walnut side branch vibration fruit picking device required fruit picking excitation force and side branch physical characteristics of the coupling relationship between the problem is not clear, the side branch excitation coupling walnut fruit picking method was put forward, in the theoretical analysis of the picking load excitation force frequency and walnut side branch inherent frequency was the same so as to form the excitation coupling based on the theoretical analysis of the excitation picking parameters and the side branch of the theoretical model of the physical characteristics of the coupling between the excitation picking parameters and the side branch excitation, the excitation acceleration and coupling excitation force under the coupling conditions were analyzed through simulation analysis of the side branch excitation, the side branch excitation coupling walnut fruit picking device was designed, the fruit picking performance of the side branch excitation coupling walnut fruit picking device was analyzed, and the fruit picking performance of the side branch excitation coupling walnut fruit picking device was experimentally verified. The results showed that the closer the frequency of the fruit picking excitation loading force was to the intrinsic frequency of the lateral branch, the easier it was to form an excitation coupling between the lateral branch and the excitation loading force. For the diameter of walnut lateral branches and the distance of the excitation loading position from the main branch stem were 30 mm and 1313 mm, 40 mm and 1 552 mm, 50 mm and 1 686 mm, and the rated power of the fruit picking device was 300 W. When the amplitude of the excitation loading force was 15 N and the intrinsic frequency of the lateral branches were 8. 80 Hz, 8. 40 Hz and 8. 90 Hz, respectively, the simulated values of lateral branch vibration acceleration reached 69. 2 m/s , 56. 1 m/s and 72. 9 m/s , respectively, and the experimental values were 66. 4 m/s , 56. 3 m/s and 74. 2 m/s , which were consistent with each other. When the fruit hanging mass of single lateral branch walnut was 2. 0 kg, the fruit picking efficiency reached 60. 0 kg/h. The walnut fruit picking net rate was closely related to the maturity. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 20
Main heading: Fruits
Controlled terms: Couplings? - ?Vibration analysis
Uncontrolled terms: Condition? - ?Condition of fruit falling by vibration? - ?Excitation force? - ?Harvesting efficiency? - ?Lateral branch excitation coupling? - ?Loading force? - ?Physical characteristics? - ?Picking machineries? - ?Side branches? - ?Walnut picking machinery
Classification code: 601.2 Machine Components? - ?602.1 Mechanical Drives? - ?821.5 Agricultural Products? - ?941.5 Mechanical Variables Measurements????
Numerical data indexing: Force 1.50E+01N, Frequency 4.00E+01Hz, Frequency 8.00E+01Hz, Frequency 9.00E+01Hz, Mass 0.00E00kg, Power 3.00E+02W, Size 1.313E+00m, Velocity 4.00E+00m/s, Velocity 9.00E+00m/s, Size 3.00E-02m, Size 4.00E-02m, Size 5.00E-02m, Size 5.52E-01m, Size 6.86E-01m, Velocity 1.00E00m/s, Velocity 2.00E+00m/s, Velocity 3.00E+00m/s
DOI: 10.6041/j.issn.1000-1298.2025.03.028
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
14. Refinement and Identification of Rural Revitalization Classification System Based on Self-organizing Development Patterns of Villages
Accession number: 20251418168405
Title of translation: 基于鄉(xiāng)村自組織演化規(guī)律的村莊分類振興體系完善與類型識(shí)別
Authors: Li, Mengwei (1); Jin, Yaya (2); Sun, Yuting (1); Jin, Xiangmu (1)
Author affiliation: (1) School of Public Affairs, Zhejiang University, Hangzhou; 310058, China; (2) College of Economics and Management, Northwest a and 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 323-333
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Guided by the theory of rural self-organization evolution, the endogenous and exogenous classification differences within the national rural revitalization classification system were systematically explored, which encompassed characteristic protection villages, suburban integrated villages, agglomeration villages, and relocation villages. The classification framework was refined from four to five categories and enhanced recognition methodologies that accounted for the quantity, quality, and spatial characteristics of village evolution. The results showed that for exogenously driven classifications, such as suburban integrated villages, characteristic preservation villages, and exogenous relocated villages, flowchart methods should be applied for identification. For classifications driven by endogenous development differences, such as agglomeration villages and endogenous relocated villages, the identification should follow the self-organizing evolution patterns of villages. Through self-organizing evolution, villages exhibited an ordered differentiation pattern of “ decay - normal - prosperity” with distinct quantity, quality, and spatial characteristics. This led to the improvement of endogenous classifications of “ relocation - existence - agglomeration” . Accordingly, employing an improved gravity model alongside a county-town scale overlay model for village evaluations offered a viable solution that aligned with the self-organizing evolutionary patterns of rural areas. Taking county L as an example, the theoretical hypotheses were tested, and the rural revitalization classification system was identified. The final classification results aligned with the quantity, quality, and spatial laws of rural self-organizing evolution. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 25
Uncontrolled terms: Classification system? - ?Gravity modeling? - ?Improved gravity model? - ?Quality characteristic? - ?Rural revitalization? - ?Rural self-organization? - ?Self organizations? - ?Self-organising? - ?Village classification? - ?Village differentiation
DOI: 10.6041/j.issn.1000-1298.2025.03.032
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
15. Prediction Method for Soil Heavy Metal Content Based on Covariates over Proximally Sensed Spectra
Accession number: 20251418174184
Title of translation: 基于近地傳感光譜協(xié)同的土壤重金屬含量空間分布預(yù)測方法
Authors: Li, Shuo (1, 2); Wang, Yajin (1); Qin, Weilin (3); Mo, Xiaoming (4); Hu, Bifeng (2, 5); Guo, Yan (2, 6)
Author affiliation: (1) Key Laboratory for Geographical Process Analysis and Simulation of Hubei Province, Central China Normal University, Wuhan; 430079, China; (2) Key Laboratory of Huang - Huai - Hai Smart Agricultural Technology, Ministry of Agriculture and Rural Affairs, Zhengzhou; 450002, China; (3) Agricultural Development Service Center of Changyang Tufa Autonomous County, Yichang; 443500, China; (4) Agriculture and Rural Affairs Bureau of Laifeng County, Enshi; 445700, China; (5) School of Public Administration, Jiangxi University of Finance and Economics, Nanchang; 330013, China; (6) Institute of Agricultural Information and Technology, Henan Academy of Agricultural Sciences, Zhengzhou; 450002, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 451-457
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Sampling, analyzing, and assessing soil heavy metal pollution requires significant manpower and resources. Access to easily obtainable environmental covariate information is crucial for enhancing the efficiency of soil heavy metal pollution monitoring. The spectra from proximal soil sensing are a comprehensive response of soil properties, and they have great potential to reveal heavy metal concentrations in soil. Near-infrared spectral characteristics of heavy metals in the surface soil of 109 samples were analyzed, and spectral information closely linked to soil Ni was extracted. This data was then utilized as auxiliary information to develop a co-Kriging model. Subsequently, co-Kriging models were constructed by using soil mechanical composition, and its combination with spectral information as auxiliary variables to compare the accuracy of spatial prediction mapping of Ni concentrations in the soil. The results indicated that the model incorporating silt concentrations in addition to the absorbance at 2 380 nm as auxiliary variables outperformed the model by using only silt concentrations. The cross-validated coefficient of determination Rcv was increased from 0. 49 to 0. 68 , while the cross-validated root mean squared error (RMSECV) was decreased from 11. 3 mg/kg to 9. 5 mg/kg. These findings suggested that NIR spectra, as readily accessible auxiliary information, can be used with soil mechanical composition to develop spatial prediction models and further enhance the precision of regional soil heavy metal surveys. The research result can offer a cost-effective solution for the spatial prediction of heavy metals in soil. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 35
Main heading: Kriging
Controlled terms: Atomic emission spectroscopy? - ?Bioremediation? - ?Heavy metals? - ?Mapping? - ?Near infrared spectroscopy? - ?Nickel? - ?Soil surveys
Uncontrolled terms: Auxiliary variables? - ?Co-Kriging? - ?Covariates? - ?Heavy metals pollution? - ?Near Infrared? - ?Near-infrared? - ?Proximal sensing? - ?Soil heavy metals? - ?Soil spectrum? - ?Spectra’s
Classification code: 201.1 Metallurgy and Metallography? - ?202.8.1 Nickel? - ?405.3 Surveying? - ?483.1 Soils and Soil Mechanics? - ?1201.9 Numerical Methods? - ?1301.1.3.1 Spectroscopy? - ?1502.1 Environmental Impact and Protection? - ?1502.4 Biodiversity Conservation
Numerical data indexing: Mass 3.00E-06kg, Mass 5.00E-06kg, Size 3.80E-07m
DOI: 10.6041/j.issn.1000-1298.2025.03.044
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
16. Phenotypic Measurement of Shiitake Mushroom Sticks Based on PP liteseg and Jetson Orin Nano
Accession number: 20251418174164
Title of translation: 基于PP-liteseg和Jetson Orin Nano的香菇菌棒表型測量方法
Authors: Liang, Xiuying (1); Liu, Huan (1); Mi, Panpan (2); Bian, Yinbing (2); Yang, Wanneng (2, 3)
Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) College of Plant Science and Technology, Huazhong Agricultural University, Wuhan; 430700, China; (3) State Key Laboratory of Crop Cenetic Improvement, Huazhong Agricultural University, Wuhan; 430070, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 140-147 and 179
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problems of difficulty in examining phenotypic traits and time-consuming and laborious manual measurements during shiitake mushroom breeding, a phenotypic measurement method for shiitake mushroom sticks applicable to the deployment of the Jetson Orin Nano platform was proposed. Image acquisition of shiitake mushroom sticks from three different data sources was performed by using cell phones and industrial cameras, and the shiitake mushroom colony dataset was labeled and enhanced; the segmentation effects of five segmentation models, namely, Bisenet, Stdcseg, U -net, Deeplabv3p, and PP - liteseg, were compared on the Test - A , Test - B , and Test - C test sets, and the results showed that PP - liteseg was the most suitable segmentation model for the test set of shiitake mushroom. The results showed that PP - liteseg was more pervasive than other networks, the mloU of PP - liteseg segmentation models on the three test sets was more than 97. 53% , the mPA was higher than 99. 49% , and the inference of a single image took 660 ms. To further balance the accuracy and real-time performance of the model, the PP - liteseg model was compressed by quantized distillation and deployed on the Jetson Orin Nano platform, and the mloU and mPA of the compressed model on the Test - B test set were 97. 50% and 99. 51% , respectively, and the inference of a single image took 43. 63 ms, which was nearly 64% shorter than that of the pre-compression model; the images of shiitake mushroom sticks were segmented by using the PP - liteseg, and the phenotypes of colonies were extracted, and then the mycelial growth length was obtained based on the radial length and axial width of the colony, and the average absolute percentage error, root mean square error and coefficient of determination of the mycelial growth length were 1. 874% , 0. 148 cm and 0. 918, respectively, compared with the manually measured values; the mycelial growth length of six strains were measured by the method in four consecutive days, and the results showed that the mycelial growth rate of six strains, both in a a single day or during the whole culture period, with the greatest difference between strains 49 and 168. The study demonstrated that the method was suitable for the phenotypic measurement of shiitake mushroom mycelium and can be run on the Jetson Orin Nano platform with good accuracy and real-time performance. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 31
Main heading: Mean square error
Controlled terms: Compression testing? - ?Medical imaging? - ?Mycelium? - ?Pixels? - ?Potassium hydroxide
Uncontrolled terms: Jetson orin nano? - ?Model lightweight? - ?Mycelial growth? - ?Mycelial growth length? - ?Phenotype? - ?PP - liteseg? - ?Segmentation models? - ?Shiitake mushroom stick? - ?Shiitake mushrooms? - ?Test sets
Classification code: 101.1 Biomedical Engineering? - ?103.1 Microbiology? - ?203 Biomaterials? - ?215.1.2 Mechanical Properties Testing Methods? - ?217.5.4 Other Structural Materials? - ?746 Imaging Techniques? - ?804.2 Inorganic Compounds? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision? - ?1202.2 Mathematical Statistics
Numerical data indexing: Percentage 4.90E+01%, Percentage 5.00E+01%, Percentage 5.10E+01%, Percentage 5.30E+01%, Percentage 6.40E+01%, Percentage 8.74E+02%, Size 1.48E+00m, Time 6.30E-02s, Time 6.60E-01s
DOI: 10.6041/j.issn.1000-1298.2025.03.014
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
17. Adaptive Path Tracking Predictive Control Method for Agricultural Machinery Based on Strategy-based Multi-objective Optimization
Accession number: 20251418174120
Title of translation: 基于多目標(biāo)優(yōu)化的策略型自適應(yīng)農(nóng)機(jī)路徑跟蹤控制方法
Authors: Liu, Huanyu (1); Tang, Jiacheng (1); Zou, Shun (1); Zhang, Lihan (1); Yu, Hao (1); Wang, Shuang (1)
Author affiliation: (1) Institute of Modern Agricultural Equipment, Xihua University, Chengdu; 610039, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 198-207
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to enhance the path tracking capability of agricultural machinery in complex environments, an adaptive predictive control method was proposed based on multi-objective optimization. The goal was to reduce external disturbances and improve path smoothness. Firstly, a kinematic model and error model of the machinery were developed, and its dynamic behavior under working conditions was analyzed. The arctic parrot algorithm was introduced, with a comprehensive error objective function designed for path tracking. By combining real-time feedback, AP adjusted model predictive control (MPC) parameters for better accuracy. Next, a multi-objective optimization algorithm was integrated with the MPC cost function to improve tracking accuracy, smoothness, and stability. To address delays caused by increased controller dimensionality, Latin hypercube sampling was used for efficient population initialization, reducing computational load. An early stopping mechanism and fitness memory were applied to accelerate the optimization process by halting iterations once a fitness threshold reached. Additionally, a warm start technique based on historical data was introduced to shorten optimization time, enabling faster application to new tasks. Simulation results at 1. 0 m/s showed a lateral maximum absolute error of only 0. 06 m, with an average error of 0. 02 m, while running time remained comparable to traditional MPC algorithms. Path smoothness was improved by 83%, indicating enhanced stability. In field tests, the algorithm outperformed traditional MPC with error reductions of 33% , 35% , and 38% at speeds of 0. 5 m/ s, 1. 0 m/s, and 1. 5 m/s, respectively. Path smoothness was increased by 40% , 51% , and 10% . These results validated the effectiveness of this method in practical applications, ensuring stable performance across complex scenarios and reducing path deviations due to external factors. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 27
Main heading: Multiobjective optimization
Controlled terms: Adaptive control systems? - ?Agricultural robots
Uncontrolled terms: Agricultural machinery path tracking? - ?Arctic puffin algorithm? - ?Hot start technology? - ?Model-predictive control? - ?Multi-objectives optimization? - ?Optimisations? - ?Path tracking? - ?Predictive control methods? - ?Tracking capability? - ?Traditional models
Classification code: 731.1 Control Systems? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?1201.7 Optimization Techniques
Numerical data indexing: Percentage 1.00E+01%, Percentage 3.30E+01%, Percentage 3.50E+01%, Percentage 3.80E+01%, Percentage 4.00E+01%, Percentage 5.10E+01%, Percentage 8.30E+01%, Size 2.00E+00m, Size 6.00E+00m, Velocity 0.00E00m/s, Velocity 5.00E+00m/s
DOI: 10.6041/j.issn.1000-1298.2025.03.020
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
18. Method of Counting Rice Grains in Ears Based on Deformable Convolution
Accession number: 20251418174167
Title of translation: 基于可變形卷積的稻粒在穗計(jì)數(shù)方法
Authors: Liu, Zeyu (1); Zhou, Yuncheng (1); Liang, Chengwei (2); Li, Ruiyang (1); Zhang, Yu (1)
Author affiliation: (1) College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang; 110866, China; (2) Rice Research Institute, Shenyang Agricultural University, Shenyang; 110866, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 363-373
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Rapid acquisition of grain number in rice spike is important for screening high-yielding and high-quality varieties. Aiming to address the problems that threshing counting destroyed the topology of the rice spike and cannot be used for the measurement of other phenotypic parameters, a method for counting rice grains in the spike was proposed. Considering the in-situ counting of rice grains as a density prediction problem, based on deformable convolution, a backbone network for feature extraction of rice spike images was designed. With a small number of selected paradigms for feature correlation of rice grains and spike images, feature correlation maps were generated through feature correlation layers, and based on the feature correlation maps, the image features were reused and cascaded to predict the distribution of density of the rice grains, which was then summed up to obtain the counting results through the density maps. The test results showed that the method had high counting accuracy. The mean absolute error (MAE) , root mean square error (RMSE) , and mean relative error (MRE) of rice grain counts of the test samples were 4.71, 6.92, and 2.9%. respectively, with MRE being only 0.7 percentage points higher than that of the manual walk-through, and MRE reduction of 9. 9, 8. 6 and 11.6 percentage points compared with that of existing benchmark methods FamNet, CSRNet and ICACount. Rice spike image feature extraction network designed with deformable convolution can effectively improve the accuracy of rice grain counting. With a close number of parameters, the model based on this network was 19. 3% and 12. 9% lower than that of ResNet - 50 in MAE and RMSE, and the model had a good fit with coefficient of determination R of 0. 940 5. Deformable convolution reduced 28. 9% and 22. 0% of rice grain count MAE and RMSE, and 1. 6 percentage points of MRE than conventional convolution for the same network architecture. Image feature reuse played an important role in improving the accuracy of rice grain counting, and this treatment decreased the MAE and RMSE of the model on the test set by 27. 6% and 22. 1% , and the MRE by 2. 2 percentage points. The processing time of single rice spike image of this method was 0. 92 s, which effectively improved the work efficiency, and the research can provide technical reference for rice spike phenotype detection and platform design. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 33
Main heading: Mean square error
Controlled terms: Analog storage? - ?Benchmarking? - ?Conformal mapping? - ?Directed graphs? - ?Grain (agricultural product)? - ?Image correlation? - ?Image denoising? - ?Image enhancement? - ?Photointerpretation? - ?Photomapping
Uncontrolled terms: Deformable convolution? - ?Feature correlation? - ?Grain numbers? - ?Mean absolute error? - ?Mean relative error? - ?Percentage points? - ?Rice? - ?Rice grains? - ?Rice spike phenotype? - ?Root mean square errors
Classification code: 405.3 Surveying? - ?716.1 Information Theory and Signal Processing? - ?742.1 Photography? - ?821.5 Agricultural Products? - ?913.3 Quality Assurance and Control? - ?1103.1 Data Storage, Equipment and Techniques? - ?1106.3.1 Image Processing? - ?1201.2 Calculus and Analysis? - ?1201.8 Discrete Mathematics and Combinatorics, Includes Graph Theory, Set Theory? - ?1201.14 Geometry and Topology? - ?1202.2 Mathematical Statistics
Numerical data indexing: Percentage 0.00E00%, Percentage 1.00E00%, Percentage 2.90E+00%, Percentage 3.00E+00%, Percentage 6.00E+00%, Percentage 9.00E+00%, Size -1.27E+00m, Time 9.20E+01s
DOI: 10.6041/j.issn.1000-1298.2025.03.036
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
19. Design and Experiment of Robot Chassis for Information Acquisition with Variable Wheelbase Omnidirectional Movement
Accession number: 20251418174191
Title of translation: 可變輪軸距全向移動(dòng)大田作物表型信息獲取機(jī)器人底盤設(shè)計(jì)與試驗(yàn)
Authors: Lu, Kunlei (1, 2); Han, Zhenhao (1, 2); Zhu, Licheng (1, 2); Feng, Xuguang (1, 2); Chen, Xi (3); Wang, Ruixue (1, 2)
Author affiliation: (1) Chinese Academy of Agricultural Mechanization Sciences Croup Co., Ltd., Beijing; 100083, China; (2) State Key Laboratory of Agricultural Equipment Technology, Beijing; 100083, China; (3) China Agricultural Mechanization Association, Beijing; 100122, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 27-38
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to further improve the versatility, mobility, and field performance of the phenotypic information acquisition robot chassis, a mobile variable-track chassis was designed based on the actual needs of field crop phenotypic information acquisition in China. Firstly, the overall structure, working principle, and technical parameters of the chassis were established according to the agronomic requirements for field crop planting and driving terrain conditions. Next, the design of key components, such as the chassis drive system, power system, and shock absorption suspension, was carried out, along with component selection and parameter verification. A chassis variable-track walking control system was developed, determining the control logic for track adjustment and walking transformation. Finally, a prototype was built to conduct performance tests. The results showed that the chassis exhibited excellent straight-line driving performance, with an average deviation rate of less than 0. 60% on hard surfaces and less than 1.26% on field surfaces. It demonstrated good steering maneuverability, with a single-turn offset less than 3. 52 mm for in-place turning on hard surfaces, an Ackermann steering turning radius less than 1. 76 m, and a single-turn offset less than 5. 18 mm for in-place turning on field surfaces, along with an Ackermann steering turning radius less than 1. 77 m. The variable track width accuracy was also commendable, with maximum track error less than 0. 01 m, making it adaptable to crops with different row spacings. The chassis showed good passability, capable of overcoming 120 mm vertical obstacles, thus meeting the requirements for navigating complex terrain like field ridges and headlands. Overall, the machine’s performance met the requirements for field terrain management operations, providing a comprehensive application platform and technical support for effective field management in wheat, corn, and open-field vegetable cultivation. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 27
Main heading: Maneuverability
Controlled terms: Agricultural robots? - ?Automobile suspensions? - ?Fertilizers? - ?Shock absorbers
Uncontrolled terms: Ackermann steering? - ?Field crops? - ?Hard surface? - ?Independent drive steering? - ?Information acquisitions? - ?Omni-directional mobiles? - ?Omnidirectional mobile chassi? - ?Phenotypic information acquisition? - ?Robot chassis? - ?Variable wheelbase
Classification code: 662.3 Automobile Components and Materials? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.3 Agricultural Chemicals? - ?1401.2 Hydraulic Equipment and Machinery? - ?1502.1.1.3 Soil Pollution
Numerical data indexing: Percentage 1.26E+00%, Percentage 6.00E+01%, Size 1.00E00m, Size 1.20E-01m, Size 1.80E-02m, Size 5.20E-02m, Size 7.60E+01m, Size 7.70E+01m
DOI: 10.6041/j.issn.1000-1298.2025.03.003
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
20. Design and Testing of Air-blown Low-loss Seed Recovery Nozzles for Oilseed Rape Combine Harvester Cutting Decks
Accession number: 20251418174176
Title of translation: 油菜聯(lián)合收獲機(jī)割臺(tái)氣吹式籽粒低損回收噴嘴設(shè)計(jì)與試驗(yàn)
Authors: Luo, Haifeng (1, 2); Jin, Yuguo (1); Tong, Xuequan (1); Wu, Mingliang (1, 2); Song, Xi (1); Jiang, Xiaohu (1, 2)
Author affiliation: (1) College of Engineering, Hunan Agricultural University, Changsha; 410128, China; (2) Hunan Key Laboratory of Intelligent Agricultural Machinery and Equipment, 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: 3
Issue date: March 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 at the problems such as big loss of grain dropped from the cutting table due to the mechanical collision of angular fruit frying pods in the process of oilseed rape combine harvesting, a low-loss recovery device of air blowing grain from the cutting table was designed, and the key components of the pneumatic nozzle were also designed. In order to ensure reasonable airflow distribution and recovery effect, the nozzle structure shape was designed by adopting the duckbill structure, and the supporting design of the harvesting device was made to realize the smooth operation of low-loss harvesting on the cutting table. Based on Fluent, the internal flow field of the nozzle was simulated, and the two-factor full factorial simulation test was carried out with the nozzle opening angle and nozzle opening width as the test factors, and with the airflow exit velocity, airflow width and airflow intersection distance as the evaluation indexes. The test results showed that when the nozzle opening angle was 35°, the nozzle opening size was 3 mm, the exit velocity was 138 m/s, the airflow width was 1 926 mm, and the airflow intersection distance was 64 mm, the wind screen coverage effect was the best; the bench test was carried out with the nozzle angle, transverse distance, and kernel drop height as the test factors, and the recycling volume as the evaluation index, and the optimal combinations of the nozzle arrangement parameters in the cutting table were as follows; nozzle angle was 19. 6° , lateral distance was 387 mm; field test results showed that the oilseed rape cutting table loss rate was 2. 48% , compared with the traditional harvesting operations, it was down by 35. 5% ~50. 4% , effectively reducing the cutting table loss, to meet the oilseed rape low-loss harvesting operation requirements. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 31
Main heading: Combines
Controlled terms: Grain (agricultural product)? - ?Harvesters? - ?Nozzle design? - ?Oilseeds? - ?Pneumatics
Uncontrolled terms: Combine harvesters? - ?Cutting deck? - ?Cutting tables? - ?Evaluation index? - ?Exit velocity? - ?Low-loss? - ?Oil seed rape? - ?Opening angle? - ?Pneumatic recovery? - ?Rape combine
Classification code: 301.1 Fluid Flow? - ?408 Structural Design? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?904 Design? - ?1401.3 Pneumatics, Equipment and Machinery
Numerical data indexing: Percentage 4.00E+00%, Percentage 4.80E+01%, Percentage 5.00E+00%, Size 3.00E-03m, Size 3.87E-01m, Size 6.40E-02m, Size 9.26E-01m, Velocity 1.38E+02m/s
DOI: 10.6041/j.issn.1000-1298.2025.03.027
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
21. Design and Experiment of Precision Seed Metering Device for Rice Bud Seed with Protruding Disturbing Species
Accession number: 20251418174163
Title of translation: 外凸擾種仿形型孔氣吸式水稻芽種精量排種器設(shè)計(jì)與試驗(yàn)
Authors: Luo, Haifeng (1, 2); Liu, Guanghui (1); Wu, Mingliang (1, 2); Zhang, He (1); Wang, Chengwei (1); Jiang, Xiaohu (1, 2)
Author affiliation: (1) College of Engineering, Hunan Agricultural University, Changsha; 410128, China; (2) Hunan Provincial Engineering Technology Research Center of Modern Agricultural Equipment, 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 227-239
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problems such as population accumulation and high water content of rice seed which are not easy to be adsorbed during seeding process, a kind of air-suction rice seed precision discharge device with convex and disturbed seed copying hole was designed. According to the mechanical and physical characteristics of Yliangyou No. 1 hybrid rice, which is widely used in South China, the structure and geometric parameters of the profile-shaped hole were designed rationally. The dynamic and kinematic analysis of filling and seeding process was carried out, and the range of working speed and working negative pressure was obtained. Based on the fluid-structure coupling theory of CFD - DEM, the adsorption force was taken as the test index, and the adsorption performance simulation tests of seven diameters were carried out. The suction hole diameter with the largest adsorption force was determined to be 1. 4 mm. At the same time, the average velocity of rice bud seed was taken as the evaluation index, and the simulation test of disturbed seed performance was carried out. Under the conditions of working speed 10 ~ 50 r/min, working negative pressure 1.2 kPa and suction hole diameter 1.4 mm, the disturbance ability of the seed plate with convex species copying hole was strong, which could effectively reduce the population accumulation phenomenon. Based on this suction hole, the working speed and working negative pressure were selected as test factors, and the qualification index X1 , replay index X2 and missing sowing index X3 were evaluated. The two-factor full factor bench tests were carried out. The test results showed that when the working speed was 25 r/min and the working negative pressure was 1. 24 kPa, the qualified index of the seed feeder was 92. 64% , the replay index was 2. 57% , and the missing sowing index was 4. 79% . The results showed that the average qualified index of each line was 92. 86% , the average reseeding index was 2. 72% , the average missing sowing index was 4. 42% , the average qualified rate of hole distance was 90. 57% , and the coefficient of consistency of discharge of each line was 3. 12% . The coefficient of variation of total displacement stability was 1. 89% , and all the evaluation indexes met the planting requirements of rice bud seed precision direct seeding, which provided a certain theoretical basis for rice bud seed seeding. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Seed
Controlled terms: Crystallizers? - ?Flow of gases? - ?Flow separation? - ?Water content
Uncontrolled terms: Air suction? - ?Air suction seed metering device? - ?CFD-DEM? - ?Convex and disturbing species of profiled hole? - ?Negative pressures? - ?Rice seed? - ?Rice sprout seed? - ?Seed-metering device? - ?Seeding process? - ?Working speed
Classification code: 301.1 Fluid Flow? - ?301.1.2 Gas Dynamics? - ?802.1 Chemical Plants and Equipment? - ?821.5 Agricultural Products? - ?941.6 Moisture Measurements
Numerical data indexing: Pressure 2.40E+04Pa, Size 1.40E-03m, Size 4.00E-03m, Angular velocity 1.67E-01rad/s to 8.35E-01rad/s, Angular velocity 4.175E-01rad/s, Percentage 1.20E+01%, Percentage 4.20E+01%, Percentage 5.70E+01%, Percentage 6.40E+01%, Percentage 7.20E+01%, Percentage 7.90E+01%, Percentage 8.60E+01%, Percentage 8.90E+01%, Pressure 1.20E+03Pa
DOI: 10.6041/j.issn.1000-1298.2025.03.023
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
22. Meta-analysis on Effects of Straw Returning on Greenhouse Gas Emissions from Wheat Fields
Accession number: 20251418174186
Title of translation: 秸稈還田對(duì)麥田土壤溫室氣體排放影響的Meta分析
Authors: Ma, Penghui (1, 2); Zhang, Huimin (1); Jing, Ming (1); Song, Changji (1); Yang, Zhiwen (1, 3); Chen, Weiwei (1); Liang, Bingjie (1, 2); Hu, Yajin (3, 4)
Author affiliation: (1) Yellow River Institute of Hydraulic Research, Yellow River Conservancy Commission, Zhengzhou; 450003, China; (2) Henan Engineering Research Center of Rural Water Environment Improvement, Zhengzhou; 450003, China; (3) Henan Key Laboratory of Ecological Environment Protection and Restoration of the Yellow River Basin, Zhengzhou; 450003, China; (4) College of Resources and Environment, Henan Agricultural University, Zhengzhou; 450046, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 425-436
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to systematically analyze the effects of straw returning on greenhouse gas emissions from wheat farmland under different climatic conditions, soil properties and field management measures, field trial data from published papers were integrated through literature retrieval and Meta-analysis method was used to quantitatively study the effect of straw returning on greenhouse gas emissions from wheat farmland under various production conditions. Simultaneously, the relative importance of various influencing factors on greenhouse gas emissions was evaluated. The results indicated that compared with no straw returning, straw returning significantly increased soil N2O emission by 15. 50% , CO2 emission by 10. 68% , and CH4 absorption was increased by 26. 45% (P 2O and CO2 emissions, and the largest increase in CH4 absorption, with effect values of 5.02% , 9.88% and 381. 63% , respectively. When the annual average temperature was no more than 10°C , straw returning resulted in the smallest increase in soil CO2 emissions, and when the annual average temperature was higher than 15 °C , straw returning resulted in the smallest increase in soil N2O emissions and the largest increase in CH4 absorption. Under straw returning, soil N2O emission effect values were decreased as soil organic carbon content was increased, while CH4 absorption effect values were increased with the increase of organic carbon content. Under straw returning, the N2O emission effect was decreased with the increase of nitrogen application rates, while the CO2 emission effect was firstly increased and then decreased with the increase of nitrogen application rates. Under no-tillage conditions, straw returning significantly reduced soil CO2 emissions by 10.81% (P 4 absorption by 91. 00% (P 4 absorption by 202. 04% (P2O emissions by 11. 33% and significantly increased CH4 absorption by 121.64% ( P ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 67
Main heading: Greenhouse gas emissions
Controlled terms: Fertilizers? - ?Low emission? - ?Straw? - ?Surface discharges
Uncontrolled terms: Annual precipitation? - ?CH 4? - ?CO 2 emission? - ?Condition? - ?Emission effects? - ?Greenhouse gas emissions? - ?Meta-analysis? - ?Nitrogen application rates? - ?Straw returning? - ?Wheat fields
Classification code: 701.1 Electricity: Basic Concepts and Phenomena? - ?821.3 Agricultural Chemicals? - ?821.6 Agricultural Wastes? - ?1502.1.1.3 Soil Pollution? - ?1502.1.2 Climate Change
Numerical data indexing: Percentage 0.00E00%, Percentage 1.081E+01%, Percentage 1.2164E+02%, Percentage 3.30E+01%, Percentage 4.00E+00%, Percentage 4.50E+01%, Percentage 5.00E+01%, Percentage 5.02E+00%, Percentage 6.30E+01%, Percentage 6.80E+01%, Percentage 9.88E+00%, Size 0.00E00m, Temperature 2.83E+02K, Temperature 2.88E+02K
DOI: 10.6041/j.issn.1000-1298.2025.03.042
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
23. Extraction Method of Phenotypic Parameters of Agaricus bisporus Based on YOLO v8 - ABSeg
Accession number: 20251418167631
Title of translation: 基于YOLO v8 - ABSeg的雙孢蘑菇表型參數(shù)提取方法
Authors: Miao, Quanlong (1); Zhou, Yang (1); Li, Jiantao (2); Zhou, Yansuo (3, 4); Li, Yu (3)
Author affiliation: (1) School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou; 310023, China; (2) West Lake University (Hangzhou) Development Co.Ltd., Hangzhou; 310024, China; (3) Zhejiang Institute of Modern Agricultural Equipment Design and Research, Hangzhou; 310003, China; (4) Zhejiang Institute of Industry and Information Technology, Hangzhou; 310003, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 158-168
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to overcome the problem of low efficiency and high cost in the manual acquisition of phenotypic parameters of Agaricus bisporus, an instance segmentation-based method for calculating phenotypic parameters for modern industrial environments was proposed. Firstly, the YOLO v8n - Seg instance segmentation model was improved through the introduction of faster neural network (FasterNet) , including the employment of partial convolutions (PConv) to reduce redundant computations and memory accesses. The squeeze-and-excitation (SE) attention mechanism was incorporated into the feature fusion network to enhance the model’s focus on the critical target components, minimizing interference from irrelevant background. The improved model successfully performed instance segmentation on Agaricus bisporus. Based on the segmentation results, four phenotypic parameters of the mushroom sub-entities were figured out; cap diameter, cap roundness, cap whiteness, and the color spots on the surface. Experimental results demonstrated that the YOLO v8 - ABSeg model achieved a 1. 6 percentage points improvement in mask accuracy on proposed custom-built Agaricus bisporus dataset, with reductions of 38. 7% , 25. 0% , and 36. 8% in the number of parameters, floating-point operations, and weight file size, respectively,frames per second was increased by 11.3%. Additionally, the calculated phenotypic parameters exhibited a measurement error of no more than 10% when compared with manual measurement results. This method provided a foundation for the automation of phenotypic parameter extraction and can be applied to other applications like the development of growth models and real-time environmental control systems, and soon. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 31
Main heading: Environmental management
Controlled terms: Image segmentation
Uncontrolled terms: Agaricus bisporus? - ?Attention mechanisms? - ?Extraction method? - ?High costs? - ?Industrial environments? - ?Instance segmentation? - ?Lightweight? - ?Parameters extraction? - ?Phenotype parameter extraction? - ?YOLO v8
Classification code: 1106.3.1 Image Processing? - ?1501.1 Sustainable Development? - ?1502.1 Environmental Impact and Protection
Numerical data indexing: Percentage 0.00E00%, Percentage 1.00E+01%, Percentage 1.13E+01%, Percentage 7.00E+00%, Percentage 8.00E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.016
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
24. Multi-objective Apple Picking Path Planning Method Based on Target Guidance
Accession number: 20251418174168
Title of translation: 基于目標(biāo)引導(dǎo)的多目標(biāo)蘋果采摘路徑規(guī)劃方法
Authors: Niu, Jinxing (1); Wang, Shuo (1); Zhao, Junlong (1); Liu, Zhengyi (1); Yu, Qingyuan (1)
Author affiliation: (1) School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou; 450011, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 208-215 and 226
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the issues of low planning efficiency and long planning paths of apple-picking robotic arms in unstructured orchard environments, a target-guided multi-objective apple-picking path planning method ( BD - PS0_TG - RRT ) was proposed, which combined a particle swarm optimization ( PSO) algorithm incorporating a branch density parameter with a target-guided rapidly-exploring random tree star ( TG - RRT ) path planning algorithm. Firstly, based on the traditional RRT algorithm, an adaptive step-size strategy was introduced, and an equilateral conical sampling region was defined. A target-biasing strategy was also incorporated to enhance the goal-directedness of sampling within this region. A direct connection strategy was used for new nodes to enable faster convergence, thereby improving the speed of path generation. Secondly, the initial planned path was refined by removing redundant points and transforming it into a smooth path using cubic B-spline curves, improving path quality. Lastly, to account for obstacles such as branches during the picking process, a branch density parameter was introduced into the PSO algorithm to obtain the optimal solution for the multi-objective picking sequence. Experimental results for path planning showed that compared with the RRT and RRT algorithms, the TG - RRT algorithm reduced average path length by 23. 18% and 11.67% , respectively, decreased average time by 12.59% and 71.96% , and lowered the average number of iterations by 68. 07% and 31. 58% . In multi-objective picking experiments, the BD - PS0_ TG - RRT algorithm with the branch density parameter reduced average planning time by 8. 14% and average iterations by 13. 24% compared with the original PSO combined with TG - RRT algorithm. These experimental results demonstrated that the BD - PSO_TG - RRT algorithm accurately generated an optimal path for multi-objective apple picking, shortened the path length, reduced planning time, and significantly improved the efficiency of multi-objective apple-picking path planning. This algorithm can provide technical reference for apple picking robots to perform multi-objective continuous picking tasks. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Robotic arms
Controlled terms: Adaptive algorithms? - ?Agricultural robots? - ?Decision trees? - ?Interpolation? - ?Motion planning? - ?Multiobjective optimization? - ?Orchards? - ?Particle swarm optimization (PSO)? - ?Random forests? - ?Robot programming
Uncontrolled terms: Apple harvesting? - ?Density parameters? - ?Multi objective? - ?Particle swarm optimization algorithm? - ?Path planning method? - ?Planning paths? - ?Planning time? - ?Rapidly-exploring random trees? - ?RRT algorithm? - ?Target guidance
Classification code: 101.6.1 Robotic Assistants? - ?731.5 Robotics? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?961 Systems Science? - ?1101 Artificial Intelligence? - ?1101.2 Machine Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1106.1 Computer Programming? - ?1201.5 Computational Mathematics? - ?1201.7 Optimization Techniques? - ?1201.8 Discrete Mathematics and Combinatorics, Includes Graph Theory, Set Theory? - ?1201.9 Numerical Methods
Numerical data indexing: Percentage 1.167E+01%, Percentage 1.259E+01%, Percentage 1.40E+01%, Percentage 1.80E+01%, Percentage 2.40E+01%, Percentage 5.80E+01%, Percentage 7.00E+00%, Percentage 7.196E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.021
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
25. Handheld Structured Light Scanning System Design and Maize Leaf Area Extraction
Accession number: 20251418174171
Title of translation: 手持式結(jié)構(gòu)光掃描系統(tǒng)設(shè)計(jì)與玉米葉面積提取
Authors: Peng, Xingshuo (1); Yang, Yue (1); Zhang, Yongliang (1); Guo, Ronggeng (1); Geng, Nan (1)
Author affiliation: (1) College of Information Engineering, Northwest a and 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 111-118 and 128
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The method of leaf area extraction based on 3D point clouds offers advantages such as non-contact, high efficiency, and high precision, making it well-suited to meet the demands of modern agriculture for rapid acquisition and accurate assessment of leaf area. Focusing on summer maize during its full growth period in field conditions, with four different fertilization treatments, each containing two sample plots, a self-developed handheld structured light crop 3 D scanner was used, point cloud data were collected throughout the entire growth period of summer maize, and a series of point cloud preprocessing processes, including point cloud registration, denoising, and downsampling, were proposed. Subsequently, the PCT deep learning point cloud segmentation network was applied to accurately segment the crop organ point clouds, extracting the maize leaf point cloud data and successfully calculating the leaf area. The segmentation results showed that the PCT network performed excellently in the point cloud segmentation accuracy for maize organs, with the precision , recall, Fl -score, and IoU metrics for the leaf point cloud all exceeding 95% , and the segmentation metrics for other organs also being above 75% . Significant differences were observed in the leaf area extraction results across different growth stages. During the seedling, jointing, and full growth stages, the extraction results were excellent, with R values of 0. 906 2 , 0. 983 8 , and 0. 994 9 , and RMSE values of 221. 34 cm2 , 172. 77 cm2 , and 206. 64 cm2 , respectively. However, in the mature stage, the model’s performance significantly was decreased, with an /T of 0.517 8 and an RMSE of 209. 32 cm . Under different fertilization levels, the leaf area extraction results were consistently good, with R values above 0.98. As the fertilization amount changed, the RMSE showed a trend of first decreasing and then increasing, with specific values of 176.38 cm , 106. 36 cm , 110. 18 cm , and 270. 34 cm . In conclusion, the method proposed can accurately and effectively extract the leaf area of individual maize plants in field conditions, providing reliable data support for precision agriculture. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Fertilizers
Controlled terms: Cloud seeding? - ?Grain (agricultural product)
Uncontrolled terms: 3 D point cloud? - ?Growth period? - ?Handheld structured light scanning system? - ?Handhelds? - ?Leaf area? - ?Point cloud segmentation? - ?Point-clouds? - ?Scanning systems? - ?Structured light scanning? - ?Summer maize
Classification code: 443.3 Precipitation? - ?821.3 Agricultural Chemicals? - ?821.5 Agricultural Products? - ?1502.1.1.3 Soil Pollution
Numerical data indexing: Percentage 7.50E+01%, Percentage 9.50E+01%, Size 1.7638E+00m, Size 1.80E-01m, Size 3.20E-01m, Size 3.40E-01m, Size 3.60E-01m, Size 6.40E-01m, Size 7.70E-01m
DOI: 10.6041/j.issn.1000-1298.2025.03.011
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
26. Wheat Leaf Area Index Estimation Based on Fusion of UAV Multispectral Information and Texture Features
Accession number: 20251418174148
Title of translation: 基于無人機(jī)多光譜信息與紋理特征融合的小麥葉面積指數(shù)估測
Authors: Qi, Hao (1); Sun, Haifang (1); Lü, Liangjie (2); Li, Si (1); Min, Jia’nan (1); Hou, Liang (1)
Author affiliation: (1) Institute of Agricultural Information and Economics, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang; 050051, China; (2) Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang; 050035, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 334-344
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Leaf area index ( LAI) is one of the important indicators for crop growth monitoring and yield prediction. In order to explore the potential of wheat LAI estimation models based on UAV multispectral technology, taking wheat breeding materials as the research object, the multispectral images were obtained based on the UAV platform at jointing, booting, heading and flowering stages of wheat, and further calculated 12 vegetation indices (VI) and eight types of texture features (TF) in each band. Then, the Pearson correlation analysis method was employed to identify VI and TF which strongly correlated with LAI, and the recursive feature elimination method ( RFE ) was used to screen the comprehensive features (CF) on the bases of the preferred two types of features. Finally, based on the three types of features, three machine learning algorithms including multiple linear regression ( MLR) , support vector regression (SVR) and gradient boosting regression (GBR) were employed to establish LAI estimation models, and the estimation accuracy of the models was compared at different growth stages. The results showed that the CF effectively improved the accuracy of wheat LAI estimation models at each growth stages; among the three machine learning algorithms, GBR performed greater stability, and had better LAI fitting for the three types of features; specifically, the LAI estimation model based on GBR, using vegetation indices RVI, NDVI, and texture features NIR_COR, R _ MEA as input variables, performed best, with R1 of 0. 91 and RMSE of 0. 45 in the training set, R1 of 0. 84 and RMSE of 0. 67 in the testing set for all stages. The research result can provide an application reference for LAI estimation of wheat based on multispectral technology. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 46
Main heading: Support vector regression
Controlled terms: Adaptive boosting? - ?Multiple linear regression
Uncontrolled terms: Estimation models? - ?Gradient boosting? - ?Leaf Area Index? - ?Machine-learning? - ?Multi-spectral? - ?Texture features? - ?UAV multispectral? - ?Vegetation index? - ?Wheat? - ?Wheat leaves
Classification code: 1101.2 Machine Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1202 Statistical Methods
Numerical data indexing: Size 1.143E+00m, Size 1.7018E+00m
DOI: 10.6041/j.issn.1000-1298.2025.03.033
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
27. Improved YOLO v8n Network for Real-time Detection of Tomato Maturity
Accession number: 20251418174188
Title of translation: 基于改進(jìn)YOLO v8n網(wǎng)絡(luò)的番茄成熟度實(shí)時(shí)檢測算法
Authors: Ren, Jingqiu (1); Wan, Enhan (1); Shan, Mi (1); Zhang, Guanghua (1); Lu, Weidang (2)
Author affiliation: (1) School of Electrical and Information Engineering, Northeast Petroleum University, Daqing; 163318, China; (2) College of Information Engineering, Zhejiang University of Technology, Hangzhou; 310014, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 374-382 and 450
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: To address the numerous challenges faced in tomato harvesting, such as the aging of farmers, labor shortages, and rising labor costs, and resolve issues related to the low maturity detection accuracy and inaccurate instance segmentation of tomato harvesting robots in complex orchard environments, an improved YOLO v8 network-based real-time tomato maturity detection algorithm was proposed. Firstly, by introducing the channel embedded positional attention module and an improved large kernel convolutional block attention module into the YOLO v8n network, the algorithm can effectively retain the positional information of tomato targets in the shallow network layers and establish long-range dependencies between target regions, thereby significantly increasing the attention of the YOLO v8n network to critical tomato features. Then a series of comprehensive and rigorous comparative experiments were conducted on the LaboroTomato dataset, demonstrating that the improved YOLO v8n network achieved 0.4 percentage points, 1.4 percentage points, and 0.3 percentage points, 1.2 percentage points improvements in detection and segmentation mAP @ 50 and mAP @ 50 - 95 , respectively, compared with that of the original YOLO v8n network. Finally, the improved YOLO v8n network was lightweight deployed on the low-cost, low-computation, and low-power Jetson Nano platform, successfully reducing memory usage from overflow to 2. 4 GB and doubling the inference speed. The research result can provide robust technical support for the real-time and accurate detection of tomato maturity by tomato harvesting robots in complex scenarios, significantly enhancing the overall efficiency and effectiveness of automated tomato harvesting operations. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Fruits
Controlled terms: Agricultural robots? - ?Costs? - ?Harvesting? - ?Industrial robots? - ?Orchards? - ?Wages
Uncontrolled terms: Attention module? - ?Harvesting robot? - ?Jetson nano? - ?Lightweight? - ?Percentage points? - ?Real- time? - ?Real-time detection? - ?Targets detection? - ?Tomato maturity? - ?YOLO v8n
Classification code: 731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?911 Cost and Value Engineering; Industrial Economics? - ?912.3 Personnel
DOI: 10.6041/j.issn.1000-1298.2025.03.037
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
28. Characteristics of Spatial and Temporal Evolution of Water Footprint of Agricultural Production and Evaluation of Water Resources Carrying Capacity in Xingkai Lake Irrigation District
Accession number: 20251418174121
Title of translation: 興凱湖灌區(qū)農(nóng)業(yè)生產(chǎn)水足跡時(shí)空演變特征與水資源承載力評(píng)價(jià)
Authors: Song, Linlin (1); Wang, Hongshu (1); Xu, Yaowen (2)
Author affiliation: (1) College of Economics and Management, Northeast Forestry University, Harbin; 150036, China; (2) School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin; 150030, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 437-450
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: To reveal the water resource utilization and structure in the Sanjiang Plain region and achieve efficient use of regional water resources, theoretical models for calculating water footprints and indicators for evaluating water resource carrying capacity were introduced. The spatiotemporal evolution of crop production water footprints, dominant influencing factors, and internal driving mechanisms in the Xingkai Lake Irrigation District from 2001 to 2021 was quantified. The irrigation water demand for different types of crops within the planned year was also forecasted and the balance of crop production water footprints, dominant influencing factors, and internal driving mechanisms in the Xingkai Lake Irrigation District from 2001 to 2021 was evaluated. It also predicted the irrigation water demand for different types of crops within the planned year and evaluated the balance of crop production water demand and supply, as well as the status of water resource carrying capacity. The results indicated that the total water footprint and blue water footprint for crop production showed a gradually decreasing trend, while the green water footprint and gray water footprint exhibited a fluctuating trend. The total water footprint of corn remained unchanged , maintaining a relatively stable level, whereas the water footprint of rice , soybeans , and other crops continued to decrease. There were significant regional differences in the crop production water footprint in the Xingkai Lake Irrigation District. The eastern region, with relatively higher annual precipitation, had a lower blue water footprint for crop production, but relatively higher green and gray water footprints. Special attention needed to be paid to the water resource use in the western region. In the evaluation of water resource carrying capacity indicators, except for the Xingkai Lake Farm, which was critically overloaded, the results of the total water use evaluation, groundwater evaluation, and comprehensive evaluation for the remaining farms were overloaded or severely overloaded, indicating a serious water shortage situation, with the 856 Farm suffering the most severe water scarcity. Although the sustainable use of water resources in the Xingkai Lake Irrigation District improved in recent years, there were obvious spatiotemporal differences and uneven regional distribution. It was still necessary to continuously optimize the crop planting structure and improve the level of sustainable water resource use in conjunction with the regional resource endowment and industrial layout. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Lakes
Controlled terms: Crops? - ?Fertilizers? - ?Groundwater resources? - ?Irrigation? - ?Water management
Uncontrolled terms: Analyze of influencing factor? - ?Irrigation districts? - ?Supply and demand balances? - ?Water footprint? - ?Water footprint characteristic? - ?Water resource carrying capacity? - ?Water supply and demand balance? - ?Water supply and demands? - ?Waters resources? - ?Xingkai lake irrigation district
Classification code: 407 Maritime and Port Structures; Rivers and Other Waterways? - ?444 Water Resources? - ?444.1 Surface Water? - ?444.2 Groundwater? - ?821.3 Agricultural Chemicals? - ?821.4 Agricultural Methods? - ?821.5 Agricultural Products? - ?1502.1.1.3 Soil Pollution
DOI: 10.6041/j.issn.1000-1298.2025.03.043
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
29. Phenotyping Identification Method for Key Wheat Growth Stage Based on Phenotyping Robot
Accession number: 20251418174969
Title of translation: 基于表型機(jī)器人的小麥關(guān)鍵生育期表型檢測方法
Authors: Song, Xubin (1); Wang, Chunying (1, 2); Li, Ming (1); Zhao, Xingtian (1); Wang, Qinglong (1); Yang, Mingqing (1); Liu, Ping (1, 3)
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) State Key Laboratory of Wheat Improvement, Shandong Agricultural University, Taian; 271018, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 67-79
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the challenges of low automation and poor accuracy in traditional field wheat phenotyping data collection and analysis, a wheat phenotyping identification robot chassis was developed and a phenotypic detection method for key wheat growth stages was proposed based on a phenotyping robot. Initially, a TD - YOLO vl 1 seedling detection model was proposed to achieve automated and precise recognition of wheat seedling emergence in the field. The incorporation of the DCNv4 module into the feature extraction network enhanced its ability to capture contextual information, allowing for the extraction of feature representations with fewer network parameters, thereby reducing computational complexity and the number of parameters. Moreover, the introduction of a task dynamic alignment detection head further utilized information from intermediate layers, promoting consistency between classification and localization tasks, and improving the model’s classification and localization performance during seedling detection. Subsequently, a phenotyping identification system for wheat was constructed, integrating multi-sensor fusion and edge computing. This system integrated the seedling detection method with previously proposed phenotyping identification techniques for heading stage monitoring and flowering stage determination, enabling the efficient and automated collection and analysis of field phenotypic data. The results indicated that the proposed method had a high accuracy in wheat seedling emergence identification (R1 =0. 908 , RMSE = 11. 73 , rRMSE = 23. 04% ) . It also enabled dynamic monitoring of wheat heading and flowering stages, exhibiting excellent temporal feature capture capabilities. The system facilitated precise determination of wheat growth stages and accurate analysis of key phenotypic traits, including spike number, spikelet number, flower number, and seedling emergence. This method can be applied for high-throughput collection and efficient analysis of field wheat phenotypic data, providing effective and reliable technical support for field phenotype acquisition in wheat breeding. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 43
Main heading: Agricultural robots
Controlled terms: Edge detection? - ?Intelligent robots? - ?Seed
Uncontrolled terms: Analysis system? - ?Detection methods? - ?Growth stages? - ?Phenotypic identification? - ?Phenotyping? - ?Phenotyping robot? - ?Seedling emergence? - ?Wheat? - ?Wheat seedlings? - ?YOLO v11
Classification code: 101.6.1 Robotic Assistants? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment? - ?821.5 Agricultural Products? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision
Numerical data indexing: Percentage 4.00E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.007
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
30. Design and Experiment of Wheel-crawler Switching Chassis for Crop Phenotyping Information Perception Robot
Accession number: 20251418174166
Title of translation: 輪履切換式作物表型信息感知機(jī)器人底盤設(shè)計(jì)與試驗(yàn)
Authors: Su, Miao (1); Yun, Yaze (1); Yao, Xia (1); Zhu, Yan (1); Cao, Weixing (1); Zhou, Dong (1)
Author affiliation: (1) National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing; 210095, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 39-48
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the issues of crop damage, insufficient flexibility, and poor passability associated with chassis systems in field crop phenotyping information perception robots, a chassis was designed that integrated wheel-crawler switching and stepless wheelbase adjustment functionalities, taking into account the agronomic practices and growth characteristics of rice and wheat cultivation in China. The overall structure and operational principles of the chassis were elaborated, and three types of easily switchable locomotion devices, i. e. , a rigid impeller, inflatable rubber wheels, and triangular tracks were developed. Additionally, components for independent four-wheel drive and four-wheel steering, along with a device for precise stepless adjustment of wheelbase, were designed. The steering performance, stability, and passability of the robot chassis were theoretically analyzed, with results confirming that the performance met the design requirements. Finite element analysis was conducted on the chassis frame, demonstrating that both the strength and stiffness met the design specifications and that resonance induced by terrain excitation can be effectively mitigated. Field tests conducted on the prototype indicated that the robot chassis exhibited excellent driving performance, with maximum linear travel speeds of 1. 02 m/s, 0. 98 m/s, and 0. 73 m/s across the three configurations, while accelerations were recorded at 0. 3 m/s , 0. 33 m/s , and 0. 18 m/s , respectively. The average deviation rates during travel were 2. 35% , 1.18%, and 1. 89% , respectively. The minimum turning radii for the wheeled and triangular tracked configurations were 2 306 mm and 1 432 mm, respectively. The rigid impeller configuration achieved a longitudinal climbing angle of 30° and a lateral climbing angle of 28°. The robot successfully traversed vertical obstacles up to 350 mm in height and negotiated field ridges of 308 mm, thereby meeting the operational requirements for phenotyping information perception in large field scenarios. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 22
Main heading: Impellers
Controlled terms: Agricultural robots? - ?Four wheel steering? - ?Structural dynamics? - ?Wheels
Uncontrolled terms: Adjustable wheelbase? - ?Crop damages? - ?Independent drive and steering? - ?Information perception? - ?Passability? - ?Phenotyping? - ?Phenotyping robot? - ?Robot chassis? - ?Triangular track? - ?Wheeled chassi
Classification code: 408 Structural Design? - ?601.2 Machine Components? - ?609.2 Pumps? - ?662.3 Automobile Components and Materials? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment
Numerical data indexing: Percentage 1.18E+00%, Percentage 3.50E+01%, Percentage 8.90E+01%, Size 3.06E-01m, Size 3.08E-01m, Size 3.50E-01m, Size 4.32E-01m, Velocity 1.80E+01m/s, Velocity 2.00E+00m/s, Velocity 3.00E+00m/s, Velocity 3.30E+01m/s, Velocity 7.30E+01m/s, Velocity 9.80E+01m/s
DOI: 10.6041/j.issn.1000-1298.2025.03.004
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
31. Cucumber Leaf Segmentation and Phenotype Extraction Method Based on Three-dimensional Point Cloud
Accession number: 20251418174161
Title of translation: 基于三維點(diǎn)云的黃瓜葉片分割與表型參數(shù)提取方法
Authors: Wang, Jizhang (1, 2); Yao, Chengzhi (1); Zhou, Jing (1, 2); Huang, Zhigang (2); Chen, Yongming (2)
Author affiliation: (1) School of Agricultural Engineering, Jiangsu University, Zhenjiang; 212013, China; (2) Jiangsu Province Internet of Things Intelligent Horticultural Facilities Engineering Technology Research Center, Changshu; 215555, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 354-362
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Automatic acquisition of plant canopy phenotypic shape is essential for seed selection and scientific cultivation of cucumber varieties. Segmentation accuracy and efficiency are low due to the difficulty of current 3D point cloud processing techniques to perform effective separation of stems and leaves on cucumber plant point clouds. Aiming to address this problem, an improved algorithm for regional growth segmentation and phenotype extraction was proposed by segmented leaves. Firstly, the point cloud data of cucumber was collected from four angles by depth camera, and on the basis of statistical filtering and color filtering to remove the background noise as well as outliers, the complete cucumber plant point cloud by aligning the point cloud based on rotary axis and generalized nearest point iterative algorithm (GICP) , and then the region growth algorithm was improved by using voxel-based and moving least squares algorithms (MLS) to realize the separation of stems and leaves and the segmentation of leaves ; finally , phenotypic parameters such as number of leaves, leaf area, leaf length , leaf width , leaf circumference were automatically extracted from the segmented leaf point cloud. The experimental results showed that individual leaves could be accurately segmented by the improved zone-growth algorithm compared with the traditional zone-growth algorithm, with an average increase in accuracy of 12. 5 percentage points for 15 d of transplanting and 22. 5 percentage points for 60 d of transplanting. The coefficient of determination R for the four parameters of leaf area, leaf length, leaf width, and leaf circumference were 0. 96, 0. 93 , 0. 93 , and 0. 94, respectively, and the root-mean-square error RMSE was 12. 69 cm , 0. 93 cm, 0. 98 cm, and 2. 27 cm, respectively, compared with the true measurements. Therefore, the proposed method can efficiently segment individual leaf point clouds from a single cucumber point cloud and accurately calculate related phenotypic traits, providing strong technical support for high-throughput automated phenotypic measurements in greenhouse cucumbers. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 34
Main heading: Iterative methods
Controlled terms: Least squares approximations? - ?Mean square error? - ?Seed? - ?Wiener filtering
Uncontrolled terms: 3D point cloud? - ?Cucumber leaf? - ?Cucumber plants? - ?Growth algorithms? - ?Leaf area? - ?Leaf length? - ?Phenotypic parameter? - ?Point-clouds? - ?Segmentation? - ?Zone growth
Classification code: 821.5 Agricultural Products? - ?1106.3 Digital Signal Processing? - ?1201.7 Optimization Techniques? - ?1201.9 Numerical Methods? - ?1202.2 Mathematical Statistics
Numerical data indexing: Size 2.70E-01m, Size 6.90E-01m, Size 9.30E-01m, Size 9.80E-01m
DOI: 10.6041/j.issn.1000-1298.2025.03.035
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
32. Influence of Different Vortex Design on Parameter Analysis and Performance Optimization of Mixed-flow Pump Impeller
Accession number: 20251418174156
Title of translation: 不同渦設(shè)計(jì)下混流泵葉輪參數(shù)分析與性能優(yōu)化
Authors: Wang, Mengcheng (1); Ding, Zheng (1); Lin, Renrong (2); Zhang, Lingbo (2); Chen, Tingling (2); Xia, Weigang (3); Chen, Jiaqi (1)
Author affiliation: (1) College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou; 225009, China; (2) Leo Croup Co., Ltd., Hangzhou; 317599, China; (3) Shanghai Kaiquan Pump Industry ( Croup) Co., Ltd.,, Shanghai; 201804, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 312-322
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: According to different forms of circulation distribution, mixed flow pump design can be divided into free vortex, forced vortex, and composite vortex designs. A mixed flow pump model TJ - HL - 05 , whose performance has been widely verified in the South to North Water Transfer Project, was taken as the research object. Based on the inverse design method, the parameterization of the impeller blade under the nonlinear circulation distribution was realized with the help of the continuity equation, the energy equation and the simplified radial balance equation. On this basis, the parameter analysis of the mixed flow pump impeller under the nonlinear circulation distribution under different working conditions was studied by using the orthogonal experimental design, and the performance optimization of the mixed flow pump was completed based on the analysis results. The results showed that the circulation control parameters rvb and rvs had a significant impact on efficiency and head under all operating conditions, and compared with traditional free vortex design, compound vortex design had a higher optimization upper limit. Compared with the original model, the efficiency of the free vortex design optimization results was increased by 0. 31 percentage points, 1.63 percentage points, and 1.03 percentage points respectively under the 0. 8()des Q?es , and 1. 2()des operating conditions, while the efficiency of the composite vortex design optimization results was increased by 1. 09 percentage points, 3. 51 percentage points, and 9. 71 percentage points, respectively, and the head difference between the three under the design operating conditions was relatively small. The results of the internal flow analysis indicated that using a compound vortex design that considered the distribution of circulation was beneficial for further improving the flow state at the outlet of the impeller, thereby reducing the hydraulic losses of downstream components of the impeller. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Vortex flow
Controlled terms: Convergence of numerical methods? - ?Flow fields? - ?Integrated circuit design? - ?Inverse problems? - ?Machine design? - ?Pumps? - ?Structural dynamics
Uncontrolled terms: Circulation distribution? - ?Compound vortex design? - ?Flow fields analysis? - ?Free vortex design? - ?Free vortices? - ?Mixed flow pump? - ?Operating condition? - ?Parameter analysis? - ?Percentage points? - ?Performance optimizations
Classification code: 301.1 Fluid Flow? - ?408 Structural Design? - ?601 Mechanical Design? - ?609.2 Pumps? - ?714.2 Semiconductor Devices and Integrated Circuits? - ?904 Design? - ?1201 Mathematics? - ?1201.9 Numerical Methods
DOI: 10.6041/j.issn.1000-1298.2025.03.031
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
33. Cotton Seedling Salt Stress Diagnosis Method Based on Multi-leaf Rapid Chlorophyll Fluorescence and ID-DRDC -Net
Accession number: 20251418174151
Title of translation: 基于多葉位快速葉綠素?zé)晒夂?D-DRDC-Net的棉苗鹽脅迫診斷方法
Authors: Weng, Haiyong (1, 2); Zeng, Haiyan (1, 2); Lei, Qingyuan (3, 4); Zhou, Beibei (3, 4); Li, Jiayi (5); Xu, Hongyan (1)
Author affiliation: (1) College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou; 350002, China; (2) Fujian Key Laboratory of Agricultural Information Sensing Technology, Fuzhou; 350002, China; (3) State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an; 710048, China; (4) Faculty of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an; 710048, China; (5) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 476-484 and 493
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Salt stress can lead to a decrease in cotton fiber quality and yield, especially during the seedling stage when it is most affected by salt stress. In order to achieve rapid diagnosis of salt stress in cotton seedlings, rapid chlorophyll fluorescence technology was used to obtain OJIP curves of cotton seedling canopy leaves under different degrees of salt stress, and deep residual network ( ResNet) and dilated convolution structures were combined to construct a ID - deep residual dilated convolutional neural network (ID - DRDC - Net) cotton seedling salt stress deep learning diagnosis model based on “ leaf - position channel” fluorescence data fusion. The results showed that salt stress significantly led to a decrease in water content in cotton seedlings, an increase in malondialdehyde ( MDA ) content, superoxide dismutase (SOD) activity, and peroxidase (POD) activity. The trend of salt stress on cotton seedlings in the vertical direction showed significant changes in various parameters of the upper leaves of the plant, with LI being the most sensitive leaf position to stress, while mature leaves were relatively less affected. Compared with other models, the diagnostic accuracy of 1D - DRDC - Net for three salt concentration gradients (0 mmol/L, 100 mmol/L and 200 mmol/L) under different stress times in cotton seedlings was 76. 67% , with an Fl score of 76. 48% , which was 5 percentage points higher than the accuracy of support vector machine ( SVM ) and back propagation neural network ( BPNN ) , 14. 45 percentage points higher than that of random forest ( RF) , and 3. 34 percentage points higher than that of bidirectional long short-term memory ( Bi - LSTM) . The fluorescence information fusion strategy based on “ leaf - position channel” was more effective than using only a single sensitive leaf position fluorescence information by 8. 89 percentage points. Its robustness and generalization ability were stronger than that of models that only use ordinary convolution kernels and cancel “ skip connections “. Finally, the established ID - DRDC - Net model achieved diagnostic accuracies of 83. 33% , 88. 33% , and 95. 00% on the 7th, 14th, and 21st day after cotton seedlings were subjected to salt stress, respectively. The research results can provide theoretical basis for cotton cultivation management. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 33
Main heading: Superoxide dismutase
Controlled terms: Convolutional neural networks? - ?Cotton fibers? - ?Data fusion? - ?Deep neural networks? - ?Diagnosis? - ?Hardware security? - ?Long short-term memory? - ?Network security? - ?Radial basis function networks? - ?Shear bands ? - ?Steganography? - ?Support vector machines? - ?Yield stress
Uncontrolled terms: 1d - DRDC - net? - ?Chlorophyll fluorescence? - ?Convolutional neural network? - ?Cotton seedling salt stress? - ?Diagnostic accuracy? - ?Leaf position? - ?Percentage points? - ?Rapid chlorophyll fluorescence? - ?Salt stresss? - ?Vertical heterogeneity distribution
Classification code: 101.3 Tissue Engineering? - ?102.1 Medicine? - ?213.1 Natural Fibers? - ?214 Materials Science? - ?214.1.1 Stress and Strain? - ?801.1 Biochemistry? - ?1101.2 Machine Learning? - ?1101.2.1 Deep Learning? - ?1106 Computer Software, Data Handling and Applications? - ?1106.2 Data Handling and Data Processing? - ?1108.1 Cybersecurity? - ?1108.2 Cryptography
Numerical data indexing: Molar concentration 0.00E00mol/m3, Molar concentration 1.00E+02mol/m3, Molar concentration 2.00E+02mol/m3, Percentage 0.00E00%, Percentage 3.30E+01%, Percentage 4.80E+01%, Percentage 6.70E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.047
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
34. Tomato Maturity Detection Method Based on Lightweight YOLO v5s MCA
Accession number: 20251418174179
Title of translation: 基于輕量化YOLO v5s-MCA的番茄成熟度檢測方法
Authors: Xi, Xiaobo (1); Ding, Jieyuan (1); Weng, Xiaoxiang (1); Wang, Yu (1); Han, Lianjie (1); Zou, Yunhan (1); Tang, Zihao (1); Zhang, Ruihong (1)
Author affiliation: (1) School of Mechanical Engineering, Yangzhou University, Yangzhou; 225127, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 383-391 and 436
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the challenges of tomato recognition in natural environments, such as interference from complex backgrounds and difficulty in detecting adjacent fruits with similar ripeness levels, a lightweight YOLO v5s - MCA model for tomato ripeness detection was proposed. The model categorized tomato ripeness into four distinct stages: mature, turning mature, color transition, and immature. Firstly, it incorporated the MobileNetV3 network as the backbone, significantly reducing the model’s parameter count and computational requirements. Moreover, the coordinate attention ( CA ) mechanism was integrated into the backbone and neck networks, enhancing the model’s ability to enhance the model’s ability to represent tomato features. Additionally, the neck network was replaced with a weighted bidirectional feature pyramid network ( BiFPN ) to strengthen feature fusion and improve recognition accuracy. The standard convolution modules in the neck network were also replaced with GSConv convolution to reduce model complexity and enhance the ability to capture target information. Experimental evaluations revealed the superior performance of the YOLO v5s - MCA model. The model achieved a parameter count of only 2. 33 X 10 , with a computational cost of 4. 1 X 10 and a memory footprint of just 4. 83 MB. The model achieved a precision of 92. 8% and a mean average precision (mAP) of 95. 1% , representing improvements of 3. 4 percentage points and 4.4 percentage points, respectively, compared with the baseline YOLO v5s model. To further validate the effectiveness of the YOLO v5s - MCA model, it was compared with six other models, including YOLO v3s, YOLO v5s, YOLO v5n, YOLO v7, YOLO v8n, and YOLO vlOn. Among these, the YOLO v5s - MCA model outperformed its counterparts in terms of lightweight design and detection performance. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Fruits
Controlled terms: Computer vision? - ?Convolution? - ?Feature extraction? - ?Image recognition
Uncontrolled terms: Color transition? - ?Complex background? - ?Detection methods? - ?Lightweight? - ?Maturity detection? - ?Modeling abilities? - ?Natural environments? - ?Percentage points? - ?Tomato? - ?YOLO v5s
Classification code: 716.1 Information Theory and Signal Processing? - ?821.5 Agricultural Products? - ?1101.2 Machine Learning? - ?1106.5 Computer Applications? - ?1106.8 Computer Vision
Numerical data indexing: Percentage 1.00E00%, Percentage 8.00E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.038
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
35. Three-dimensional Reconstruction and Phenotype Detection of Citrus Fruits Based on Single-view RGBD Images
Accession number: 20251418174182
Title of translation: 基于單視角RGBD圖像的柑橘果實(shí)三維重建與表型檢測方法
Authors: Xu, Shengyong (1, 2); Yi, Tongzhou (1, 2); Qin, Ziyi (1, 2); Fan, Qingtao (1, 2); Yang, Honglei (1, 2); Li, Shanjun (1, 2)
Author affiliation: (1) School 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
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 80-90
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The measurement and analysis of fruit phenotypes are crucial aspects of plant breeding and genetics research. Methods for phenotype detection using single-view RGBD images offer high throughput and low cost but are limited by sensor resolution and perspective, often failing to obtain data such as the surface area and volume of fruits. An improved method was proposed based on PFNET that used a depth camera to capture single-view point clouds of spherical-like fruits for high-precision 3D reconstruction and non-invasive phenotype measurements. To address the issue of varying input scales in the completion network, an adaptive geometric completion strategy was introduced to transform single-view point clouds into approximate hemispheres. The addition of a fourth scale to the PFNET framework enhanced the utilization of dense point clouds acquired by KINECT cameras, facilitating the completion of complex shapes and structures rich in detail. By incorporating a four-head self-attention module, the network’s ability to capture interdependencies and spatial relationships among points in the point cloud was improved, enhancing feature extraction capabilities. An optimized fruit point cloud module was added to resolve issues with local diffusion in the original network-generated point clouds and to improve their quality. A targeted phenotype detection method, designed to mimic manual measurements, was also proposed. Experimental results showed that this method achieved point cloud quality comparable to that obtained by structured light 3D scanners for citrus fruits, with high fidelity in 3D reconstruction. For the detection of four phenotypes-transverse diameter, longitudinal diameter, surface area, and volume-the R values exceeded 0. 96, with average measurement accuracy above 93. 24% , approaching that of 3D scanners but at 50 times of the efficiency and one-tenth of the cost. Compared with RGBD image methods, the single-fruit detection time was increased by 17.97 s, but there was a significant improvement in transverse and longitudinal diameter detection accuracy, allowing for the simultaneous measurement of four phenotypic parameters. Compared with the 3D scanner method, the difference in detection accuracy was within 4 percentage points, but the speed was more than 48 times faster, with hardware costs reduced to only one-tenth of the latter’s and easier implementation of automation. This method struck a good balance between detection accuracy, operational speed, hardware cost, and level of automation, offering a cost-effective, high-performance 3D reconstruction technology with great potential for non-invasive measurement of spherical-like fruit phenotypes. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 23
Main heading: Fruits
Controlled terms: Multispectral scanners? - ?Phytoplankton? - ?Spheres
Uncontrolled terms: 3D reconstruction? - ?3D-scanners? - ?Deep learning? - ?Detection accuracy? - ?PFNET? - ?Phenotypic detection? - ?Point cloud completion? - ?Point-clouds? - ?RGBD image? - ?Spherical fruits
Classification code: 103 Biology? - ?821.5 Agricultural Products? - ?942.1.3 Optical Instruments? - ?942.2.2 Detectors and Sensing? - ?1201.14 Geometry and Topology
Numerical data indexing: Percentage 2.40E+01%, Time 1.797E+01s
DOI: 10.6041/j.issn.1000-1298.2025.03.008
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
36. Design and Experiment of Wheat Plot Seeder Control System Based on Beidou Fault-tolerant Strategy
Accession number: 20251418174157
Title of translation: 基于北斗容錯(cuò)策略的小麥小區(qū)播種機(jī)控制系統(tǒng)研究
Authors: Xue, Chen (1); Chen, Liqing (1, 2); Zhang, Chunling (1, 2); Liu, Ce (1, 2); Zhang, Liuyang (1); Zhu, Junwen (1)
Author affiliation: (1) School of Engineering, Anhui Agricultural University, Hefei; 230036, China; (2) Anhui Province Key Laborotary of Intelligent and Green Agricultural Equipment, Hefei; 230036, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 240-246 and 362
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: With the development of intelligence, Beidou system has been widely used in agricultural machinery, but there is a problem of Beidou signal loss during operation. In response to the problem of Beidou signal loss in the electric control seeding system of the wheat plot, which leads to abnormal Beidou system messages and a decrease in seeding accuracy, a wheat plot seeding control system was proposed based on fault-tolerant strategy. Firstly, by establishing a Beidou message parsing model, the factors affecting the speed of the seeding motor were determined, and a Beidou fault-tolerant strategy based on trend moving average method was proposed. Secondly, the fuzzy neural network PID algorithm improved by particle swarm optimization algorithm was applied to achieve precise control of the motor. Finally, experimental verification was carried out. The results of the bench test showed that when artificially modifying the Beidou message to simulate anomalies, the average coefficient of variation for the consistency of wheat row displacement was 3. 87% , which met the seeding requirements. The fault-tolerant strategy was applied to field sowing operations in a wheat plot. The experimental results showed that the coefficient of variation of multi row sowing uniformity in three sets of experiments were 19. 94% , 20. 76% , and 21. 79% , respectively. And the coefficient of variation for uniformity of single row sowing was 19. 93% , 20. 87% , and 22. 26% , respectively, which met the national standards and agricultural requirements for the wheat plot, and verified the reliability and accuracy of the seeding control system based on fault-tolerant strategy. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 24
Main heading: Particle swarm optimization (PSO)
Controlled terms: Electric final control devices? - ?Electric machine control
Uncontrolled terms: Abnormal message? - ?Beidou fault-tolerance strategy? - ?Beidou systems? - ?Coefficients of variations? - ?Electric control? - ?Fault-tolerant strategy? - ?Moving average method? - ?Seeding uniformity? - ?Signal loss? - ?Wheat plot seeder
Classification code: 731.2 Control System Applications? - ?732.1 Control Equipment? - ?1106 Computer Software, Data Handling and Applications? - ?1201.7 Optimization Techniques
Numerical data indexing: Percentage 2.60E+01%, Percentage 7.60E+01%, Percentage 7.90E+01%, Percentage 8.70E+01%, Percentage 9.30E+01%, Percentage 9.40E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.024
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
37. Design and Experiment of Side-throwing Cotton Stalk Crushing and Returning Device
Accession number: 20251418174112
Title of translation: 側(cè)拋式棉稈粉碎還田裝置設(shè)計(jì)與試驗(yàn)
Authors: Yan, Limin (1, 2); Wu, Tao (1); Jiang, Deli (1); Gou, Haixiao (1, 2); Fu, Xuanhe (1); Zhang, Jinhao (1)
Author affiliation: (1) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832003, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 216-226
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problems of low qualified rate of cotton stalk crushing length after operation of cotton stalk crushing and returning device, easy accumulation and uneven distribution of broken stalks after throwing and returning to the field, a side throwing cotton stalk crushing and returning device which can be installed on the residual film recycling machine was designed. The structure and working principle of the device were expounded. The structure design and operation performance analysis of key components such as cotton stalk crushing device, lateral conveying device and broken stalk throwing device were carried out, and the structure and operation parameters of key components were preliminarily determined. The discrete element simulation analysis and experimental design of the straw scattering device were carried out. According to the design scheme, a type of side throwing cotton stalk crushing and returning device was developed and installed on the residual film recycling machine for three-factor and three-level quadratic regression orthogonal field experiment. The results showed that when the forward speed of the machine was 8 km/h, the rotation speed of the crushing knife shaft was 2 000 r/min, and the rotation speed of the screw conveyor was 1 200 r/min, the qualified rate of cotton stalk crushing length was 93. 96% , the throwing uniformity was 86. 98% , the average cotton stalk crushing length was 116. 9 mm, and the average stubble height was 71. 4 mm. The machine had the best field operation effect under this parameter combination. The test indexes of the device can meet the design and agronomic requirements, which provided a theoretical basis and support for the structural optimization design of the cotton stalk crushing and returning device. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 22
Main heading: Screw conveyors
Uncontrolled terms: Cotton stalk? - ?Design and operations? - ?Design performance? - ?Lateral transport? - ?Operation performance? - ?Parameter optimization? - ?Residual films? - ?Rotation speed? - ?Scattering back to the field? - ?Structure design
Classification code: 692.1 Conveyors
Numerical data indexing: Angular velocity 0.00E00rad/s, Angular velocity 3.34E+00rad/s, Percentage 9.60E+01%, Percentage 9.80E+01%, Size 4.00E-03m, Size 8.00E+03m, Size 9.00E-03m
DOI: 10.6041/j.issn.1000-1298.2025.03.022
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
38. Precision Reduction Mechanism Design and Stiffness Analysis
Accession number: 20251418174190
Title of translation: 精密微動(dòng)縮小機(jī)構(gòu)設(shè)計(jì)與剛度分析
Authors: Yang, Manzhi (1); Wang, Yue (1); Zhang, Xiaodong (1); Zhang, Chuanwei (1); Han, Feiyan (1); Feng, Bin (1)
Author affiliation: (1) College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an; 710054, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 531-538
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Precision micromotion reduction mechanism can provide precision motion displacement in a small space, which can be widely used in microelectronics, medical devices and chip packaging and other precision operation fields. A precision micromotion reduction mechanism was designed based on the principle of flexible hinge lever and the principle of no additional motion, which was able to reduce the input displacement according to 2- 1 precision, and there was no additional force and displacement in the process of motion. The stiffness analysis of the designed precision micromotion reduction mechanism was carried out by the equivalent stiffness method, and the theoretical stiffness of the mechanism was calculated to be 75.72 N/|xm; the stiffness of the precision micromotion reduction mechanism was analyzed by the finite element method to be 74. 06 N/|xm; and the stiffness of the precision micromotion reduction mechanism was measured by the experimental method to be 68. 86 N/|xm. The error between the theoretical analysis results and finite element analysis results was 2. 19% , and the error between the theoretical analysis results and experimental results was 9. 06% . The analysis results verified the validity and accuracy of the analysis method of equivalent stiffness method. The results of the study had important theoretical reference value for the design and stiffness analysis of precision micromanipulation mechanism. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Chip scale packages
Controlled terms: Biomedical equipment? - ?Hinges? - ?Micromanipulators? - ?Precision engineering
Uncontrolled terms: Design Analysis? - ?Equivalent stiffness? - ?Equivalent stiffness method? - ?Lever principle? - ?Mechanism design? - ?Micro motion? - ?Micromotion reduction mechanism? - ?Precision motion? - ?Reduction mechanisms? - ?Stiffness analysis
Classification code: 101.2 Biomedical Equipment? - ?601.2 Machine Components? - ?601.3 Mechanisms? - ?714.2 Semiconductor Devices and Integrated Circuits? - ?731.5 Robotics? - ?901 Engineering Profession
Numerical data indexing: Force 6.00E+00N, Force 7.572E+01N, Force 8.60E+01N, Percentage 1.90E+01%, Percentage 6.00E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.053
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
39. Method of Navigation Parameter Acquisition of Agricultural Machinery in Tunnel Greenhouses Based on Steel Tube Detection
Accession number: 20251418174174
Title of translation: 基于鋼骨架檢測的單棟塑料溫室農(nóng)業(yè)機(jī)械導(dǎo)航參數(shù)獲取方法
Authors: Ye, Ziwei (1); Yu, Feng (2); Qi, Zezhong (1); Zhou, Jun (1); Ji, Haibo (3); Ge, Xunyi (2)
Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Jiangsu Agricultural Machinery Development and Application Center, Nanjing; 210000, China; (3) Nantong FLW Agricultural Equipment Co., Ltd.,, Nantong; 226000, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 485-493
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: With the aim of meeting the autonomous navigation requirements of small and medium-sized agricultural machinery in tunnel greenhouse with no crops or low crops, a navigation line fitting method based on steel tube detection was proposed. Firstly, the indoor environment structure was analyzed. Secondly, the greenhouse point cloud data was collected by LiDAR, and the nearest side window point convergence was extracted from the 3D laser point cloud data by Euclidian transformation, pass-through filtering and DBSCAN clustering. Then a steel tube detection method was proposed with the intention of obtaining stable steel tube point cloud, which iterated through all the scanning lines of the target window point cloud, considering its spatial location and other factors, set different thresholds to filter out the plastic film point cloud and extract the qualified steel tube point cloud. Finally, a straight line fitted by the steel tube point cloud was obtained by principal component analysis, and the navigation parameters of the platform in the greenhouse were determined by using this as the navigation reference line. The steel tube detection test showed that the efficiency of the steel tube detection method in tunnel greenhouses was not less than 88% , and the navigation reference line fitted by the proposed algorithm had a high updating frequency. In the navigation parameter measurement accuracy test, the mean absolute errors of cross range and yaw angle were 0. 03 m and 2. 12° , respectively. The research result can meet the requirements of autonomous navigation of agricultural machinery in a tunnel greenhouse, which can provide reference for the research of autonomous navigation in this environment. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 22
Main heading: Tubular steel structures
Controlled terms: Agricultural robots? - ?Automatic guidance (agricultural machinery)? - ?Concrete dams
Uncontrolled terms: Autonomous navigation? - ?Detection methods? - ?LiDAR? - ?Navigation parameters? - ?Parameters acquisitions? - ?Point cloud data? - ?Point-clouds? - ?Reference lines? - ?Steel tube? - ?Tunnel greenhouse
Classification code: 202.5.3 Steel? - ?217.2 Concrete? - ?408.1 Structural Members and Shapes? - ?441.1 Dams? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment
Numerical data indexing: Percentage 8.80E+01%, Size 3.00E+00m
DOI: 10.6041/j.issn.1000-1298.2025.03.048
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
40. Design and Experimentation of Fish Feeding Intensity System Based on Binocular Cameras and Deep Learning
Accession number: 20251418174189
Title of translation: 基于雙目相機(jī)和深度學(xué)習(xí)的魚類攝食強(qiáng)度分析方法
Authors: Yu, Guoyan (1, 2); Qian, Liwen (1, 2); Liu, Haochun (1, 2); He, Zijian (1, 2)
Author affiliation: (1) School of Mechanical Engineering, Guangdong Ocean University, Zhanjiang; 524088, China; (2) Guangdong Marine Equipment and Manufacturing Engineering Technology Research Center, Zhanjiang; 524088, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 403-413 and 424
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Assessing the feeding intensity of fish in large-scale cages is crucial for enhancing feed utilization and reducing farming costs. Traditional feeding methods heavily rely on the experience of aquaculture managers, often leading to overfeeding, which contaminates water quality, or underfeeding, and adversely affects fish health. To accurately determine fish feeding intensity in deep-sea cage farming and achieve precise feeding, focusing on the splashes generated by pompano during feeding, utilizing depth images captured by a binocular camera, a non-invasive feeding intensity analysis method was proposed, involving semantic segmentation and area calculation of the splash. Firstly, to enable the model’s deployment on low-cost edge devices, the YOLO v8n - seg model was improved through the incorporation of StarNet, BiFPN, and a custom-designed SCD - Head shared convolutional detection head, resulting in the lightweight YOLO v8n - SBS model. This modification achieved a 3. 2 percentage points increase in accuracy while reducing the number of parameters and floating-point operations by 71% and 36% , respectively. Secondly, to minimize equipment costs, a binocular camera was employed, and PVC boards were used to simulate splash targets on land for experimental convenience. A linear regression model (DI) was proposed to calculate splash area based on depth information. The results of the DI model on the test set demonstrated an R value of 0. 977 , an RMSE of 0. 033 m , and an MAE of 0. 023 m , indicating robust performance. Ultimately, the two models were combined into YOLO v8n -SBS - DI, which can segment splashes and compute their area, allowing for the assessment of feeding intensity through the trend of splash area changes. Sea trial results showed that the calculated splash area yields an R? value of 0. 914, an RMSE of 0. 973 m , and an MAE of 0. 870 m . These experimental outcomes confirmed that the model exhibited strong robustness and met the demands for splash area calculations in complex environments, thereby providing technical support for determining fish feeding intensity. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 30
Main heading: Semantic Segmentation
Controlled terms: Binoculars? - ?Fish? - ?Linear regression? - ?Underwater cameras
Uncontrolled terms: Area calculation? - ?Binocular camera? - ?Deep sea? - ?Deep-sea cage aquaculture? - ?Fish feeding? - ?Large-scales? - ?Lightweight? - ?R value? - ?Semantic segmentation? - ?YOLO v8n - seg
Classification code: 741.3 Optical Devices and Systems? - ?742.2 Photographic and Video Equipment? - ?822.3 Food Products? - ?1106.8 Computer Vision? - ?1202.2 Mathematical Statistics
Numerical data indexing: Percentage 3.60E+01%, Percentage 7.10E+01%, Size 2.30E+01m, Size 3.30E+01m, Size 8.70E+02m, Size 9.73E+02m
DOI: 10.6041/j.issn.1000-1298.2025.03.040
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
41. Analysis of Drought Phenotypic Characteristics of Poplar Seedlings Based on TLS Point Cloud Skeleton Extraction
Accession number: 20251418174154
Title of translation: 基于TLS點(diǎn)云骨架提取的楊樹苗木干旱表型特征分析
Authors: Zhang, Huichun (1, 2); Zhou, Liwen (1); Bian, Liming (3, 4)
Author affiliation: (1) School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing; 210037, China; (2) Collaborative Innovation Center for Efficient Processing and Utilization of Forestry Resources, Nanjing Forestry University, Nanjing; 210037, China; (3) College of Forestry and Grassland, Nanjing Forestry University, Nanjing; 210037, China; (4) Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing; 210037, China
Corresponding author: Zhang, Huichun([email protected])
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 188-197
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The key to monitoring plant drought stress lies in how to accurately locate and identify targets, and for this reason, an efficient plant phenotype extraction system has become a necessity. Because of its ability to provide high-precision 3D description, 3D point cloud information has become an important data support in this system, which provides a solid technical foundation for the monitoring of plant growth in arid environments. Ground-based LiDAR technology was used to collect the three-dimensional point cloud data of poplar seedlings, and an LI median skeleton extraction algorithm combined with pre-segmentation was proposed to realize fine phenotype extraction and drought feature analysis. Firstly, the original point cloud was denoised and preprocessed by elevation analysis, radius filtering and color index filtering. Secondly, the improved DBSCAN algorithm was used to realize the single-tree segmentation of the group point cloud, and the octree based on the greedy algorithm was combined with the global search to optimize the segmentation accuracy. Finally, the KNN algorithm and MRF algorithm were used to pre-segment the point cloud of a single plant, so as to improve the spatial consistency of the point cloud data, reduce the computational complexity of the LI median algorithm, and calculate the phenotypic characteristics of poplar seedlings through the obtained skeleton point cloud. Two new indexes were introduced to reveal the adaptation mechanism of poplar seedlings under drought stress by optimizing resource allocation and reducing water consumption. Among them, the crown length rate ranked first in the gray correlation degree of drought resistance evaluation in the CK group and DT group, with a correlation coefficient of - 0. 85 , indicating that it was highly sensitive to water supply and could fully reflect the resource use efficiency and drought resistance of plants, which was the core index to evaluate the drought adaptability of poplar seedlings. By combining three-dimensional point cloud technology and fine phenotypic analysis, the research can provide technical support for efficient and accurate monitoring of early drought stress in poplar seedlings, which was of significance for determining drought phenotypic indicators and optimizing the drought resistance evaluation system. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Musculoskeletal system
Controlled terms: Seed
Uncontrolled terms: Drought resistance? - ?Drought response? - ?Drought response indicator? - ?Drought stress? - ?Phenotypic characteristic? - ?Point cloud skeleton? - ?Point-clouds? - ?Poplar? - ?Skeleton extraction? - ?Terrestrial laser scanning
Classification code: 101.4 Biomechanics, Bionics and Biomimetics? - ?821.5 Agricultural Products
DOI: 10.6041/j.issn.1000-1298.2025.03.019
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
42. Crushing Mechanism of Walnut under Extrusion-shear Load Based on FDEM
Accession number: 20251418174165
Title of translation: 基于FDEM的核桃擠壓-剪切載荷下破碎機(jī)理與減損方法
Authors: Zhang, Yongcheng (1, 2); Gai, Guangxin (2); Zong, Wangyuan (1); Hen, Peiyu (2); Wang, Faan (3); Wang, Xingyu (2)
Author affiliation: (1) School of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) School of Mechanical and Electrical Engineering, Tarim University, Alar; 843300, China; (3) College of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming; 650500, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 291-300
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Shell cracking to extract the kernel is a crucial step in the advanced processing of walnuts. Addressing the low shelling efficiency and inadequate kernel integrity associated with current cracking methods, the finite discrete element method ( FDEM) was employed to simulate the fracture process of walnuts under extrusion-shear loads. A extrusion-shear cracking technique was proposed. Initially, physical parameters such as shell thickness and shell-kernel gaps of the Wen 185 walnuts were measured to construct and calibrate the simulation model. Subsequently, both qualitative and quantitative analyses were conducted to examine how the shelling angle under extrusion-shear loads affected the fracture of the shell and kernel. The relationship between shelling angle, compression amount, and the fragmentation of the walnut shell and kernel was also investigated. This clarified the cracking mechanism under extrusion-shear loads and the reasons for kernel damage. The results showed that the cracking mechanism of walnut shells and kernels involved the following; the walnut shell fractured primarily under tensile stress, generating penetrating cracks on the contact surface, which facilitated rapid shell breaking. In contrast, the walnut kernel fractured predominantly under shear stress. During the shell-breaking process, the walnut kernel tended to come into contact with the shell at multiple points, leading to stress concentration, which caused kernel fractures and hindered the preservation of kernel integrity. As the compression increased at different cracking angles, the continuous force exerted on the walnut shell caused inward movement, progressively increasing the damage to the walnut kernel. Based on these mechanisms, it was suggested that after the initial shell fracture, the application of cracking force should cease to allow for deformation recovery time. Subsequently, applying intermittent loading forces can reduce multiple contact points between the shell and kernel, enabling multiple shell fractures with minimal displacement and effectively reducing kernel damage. Finally, a co-directional roller cracking method was proposed to achieve multiple small-displacement shelling, which was validated through experiments. The preliminary optimization results showed that with roller speeds of 33 r/min and 28 r/min and a shelling gap of 33 mm, the shelling rate reached 96. 9% , and the kernel integrity rate was 84. 3% . Compared with traditional counter-rotating shelling methods, the shelling and kernel integrity rates were improved by 7. 7 percentage points and 3.2 percentage points, respectively. The research result can provide a theoretical reference for enhancing walnut shelling efficiency and kernel integrity. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 36
Main heading: Shear stress
Controlled terms: Cracks? - ?Extrusion? - ?Fracture? - ?Gluing? - ?Rollers (machine components)? - ?Safety factor? - ?Shear flow? - ?Shells (structures)? - ?Strain hardening? - ?Stress analysis ? - ?Stress concentration? - ?Superplasticity? - ?Tensile stress? - ?Thermal spraying
Uncontrolled terms: Cracking mechanisms? - ?Discrete elements method? - ?Extrusion-shear? - ?Finite coupled discrete element method? - ?Percentage points? - ?Shear loads? - ?Shelling rate? - ?The whole rate of benevolence? - ?Walnut? - ?Walnut shells
Classification code: 201.5.2.2 Metal Forming Practice? - ?201.7.1 Heat Treatment Processes? - ?206.1 Processing of Plastics and Other Polymers? - ?208.1 Coating Techniques? - ?210 Adhesive Materials? - ?214 Materials Science? - ?214.1.1 Stress and Strain? - ?214.1.2 Fatigue, Cracks and Fracture? - ?214.1.3 Elasticity, Plasticity, Creep and Deformation? - ?301.1.5 Flow of Fluid-Like Materials? - ?408.1 Structural Members and Shapes? - ?601.2 Machine Components? - ?914 Safety Engineering? - ?914.1 Accidents and Accident Prevention
Numerical data indexing: Angular velocity 4.676E-01rad/s, Angular velocity 5.511E-01rad/s, Percentage 3.00E+00%, Percentage 9.00E+00%, Size 3.30E-02m
DOI: 10.6041/j.issn.1000-1298.2025.03.029
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
43. UWB Greenhouse Positioning Technology Based on Improved Adaptive Kalman Filter Algorithm
Accession number: 20251418167477
Title of translation: 基于改進(jìn)自適應(yīng)卡爾曼濾波算法的溫室UWB定位技術(shù)
Authors: Zhang, Zhaoguo (1); Zhu, Shiliang (1); Wang, Faan (1); Xie, Kaiting (2); Zhang, Jionghao (1); Li, Manman (1)
Author affiliation: (1) Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming; 650500, China; (2) Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming; 650500, China
Corresponding author: Zhang, Zhaoguo([email protected])
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 494-502 and 522
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the issue of insufficient positioning accuracy of ultra-wideband (UWB) positioning technology in agricultural greenhouse environments, caused by poor interference immunity and unknown statistical characteristics, a UWB positioning technology was proposed based on an improved adaptive Kalman filter ( IAKF) algorithm. Firstly, an anomaly detection mechanism was introduced to identify divergence phenomena during the filtering process. Subsequently, the measurement noise covariance matrix was updated in real-time to suppress filter divergence and enhance the algorithm’s adaptability in the presence of strong noise fluctuations. Simulation positioning experiments under three different noise environments were conducted to compare and analyze the performance of UWB , IAKF, adaptive Kalman filter (AKF) , and Kalman filter (KF) algorithms. The simulation results showed that the IAKF algorithm exhibited stronger adaptability and robustness. Finally, using a self-developed agricultural tracked vehicle as the positioning carrier, UWB positioning experiments were conducted in the greenhouse environment. The experimental results indicated that in the greenhouse environment, the positioning accuracy of the tracked vehicle using the IAKF algorithm was improved by 22. 2% and 13. 0% in line of sight (LOS) and 20. 0% and 15. 4% in non line of sight (NLOS) scenarios compared with that of the AKF and KF algorithms, respectively. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 33
Main heading: Adaptive filters
Controlled terms: Adaptive filtering? - ?Kalman filters? - ?Tracked vehicles? - ?Wiener filtering
Uncontrolled terms: Adaptive kalman filter? - ?Adaptive kalman filter algorithms? - ?Greenhouse environment? - ?Improved adaptive kalman filter? - ?Kalman filter algorithms? - ?Positioning accuracy? - ?Positioning technologies? - ?Precise position? - ?Technology-based? - ?Ultrawide band
Classification code: 663 Buses, Tractors and Trucks? - ?703.2 Electric Filters? - ?716.1 Information Theory and Signal Processing? - ?1106.3 Digital Signal Processing
Numerical data indexing: Percentage 0.00E00%, Percentage 2.00E+00%, Percentage 4.00E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.049
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
44. Drought Monitoring in Haihe River Basin Based on Drought Fluorescence Monitoring Index
Accession number: 20251418167632
Title of translation: 基于干旱熒光監(jiān)測指數(shù)的海河流域干旱監(jiān)測研究
Authors: Zhao, Anzhou (1); Han, Xiaoran (1); Liu, Xianfeng (2); Zhang, Wei (1); Wang, Yahui (1); Li, Muyi (3)
Author affiliation: (1) School of Mining and Geomatics, Hebei University of Engineering, Handan; 056038, China; (2) School of Geography and Tourism, Shaanxi Normal University, Xi’an; 710119, China; (3) School of Civil Engineering and Architecture, Suqian University, Suqian; 223800, China
Corresponding author: Zhao, Anzhou([email protected])
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 458-466
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The Haihe River Basin is a crucial agricultural production region in China, and understanding the temporal and spatial characteristics of drought is vital for managing agricultural water resources and ensuring food security. Drought fluorescence monitoring index ( DFMI) for the Haihe River Basin was constructed based on the sun-induced chlorophyll fluorescence (SIF) , land surface temperature (LST) , precipitation, and soil moisture ( SM ) . This index comprehensively integrated vegetation growth, temperature, precipitation, and soil moisture content to monitor drought conditions. At the same time, the accuracy of the DFMI was evaluated by using existing drought indices and soil moisture data from monitoring stations. Additionally, trend analysis and run theory were employed to analyze the temporal and spatial evolution characteristics of the DFMI in the Haihe River Basin from 2001 to 2021 , as well as the spatial distribution of variables such as drought frequency, drought duration, and drought intensity. Results indicated that the correlation coefficients between DFMI and SM , self-calibrating Palmer droughtseverity index (scPDSI) , standardized precipitation evapotranspiration index (SPEI) (SPEI01 , SPEI03 , SPEI06, SPEI09, SPEI12) were 0. 58 , 0.64, 0.73, 0.52, 0.44, 0.47 and 0. 49, respectively. The correlation between DFMI and SM at 12 sites passed the 0.05 significance level test, indicating that DFMI was suitable for drought monitoring in the Haihe River Basin. The annual mean value of DFMI in the Haihe River Basin exhibited a significant increasing trend from 2001 to 2021 , with an increase rate of 0. 009 7/a (p ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 36
Main heading: Soil moisture
Controlled terms: Evapotranspiration? - ?Rivers
Uncontrolled terms: %moisture? - ?Drought characteristics? - ?Drought duration? - ?Drought fluorescence monitoring index? - ?Drought intensities? - ?Drought monitoring? - ?Haihe River basin? - ?Monitoring index? - ?Space-time evolution? - ?Upward trend
Classification code: 407 Maritime and Port Structures; Rivers and Other Waterways? - ?444 Water Resources? - ?483.1 Soils and Soil Mechanics? - ?1502.3 Hydrology
Numerical data indexing: Age 1.666E-01yr, Percentage 1.80E+01%, Percentage 2.60E+01%, Percentage 3.60E+01%, Percentage 6.342E+01%, Percentage 9.60E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.045
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
45. Design of Automatic Determination System for Point Cloud Segmentation and Morphology of Dairy Cows Based on SGPointNet + + Model
Accession number: 20251418169006
Title of translation: 基于SGPointNet + +模型的奶牛點(diǎn)云分割與表型自動(dòng)測定系統(tǒng)設(shè)計(jì)
Authors: Zhao, Jian (1, 2); Zhou, Guoyuan (1, 2); Wang, Zhiwen (1, 2); Li, Guoliang (1, 2); Zhong, Fagang (3); Li, Jiawei (1, 2)
Author affiliation: (1) College of Informatics, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key Laboratory of Smart Farming Technology for Agricultural Animals, Ministry of Agriculture and Rural Affairs, Wuhan; 430070, China; (3) Xinjiang Academy of Agricultural and Reclamation Science, Shihezi; 830049, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 180-187
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming to address the issues of heavy manual workload and the potential for inducing stress responses in dairy cow during traditional body measurement, a three-dimensional (3D) reconstruction and point cloud segmentation approach was proposed. This approach utilized an improved point cloud segmentation model for the automatic calculation of body measurements in cow. The research focused on Chinese Huaxi cow, and 212 sets of point cloud data from 115 dairy cows were collected using a 3D point cloud acquisition system. The Super - 4pcs algorithm was used for point cloud registration, followed by spatial pass-through filtering and neighborhood-based outlier filtering to complete the 3D reconstruction of the cow’s point cloud. The PointNet + + point cloud segmentation algorithm, combined with the spatial grouping enhancement ( SGE) module, was used to propose the improved SGPointNet + + model for point cloud segmentation. The segmentation results were then used to measure four body parameters; height, chest girth, abdominal girth, and withers height. The experimental results showed that the mean intersection over union ( MIoU) for segmentation using the SGPointNet + + model on the test set was 81. 87% , which was 27. 82 percentage points, 1.55 percentage points, 1. 19 percentage points, and 1.07 percentage points higher than that of PointNet, ASSANet, PointNeXt, and PointNet + + , respectively. The average absolute percentage errors for body measurements were 2. 38% , 3. 05% , 1.32% , and 1.69% for body height, chest girth, abdominal girth, and withers height, respectively. These results indicated that this method can be used for dairy cow body measurement, reducing workload while ensuring computational accuracy. It provided a methodological foundation for continuous animal phenotype measurement and offered technical insights for further improvements in segmentation and body measurement calculation models. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 27
Main heading: 3D reconstruction
Controlled terms: Digital elevation model? - ?Fertilizers? - ?Three dimensional computer graphics
Uncontrolled terms: Body measurements? - ?Body size measurement? - ?Body sizes? - ?Dairy cow? - ?Diary cow point cloud? - ?Partition? - ?Point cloud segmentation? - ?Point-clouds? - ?Size measurements? - ?Three-dimensional reconstruction
Classification code: 821.3 Agricultural Chemicals? - ?902.1 Engineering Graphics? - ?1106.2 Data Handling and Data Processing? - ?1106.3.1 Image Processing? - ?1106.8 Computer Vision? - ?1502.1.1.3 Soil Pollution
Numerical data indexing: Percentage 1.32E+00%, Percentage 1.69E+00%, Percentage 3.80E+01%, Percentage 5.00E+00%, Percentage 8.70E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.018
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
46. Design and Experiment of Intermittent Probe for Rumen pH Measurement in Dairy Cows
Accession number: 20251418174178
Title of translation: 基于超彈性金屬的間斷式奶牛瘤胃pH測量探頭設(shè)計(jì)與試驗(yàn)
Authors: Zhao, Jizheng (1, 2); Liu, Han (1, 2); Wang, Kaimin (1, 2); Zhang, Yanqin (1, 2); Qiu, Xinyang (1, 2); Song, Huaibo (1, 2)
Author affiliation: (1) College of Mechanical and Engineering, Northwest a and F University, Shaanxi, Yangling; 712100, China; (2) Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, 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: 3
Issue date: March 2025
Publication year: 2025
Pages: 392-402
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Rumen pH is an important physiological indicator for the health of cows in modern dairy farming. Among the existing electrodes, the intermittent pH reference electrode uses gas pressurization to promote the electrolyte exudation. However, there is a risk that the electrolyte outflow may be blocked. Hyperelastic metal was used to design a valve to control the intermittent outflow of reference electrolyte and a reference electrolyte pressurization component based on a spring piston system. The final assembly of the intermittent rumen pH detection probe in dairy cows was completed. The finite element analysis of the valve component determined that the length of the hyperelastic metal rod in the valve component was 9 mm, and the distance between the central axis of the silicone tube and the fixed end of the nitinol rod was 4. 5 mm. The pressure component used a spring with a piston for pressure, the spring stiffness was 0. 284 N/mm, the free height was 70 mm, and the maximum compression was 49 mm. The finite element analysis of the valve components showed that the maximum stress of the hyperelastic metal rod was 281 MPa, which was within the hyperelastic range and can be recycled. Performance experiments showed that the probe can work stably with the pH error no more than 0. 1. According to the life test, the probe can be used 60 480 times. When the measurement period was set to be 20 min, the probe can meet the service life of two years. In the rumen environment test, the average absolute deviation between manual measurement and system measurement was 0. 11 , and the maximum absolute deviation was 0. 25. The research result can provide technical means and reference for the development of rumen pH monitoring equipment. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 22
Main heading: Probes
Controlled terms: Crystallizers? - ?Fertilizers? - ?pH meters? - ?pH sensors? - ?Pistons
Uncontrolled terms: Cow? - ?Dairy cow? - ?Finite element analyse? - ?Hyper elastic? - ?Hyperelastic materials? - ?Intermittent measurements? - ?Metal rods? - ?pH Electrode? - ?Rumen ph electrode? - ?Valve components
Classification code: 101.8 Biosensing Technology? - ?608.1.1 Internal Combustion Engine Components? - ?802.1 Chemical Plants and Equipment? - ?802.3 Chemical Operations? - ?821.3 Agricultural Chemicals? - ?942.1.7 Special Purpose Instruments? - ?1502.1.1.3 Soil Pollution
Numerical data indexing: Pressure 2.81E+08Pa, Size 4.90E-02m, Size 5.00E-03m, Size 7.00E-02m, Size 9.00E-03m, Surface tension 2.84E+05N/m, Time 1.20E+03s
DOI: 10.6041/j.issn.1000-1298.2025.03.039
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
47. Multi-sensor Crop Phenotype Time Synchronous Acquisition Method
Accession number: 20251418174180
Title of translation: 多傳感器作物表型時(shí)間同步采集方法
Authors: Zhao, Yandong (1, 2); Liu, Haoyu (1, 2); Song, Runze (3); Sheng, Wenyi (3); Zhang, Man (3)
Author affiliation: (1) School of Technology, Beijing Forestry University, Beijing; 100083, China; (2) Beijing Laboratory of Urban and Rural Ecological Environment, Beijing; 100083, China; (3) School of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 58-66
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In the synchronous acquisition of crop multi-source information, integrating multi-source sensors to realize the synchronous acquisition of crop phenotype information has become the current trend of crop phenotype acquisition. Aiming at the key problem of dynamic synchronous acquisition in unstructured environment, in order to accurately and synchronously capture the multidimensional phenotypic feature data of crops at a specific time, a fixed multi-phenotypic trait imaging unit device was designed based on depth camera, binocular camera, thermal infrared camera and multispectral camera. The research on time synchronization acquisition of sensor data was carried out based on precision time protocol (PTP) , broke through the time synchronization parallel acquisition technology of multi-source heterogeneous sensors, and realized the time synchronization acquisition of multi-dimensional imaging characteristics of crop phenotypes in unstructured environment. For the time synchronization and stability of the system, a continuous 72 h test was carried out. The root mean square error of time synchronization error between the system clock of the timing board of each sensor ( slave clock ) and the 1 - PTP clock of the timing board (master clock) was less than 132 ns, and the long-term jitter was less than 286 ns. This result showed that the time synchronization error met the technical requirements. In order to evaluate the stability and reliability of the system, totally 100 experiments were carried out on crops with high intensity continuous sampling. The results showed that the system showed good stable performance in the whole experiment process, and can stably complete the continuous acquisition task. Under the condition of time synchronization, each sensor was synchronously triggered by the timing board, and the acquisition time error was controlled within 1 ms. The stability and dynamic performance of the system met the actual needs of agricultural production. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 32
Main heading: Temperature indicating cameras
Controlled terms: Electric clocks? - ?Fertilizers? - ?Forward error correction? - ?Ultrasonic cameras
Uncontrolled terms: Crop phenotyping? - ?Multi sensor? - ?Multi-Sources? - ?Phenotyping? - ?Precision time protocols? - ?Synchronization acquisitions? - ?Synchronous acquisition? - ?Time synchronization? - ?Time synchronization errors? - ?Unstructured environments
Classification code: 704.2 Electric Equipment? - ?742.2 Photographic and Video Equipment? - ?753.2 Ultrasonic Devices? - ?821.3 Agricultural Chemicals? - ?942.1.11 Temperature Measuring Instruments? - ?1103.3 Data Communication, Equipment and Techniques? - ?1502.1.1.3 Soil Pollution
Numerical data indexing: Time 1.00E-03s, Time 1.32E-07s, Time 2.592E+05s, Time 2.86E-07s
DOI: 10.6041/j.issn.1000-1298.2025.03.006
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
48. Design and Testing of Streamlined Largemouth Bass Recirculating Aquaculture System
Accession number: 20251418174113
Title of translation: 精簡式大口黑鱸循環(huán)水養(yǎng)殖系統(tǒng)設(shè)計(jì)與試驗(yàn)
Authors: Zhu, Ming (1, 2); Fan, Hao (1); Wan, Peng (1, 2); Qi, Yueying (1); Lei, Xiang (1); Wang, Rong (1)
Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key Laboratory of Aquaculture Facilities Engineering, Ministry of Agriculture and Rural Affairs, Wuhan; 430070, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 414-424
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to explore the feasibility and application development value of simple, stable and low-cost recirculating water aquaculture system, a freshwater fish recirculating water aquaculture system was constructed by optimizing and improving the water intake structure, oxygenation mode and streamlining the system composition, and a 90 d largemouth bass aquaculture trial was carried out to verify the system indexes. The results showed that at the start-up stage, the biofilm could be successfully hung in 18 d with a mixed culture in the mode of 2: 3 ratio of mature filter media to initial filter media; during the culture process, the mean values of temperature, dissolved oxygen concentration and pH were (27.60 ± 0. 30) °C , ( 10. 25 ± 0. 23 ) mg/L and 7. 10 ±0.31, respectively, and the mean values of ammonia nitrogen concentration and nitrite nitrogen concentration were ( 0. 27 ± 0. 14 ) mg/L and ( 0. 10 ± 0. 03) mg/L, nitrate nitrogen concentration range was between 7. 41 mg/L and 35. 89 mg/L, and water turbidity was (0. 25 ±0. 01 ) NTU ( nephelometric turbidity units) ; the average mass of largemouth bass was increased from (61. 25 ±3. 06) g to (256. 54 ±12. 84) g, and the maximal culture density reached 42. 54 kg/m , with a mean bait coefficient of 1. 16 and a survival rate of 98. 85% ~ 100% ; muscle texture characterization revealed that the muscle hardness of largemouth bass was increased moderately and elasticity was increased, which enhanced the taste of the fish; the running cost was about 21. 16 yuan/kg, which could yield a good economic return. The research result was conducive to the popularization of recirculating water aquaculture system and it can provide a reliable platform for freshwater fish scientific research. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 35
Main heading: Fish
Controlled terms: Ammonia? - ?Fisheries? - ?Oxygenation
Uncontrolled terms: Application development? - ?Aquaculture systems? - ?Filter mediums? - ?Freshwater fishes? - ?Largemouth bass? - ?Low-costs? - ?Mean values? - ?Nitrogen concentrations? - ?Recirculating aquaculture system? - ?Simple++
Classification code: 471.5 Sea as Source of Minerals and Food? - ?802.2 Chemical Reactions? - ?804.2 Inorganic Compounds? - ?822 Food Technology? - ?822.3 Food Products
Numerical data indexing: Linear density 5.40E+01kg/m, Mass density 4.10E-02kg/m3, Mass density 8.90E-02kg/m3, Percentage 1.00E+02%, Percentage 8.50E+01%
DOI: 10.6041/j.issn.1000-1298.2025.03.041
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
49. Design and Motion Control of Six-wheeled Multimodal Mobile Robot
Accession number: 20251418168194
Title of translation: 六輪多模式移動(dòng)機(jī)器人設(shè)計(jì)與運(yùn)動(dòng)控制
Authors: Zhu, Qunwei (1); Luo, Zirong (1); Jiang, Tao (1); Lu, Zhongyue (1); Xia, Minghai (1); Hong, Yang (1)
Author affiliation: (1) College of Intelligence Science and Technology, National University of Defense Technology, Changsha; 410005, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 523-530
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problems of large turning radius, inflexible motion and poor terrain adaptability of traditional six-wheeled robots, a six-wheeled multimodal mobile robot with articulated double rocker arm suspension and independent drive steering structure was proposed. The overall robot architecture consisted of an independently driven steering module, an integrated body, an articulated rocker suspension module and a control module, which can realize multimodal movement modes such as straight running, translation, in-situ steering, and turning around any point, and had the advantages of manoeuvrability, flexibility, and strong adaptability to the terrain. The multimodal motion mechanism and obstacle-crossing principle of the robot were analyzed, the multimodal kinematics model of the robot was established, and the relational equations of motion parameters under the multimodal motion of the robot were determined. The robot control system adopted a multi-task parallel mode of motor task, sensor task and remote control task, and a multimodal PID controller based on UCOS III parallel operating system, which improved the real-time, reliability and portability of the robot control system. The simulation environment and test prototype of a six-wheeled multimodal mobile robot were built, and the basic motion performance of the robot in multiple modes and the ability to pass through various complex terrains such as stairs, vertical obstacles and trenches were verified. The data of the robot’s motion attitude and motion speed under different terrains were tested, and the results of the robot’s multi-mode simulation motion and prototype test were analyzed to prove that the six-wheeled multimodal mobile robot structure had a better performance of passability and terrain adaptability than that of the traditional six-wheeled robot, and the study can provide a reference for the optimization and improvement of the structure of six-wheeled robots. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Mobile robots
Controlled terms: Agricultural robots? - ?All wheel drive vehicles? - ?Automobile steering equipment? - ?Automobile suspensions? - ?Industrial robots? - ?Invariance? - ?Multipurpose robots? - ?Robot Operating System? - ?Robotic arms? - ?Structural analysis ? - ?Structural dynamics? - ?Three term control systems? - ?Voltage stabilizing circuits
Uncontrolled terms: Double rocker suspension? - ?Multi-modal? - ?Multimodal motion control? - ?Robot control systems? - ?Rocker suspension? - ?Six wheel drive? - ?Six-wheel drive and steering? - ?UCOS III operating system? - ?Wheel steering? - ?Wheeled robot
Classification code: 101.6.1 Robotic Assistants? - ?408 Structural Design? - ?662.1 Automobiles? - ?662.3 Automobile Components and Materials? - ?713.5 Other Electronic Circuits? - ?731.1 Control Systems? - ?731.5 Robotics? - ?731.6 Robot Applications? - ?821.2 Agricultural Machinery and Equipment
DOI: 10.6041/j.issn.1000-1298.2025.03.052
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
50. Phenotypic Identification Method for Whole Growth Cycle of Hanging Watermelon
Accession number: 20251318143734
Title of translation: 考慮全生長周期的吊蔓西瓜表型識(shí)別方法研究
Authors: Liu, Ze (1, 2); Zhao, Zechuan (1, 3); Xu, Tong (1, 2); Liu, Tao (1); Zhu, Delan (1, 2); Ji, Zihan (1, 2)
Author affiliation: (1) College of Water Resources and Architectural Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Area, Ministry of Education, Northwest A&F University, Shaanxi, Yangling; 112100, China; (3) POWERCHINA Chengdu Engineering Co., Ltd., Chengdu; 610072, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 119-128
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In response to the current focus on single growth stage phenotype characteristics in most phenotype research, which makes it difficult to accurately monitor plant growth throughout whole growth cycle, a high-accuracy identification method for key phenotypic parameters of hanging watermelon throughout whole growth cycle was proposed by combining multiple deep learning methods and machine vision technologies. In the seedling stage, leaf area calculation model based on Leaf SAM and leaf count model based on Xception were established, and the experiments results showed that the R of the leaf area and leaf count models were 0. 96 and 0. 98, and the root mean square error (RMSE) was 2. 98 cm and 0. 14, respectively. During the elongation period, plant height measurement model based on YOLO v5 and binocular vision principles, as well as stem thickness calculation model based on OpenCV, were established separately, and the experiment results showed that the R of the plant height and stem thickness measurement model were 0.94 and 0.92, and the RMSE was 4. 18 cm and 0. 17 mm, respectively. In the fruiting and ripening stages, a fruit projection area calculation model based on UNet was established, and the experiment results showed that the R of the fruit projection model and the RMSE were 0. 99 and 9. 85 cm, respectively. The above results showed that the linear relationship between the calculated and manually measured values was significant, and the comprehensive error was low, which can effectively calculate the key phenotypic parameters throughout the whole growth cycle of hanging watermelon. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 25
Main heading: Fruits
Controlled terms: Binocular vision? - ?Seed? - ?Thickness measurement? - ?Velocity measurement
Uncontrolled terms: Calculation models? - ?Deep learning? - ?Growth cycle? - ?Hanging watermelon? - ?Identification method? - ?Machine-vision? - ?Model-based OPC? - ?Phenotype? - ?Root mean square errors? - ?Whole growth cycle
Classification code: 741.2 Vision? - ?821.5 Agricultural Products? - ?941.5 Mechanical Variables Measurements????? - ?942.1.7 Special Purpose Instruments
Numerical data indexing: Size 1.70E-02m, Size 1.80E-01m, Size 8.50E-01m, Size 9.80E-01m
DOI: 10.6041/j.issn.1000-1298.2025.03.012
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc.
51. Evaluation of Phenotypic Characteristics in Litchi Fruiting Stage Using Multi-source Evaluation Data
Accession number: 20251418161989
Title of translation: 融合多源評(píng)價(jià)數(shù)據(jù)的荔枝果期表型特征評(píng)估
Authors: Lu, Jianqiang (1, 2); Yuan, Jiajun (1); Yu, Chaoyan (3); Wang, Weixing (4); Niu, Hongyu (1); Lan, Yubin (1, 2); Tan, Yangyi (1)
Author affiliation: (1) College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou; 510640, China; (2) National Center for International Collahoration Research on Precision Agricultural Aviation Pesticides Spraying Technology (NPAAC), Guangzhou; 510642, China; (3) Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou; 510640, China; (4) Zhujiang College of South China Agricultural University, Guangzhou; 510900, China
Corresponding author: Lan, Yubin([email protected])
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 56
Issue: 3
Issue date: March 2025
Publication year: 2025
Pages: 91-100
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The applioation of artificial intelligence technology in litchi phenotype acquisition mainly focuses on object recognition, yield estimation, and picking localization. However, there is a notable lack of evaluation technology for assessing litchi growth quality throughout its entire fruiting stage. Aiming to integrate multi-source data indicators to perform a comprehensive assessment of litchi growth quality during the fruiting stage, thereby generating the evaluation profiles for litchi fruiting stages, based on the YOLO v7 network framework, an object recognition algorithm named LFS — YOLO was proposed. This algorithm enhanced recognition accuracy by mitigating errors and influences stemming from dynamic environmental backgrounds and by incorporating global attention mechanisms. Furthermore, the CIoU loss function was optimized through the inclusion of the angle between predicted regression vectors, which redefined and improved the angle penalty measure. This optimization reduced the overall degrees of freedom, thereby facilitating a more effective alignment of predicted bounding boxes with the nearest axis. By integrating multi-dimensional data, a quality evaluation function was established as the foundation for comprehensive evaluation. Experimental results indicated that the LFS — YOLO algorithm achieved a recognition accuracy of 89. 1%, a precision of 92. 3%, and a recall of 93. 0%. The evaluation profiles generated for die litchi fruiting stage illustrated various indicators that influence growth quality throughout this stage, providing valuable insights for the advancement of comprehensive evaluation teehnologies pertaining to litchi fruiting stage. ? 2025 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 24
Controlled terms: Regression analysis
Uncontrolled terms: Attention mechanisms? - ?Comprehensive evaluation? - ?Evaluation of phenotypic characteristic? - ?Global attention mechanism? - ?Litchi? - ?Meteorological data? - ?Multi-Sources? - ?Recognition accuracy? - ?Source evaluations? - ?YOLO v7
Classification code: 1202.2 Mathematical Statistics
Numerical data indexing: Percentage 0.00E00%, Percentage 1.00E00%, Percentage 3.00E+00%
DOI: 10.6041/j.issn.1000-1298.2025.03.009
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2025 Elsevier Inc
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