2021年10月第37卷第20期

2021年10月第37卷第20期

Accession number:20215211395665
Title:Effects of different soil surface mulching patterns on soil moisture and nutrient in dryland apple orchard in east Gansu Province
Title of translation:陇东旱地苹果园不同地面覆盖模式的水分与养分效应
Authors: (1); (1); (1); (1); (1); (1)
Author affiliation:(1) Institute of Fruit and Floriculture Research, Gansu Academy of Agricultural Science, Lanzhou; 730070, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:117-126
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:26
Main heading:Fruits
Controlled terms:Drought - Evapotranspiration - Forestry - Harvesting - Landforms - Moisture determination - Nutrients - Orchards - Rain - Sediments - Seepage - Soil moisture
Uncontrolled terms:Apple orchards - Cumulative amount - Fruit nutrient uptake - Gansu province - NO3--N - Nutrient uptake - Soil layer - Soil surface mulching - Soil surfaces - Yield
Classification code:443.3 Precipitation - 444 Water Resources - 481.1 Geology - 483 Soil Mechanics and Foundations - 483.1 Soils and Soil Mechanics - 821.0 Woodlands and Forestry - 821.3 Agricultural Methods - 821.4 Agricultural Products - 944.2 Moisture Measurements
Numerical data indexing:Percentage 9.20E+01% to 9.62E+01%, Size 0.00E00m to 1.00E00m, Size 0.00E00m to 3.00E+00m, Size 0.00E00m to 5.00E+00m, Size 1.00E00m to 2.00E+00m, Size 3.00E+00m to 4.00E+00m, Size 3.00E+00m to 5.00E+00m, Size 4.00E+00m to 5.00E+00m, Age 1.70E+01yr, Percentage 1.30E+01%, Percentage 1.31E+01%, Percentage 3.44E+01%, Percentage 3.68E+01%, Percentage 3.96E+01%, Percentage 8.30E+00%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395652
Title:Construction of the quality regulation system for provincial scale slope farmland based on quality evaluation
Title of translation:基于质量评价的省域尺度坡耕地质量调控体系构建
Authors: (1); (1); (1); (1); (1); (1)
Author affiliation:(1) College of Water Conservancy, Yunnan Agricultural University, Laboratory of Land Resources Utilization and Protection Engineering in Yunnan Province, Kunming; 650201, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:136-145
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Farms
Controlled terms:Biogeochemistry - Irrigation - Land use - Nitrogen - Organic compounds - pH - Phosphorus - Potassium - Quality control - Soil pollution - Soils - Water pollution - Water quality
Uncontrolled terms:Available phosphorus - Evaluation - Farmland qualities - Obstacle factor diagnose - pH value - Regulation system - Regulatory potential - Slope farmland - Sloping farmlands - Yunnan
Classification code:403 Urban and Regional Planning and Development - 445.2 Water Analysis - 453 Water Pollution - 481.2 Geochemistry - 483.1 Soils and Soil Mechanics - 549.1 Alkali Metals - 801.1 Chemistry, General - 801.2 Biochemistry - 804 Chemical Products Generally - 804.1 Organic Compounds - 821 Agricultural Equipment and Methods; Vegetation and Pest Control - 821.3 Agricultural Methods - 913.3 Quality Assurance and Control
Numerical data indexing:Linear density 1.31E-01kg/m, Mass 1.3781E-04kg, Mass 2.889E-02kg, Mass 3.244E-05kg, Percentage 7.333E+01%, Size 1.735E-01m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395533
Title:Research progress of the restitution coefficients of collision of particles in agricultural and food fields
Title of translation:农业和食品领域中颗粒碰撞恢复系数的研究进展
Authors: (1); (2); (1); (1); (1); (1)
Author affiliation:(1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) Tractor Research Institute, Weichai Lovol Heavy Industry, Weifang; 261000, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:313-322
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:80
Main heading:Kinematics
Controlled terms:Agricultural machinery - Agricultural products - Finite difference method - Kinetics - Surface roughness - Velocity
Uncontrolled terms:Collision types - Determination - Energy - Particle - Particles collisions - Responsive behaviour - Restitution coefficient - Restitution coefficient of collision - Theoretical modeling - Velocity of particles
Classification code:631.1 Fluid Flow, General - 821.1 Agricultural Machinery and Equipment - 821.4 Agricultural Products - 921.6 Numerical Methods - 931 Classical Physics; Quantum Theory; Relativity - 931.1 Mechanics - 931.2 Physical Properties of Gases, Liquids and Solids

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395531
Title:Impulsive force simulation of the rubber ball sieve-cleaning device for batch seed cleaners
Title of translation:批次式种子清选机橡胶球清筛装置激振力模拟分析
Authors: (1); (1); (1); (1); (2, 3); (1)
Author affiliation:(1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (3) Key Laboratory of Agro-Products Postharvest Handling, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:23-33
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Cleaning
Controlled terms:Equipment testing - Friction - Rubber - Sieves
Uncontrolled terms:Breeding materials - Cleaning devices - Forces measurements - Impulsive forces - Performance - Rubber balls - Seed cleaning - Sieve-cleaning device - Simulation - Vibration frequency
Classification code:802.3 Chemical Operations - 818.1 Natural Rubber
Numerical data indexing:Force 1.878E+01N, Force 1.90E+01N, Force 8.87E+00N, Force 9.00E+00N, Frequency 7.20E+00Hz, Percentage 1.00E+01%, Percentage 5.00E+00%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395667
Title:Quantity statistics of spruce under UAV aerial videos using YOLOv3 and SORT
Title of translation:利用无人机航拍视频结合YOLOv3模型和SORT算法统计云杉数量
Authors: (1, 2); (1, 2); (1, 2); (1); (3); (1, 4)
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) Department of Horticultural Science, Texas A&M University, College Station; TX; 77843, United States; (4) Key Laboratory of State Forestry Administration for Forestry Equipment and Automation, Beijing; 100083, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:81-89
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:42
Main heading:Unmanned aerial vehicles (UAV)
Controlled terms:Antennas - Data acquisition - Error statistics - Mean square error - Statistical tests
Uncontrolled terms:Aerial video - Frame-rate - Key indicator - Mean absolute error - Performance - Quantity statistic - Root mean square errors - SORT - Spruce - YOLOv3
Classification code:652.1 Aircraft, General - 723.2 Data Processing and Image Processing - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 9.23E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395507
Title:Disinfection efficacy of slightly acidic electrolyzed water sprayed on Salmonella on the chicken manure contaminated eggs
Title of translation:微酸性电解水对受鸡粪液污染鸡蛋表面沙门氏菌的喷雾消毒效果
Authors: (1); (1); (1); (1)
Author affiliation:(1) Nanchang Key Laboratory of Animal Health and Safety, College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang; 330045, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:333-338
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:27
Main heading:Salmonella
Controlled terms:Chlorine - Disinfectants - Disinfection - Efficiency - Fertilizers - Fumigation - Linear regression - Manures - Ozone
Uncontrolled terms:% reductions - Chicken manure - Cleaning and disinfections - Cleaning treatment - Disinfection treatments - Egg - Electrolytics - Salmonella enteritidis - Slightly acidic electrolytic water - Slightly acidic electrolyzed waters
Classification code:461.9 Biology - 803 Chemical Agents and Basic Industrial Chemicals - 804 Chemical Products Generally - 821.2 Agricultural Chemicals - 821.5 Agricultural Wastes - 913.1 Production Engineering - 922.2 Mathematical Statistics
Numerical data indexing:Mass density 2.50E-02kg/m3, Mass density 3.50E-02kg/m3, Percentage 1.00E+02%, Time 1.80E+01s, Time 2.40E+01s

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395595
Title:Suitable particle size range of sand filter layers based on fractal dimension characteristics
Title of translation:基于分形维数特征的砂滤层适宜粒径范围
Authors: (1, 2); (1); (2); (1); (1)
Author affiliation:(1) Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences/Key Laboratory of Water-Saving Agriculture of Henan Province, Xinxiang; 453002, China; (2) School of Civil and Architectural Engineering, Anyang Institute of Technology, Anyang; 455000, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:162-168
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:32
Main heading:Particle size
Controlled terms:Computerized tomography - Erosion - Fractal dimension - Higher order statistics - Normal distribution - Particle size analysis - Porosity - Quartz - Rivers - Sand - Sediments
Uncontrolled terms:Box-counting - Box-counting fractal dimension - Filtration performance - Images processing - Particles sizes - Quartz sand - Quartz sand filter - Sand filter - Surface filtration
Classification code:482.2 Minerals - 483 Soil Mechanics and Foundations - 483.1 Soils and Soil Mechanics - 723.5 Computer Applications - 921 Mathematics - 922.1 Probability Theory - 922.2 Mathematical Statistics - 931.2 Physical Properties of Gases, Liquids and Solids - 951 Materials Science
Numerical data indexing:Percentage 6.20E-01%, Percentage 6.70E-01%, Percentage 8.00E-01%, Percentage 8.10E-01%, Percentage 9.10E-01%, Percentage 9.30E-01%, Size 1.00E-04m, Size 1.40E-03m to 1.70E-03m, Size 5.03E-04m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395642
Title:Spatial distribution and compensation strategy of land fallow based on quality-risk in arid areas
Title of translation:基于"质量-风险"的干旱区休耕空间布局及补偿策略
Authors: (1); (2); (3); (1); (4); (5)
Author affiliation:(1) College of Public Administration, Nanjing Agricultural University, Nanjing; 210095, China; (2) Shanghai Academy of Agricultural Sciences, Institute of Agricultural Science and Technology Information, Shanghai; 201403, China; (3) College of Economics and Management, Northwest A&F University, Yangling; 712100, China; (4) School of Business, Anhui University of Technology, Maanshan; 243002, China; (5) College of Management, Xinjiang Agricultural University, Urumqi; 830052, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:266-276
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:37
Main heading:Land use
Controlled terms:Climate models - Cultivation - Ecology - Efficiency - Indicators (chemical) - Quality control - Risk perception - Rivers - Soils - Spatial distribution - Watersheds
Uncontrolled terms:Cultivated land qualities - Cultivated lands - Ecological compensation - Farmland qualities - Kaidu-kongque river basin - Land degradation - Land degradation risk - Land fallow - River basins - Spatial layout
Classification code:403 Urban and Regional Planning and Development - 405.3 Surveying - 443 Meteorology - 444.1 Surface Water - 454.3 Ecology and Ecosystems - 483.1 Soils and Soil Mechanics - 801 Chemistry - 804 Chemical Products Generally - 821.3 Agricultural Methods - 902.1 Engineering Graphics - 913.1 Production Engineering - 913.3 Quality Assurance and Control - 914.1 Accidents and Accident Prevention - 921 Mathematics

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395537
Title:Influence of circulation distribution on the optimization results of mixed-flow pump based on inverse design
Title of translation:环量分布对基于反问题设计的混流泵优化结果的影响
Authors: (1); (1); (1); (1); (1)
Author affiliation:(1) National Research Center of Pumps, Jiangsu University, Zhenjiang; 212023, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:44-52
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Vortex flow
Controlled terms:Computational fluid dynamics - Design - Genetic algorithms - Impellers - Inverse problems - Pumps - Radial basis function networks - Sensitivity analysis
Uncontrolled terms:Baseline models - Circulation distribution - Hydrodynamic parameters - Impeller outlet - Inverse designs - Local sensitivity analysis - Mixed flow pump - Mixed-flow pump impellers - Optimisations - Optimization design
Classification code:601.2 Machine Components - 618.2 Pumps - 631.1 Fluid Flow, General - 723.5 Computer Applications - 921 Mathematics - 931.1 Mechanics
Numerical data indexing:Percentage 1.00E+01%, Percentage 3.00E+00%, Percentage 8.414E+01%, Percentage 8.508E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395499
Title:Quantifying the water sources of Camellia oleifera during fruit growth peak period using hydrogen and oxygen isotopes
Title of translation:基于氢氧同位素的油茶果实生长高峰期水分来源量化
Authors: (1); (1); (1); (1); (1); (1); (1)
Author affiliation:(1) College of Water Resources & Civil Engineering, Hunan Agricultural University, Changsha; 410128, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:154-161
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:35
Main heading:Soil moisture
Controlled terms:Forestry - Fruits - Isotopes - Plants (botany) - Soil testing - Water absorption
Uncontrolled terms:%moisture - Camellia oleifera - Fruit growth - Fruit growth peak of camellia oleifera - MixSIAR model - Peak period - Soil layer - Soil water - Water source - Water use
Classification code:483.1 Soils and Soil Mechanics - 802.3 Chemical Operations - 821.0 Woodlands and Forestry - 821.4 Agricultural Products
Numerical data indexing:Age 3.00E+00yr to 5.00E+00yr, Percentage 1.20E+01%, Percentage 1.90E+01%, Percentage 2.05E+01%, Percentage 2.82E+01%, Percentage 5.13E+01%, Percentage 8.00E+00%, Size 0.00E00m to 1.00E00m, Size 0.00E00m to 3.00E-01m, Size 1.00E00m, Size 5.87E-02m, Size 6.00E-01m to 1.00E00m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395618
Title:Effect of magnetization of irrigation water on the clogging of drip irrigation emitters with integrated water and fertilizer
Title of translation:灌溉水磁化处理对水肥一体化滴灌滴头堵塞的影响
Authors: (1, 2); (1, 2); (1, 2); (1, 3)
Author affiliation:(1) The Key Laboratory of Agricultural Soil and Water Engineering in Arid Areas, Northwest A&F University, Yangling; 712100, China; (2) College of Water Conservancy and Civil Engineering, Northwest A&F University, Yangling; 712100, China; (3) Institute of Soil and Water Conservation, MWR & CAS, Yangling; 712100, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:127-135
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:35
Main heading:Irrigation
Controlled terms:Fertilizers - Magnetization - Metabolism - Mixtures - Sediments - Sulfur compounds - Urea
Uncontrolled terms:Compound fertilizer - Drip irrigation - Dripper clogging - Integration of water and fertilizers - Irrigation waters - Magnetization intensities - Magnetization treatment - Mitigation effects - Particles sizes - Yellow river
Classification code:483 Soil Mechanics and Foundations - 701.2 Magnetism: Basic Concepts and Phenomena - 804 Chemical Products Generally - 804.1 Organic Compounds - 821.2 Agricultural Chemicals - 821.3 Agricultural Methods
Numerical data indexing:Magnetic flux density 2.00E-01T, Magnetic flux density 4.00E-01T, Magnetic flux density 6.00E-01T, Mass density 3.00E+00kg/m3, Percentage 1.036E+01%, Percentage 1.117E+01%, Percentage 1.787E+01%, Percentage 2.00E+00%, Percentage 2.575E+01%, Percentage 2.75E+01%, Percentage 4.61E+00%, Percentage 5.26E+00%, Percentage 5.33E+00%, Percentage 5.536E+01%, Percentage 6.877E+01%, Percentage 7.50E+01%, Size 3.00E-05m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395691
Title:Effects of different extraction methods on phenolic compounds and antioxidant activity in Hemerocallis flower
Title of translation:不同提取方式对萱草花中酚类物质及抗氧化活性的影响
Authors: (1); (1); (1); (1); (1); (1); (1)
Author affiliation:(1) Faculty of Fragrance, Fragrance and Cosmetics, Shanghai Institute of Technology, Shanghai; 201418, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:303-312
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:38
Main heading:Extraction
Controlled terms:Antioxidants - Citrus fruits - Fermentation - Flavonoids - Free radicals - High performance liquid chromatography - Ketones - Phenols - Plants (botany) - Pyrene - Ultrasonics
Uncontrolled terms:Antioxidant activities - Free fraction - Free phenol - Hemerocallis - Hemerocallis flower - Phenolic antioxidant - Phenolic compounds - Ultrasonic extraction - Ultrasonic processing - Vitamin C
Classification code:753.1 Ultrasonic Waves - 802.3 Chemical Operations - 803 Chemical Agents and Basic Industrial Chemicals - 804 Chemical Products Generally - 804.1 Organic Compounds - 804.2 Inorganic Compounds - 821.4 Agricultural Products
Numerical data indexing:Percentage 7.50E+01%, null 2.488E+01null, null 2.838E+01null, null 3.182E+01null, null 3.512E+01null, null 3.557E+01null, null 3.56E+01null, null 3.824E+01null, null 3.974E+01null, null 4.053E+01null, null 4.149E+01null, null 4.432E+01null, null 4.74E+01null, null 4.82E+01null

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395589
Title:Maize straw motion law in subsoiling operation using discrete element method
Title of translation:基于离散元法的深松作业玉米秸秆运动规律
Authors: (1); (1); (1); (1); (1); (1)
Author affiliation:(1) School of Engineering, Northeast Agricultural University, Harbin; 150030, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:53-62
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:32
Main heading:Finite difference method
Controlled terms:Adhesives - Friction - High speed cameras - Machine tools - Rigid structures
Uncontrolled terms:Discrete elements method - Lateral displacements - Maize straw - Motion law - Rigid body - Simulation - Simulation data - Straw movement - Subsoiling - Test
Classification code:408 Structural Design - 603.1 Machine Tools, General - 742.2 Photographic Equipment - 921.6 Numerical Methods
Numerical data indexing:Percentage 1.60E-01% to 1.106E+01%, Percentage 1.60E-01% to 1.231E+01%, Percentage 3.60E-01% to 9.67E+00%, Percentage 5.60E-01% to 1.011E+01%, Size 6.00E-02m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395549
Title:Monitoring of winter wheat growth under UAV using variation coefficient method and optimized neural network
Title of translation:变异系数法结合优化神经网络的无人机冬小麦长势监测
Authors: (1); (1); (2); (1); (3); (1); (3)
Author affiliation:(1) School of Spatial Informatics and Geomatics Engineering, Anhui University of Science and Technology, Huainan; 232001, China; (2) Huaibei Mining (Group) Co. Ltd, Huaibei; 235001, China; (3) School of Earth and Environment, Anhui University of Science and Technology, Huainan; 232001, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:71-80
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:47
Main heading:Unmanned aerial vehicles (UAV)
Controlled terms:Antennas - Backpropagation - Chlorophyll - Crops - Decision trees - Ecology - Errors - Forestry - Genetic algorithms - Infrared devices - Least squares approximations - Maximum likelihood - Mean square error - Neural networks - Remote sensing - Torsional stress - Vegetation
Uncontrolled terms:Back-propagation neural networks - Coefficient of variation method - Coefficients of variations - Comprehensive growth monitoring indicator - Growth monitoring - Monitoring indicators - Remote-sensing - Variation method - Vegetation index - Winter wheat
Classification code:454.3 Ecology and Ecosystems - 652.1 Aircraft, General - 723.4 Artificial Intelligence - 804.1 Organic Compounds - 821.0 Woodlands and Forestry - 821.4 Agricultural Products - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 921.6 Numerical Methods - 922.1 Probability Theory - 922.2 Mathematical Statistics - 961 Systems Science
Numerical data indexing:Percentage 2.222E+01%, Percentage 2.679E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395556
Title:Acoustic characteristics of the feeding pellets for Micropterus salmoides in circulating aquaculture
Title of translation:循环水养殖大口黑鲈摄食颗粒饲料的声学特征
Authors: (1, 2); (2); (1, 2); (2); (2)
Author affiliation:(1) College of Fisheries and Life Science, Shanghai Ocean University, Shanghai; 201306, China; (2) Fishery Machinery and Instrument Research Institute, Chinese Academy of Fishery Sciences, Shanghai; 200092, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:219-225
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:27
Main heading:Time domain analysis
Controlled terms:Acoustic waves - Aquaculture - Audio acoustics - Biomolecules - Fast Fourier transforms - Feeding - Frequency domain analysis - Meats - Video recording
Uncontrolled terms:Acoustic signals - Characteristics parameters - Feature parameters - Feeding activities - Feeding behavior - Feeding system - Micropteri salmoide - Micropterus - Passive acoustics - Sound signal
Classification code:461.9 Biology - 691.2 Materials Handling Methods - 716.4 Television Systems and Equipment - 751.1 Acoustic Waves - 801.2 Biochemistry - 821.3 Agricultural Methods - 822.3 Food Products - 921 Mathematics - 921.3 Mathematical Transformations
Numerical data indexing:Frequency 4.20E+03Hz to 7.40E+03Hz

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395532
Title:Research progress and prospect of pesticide droplet deposition characteristics
Title of translation:农药雾滴沉积特性研究进展与展望
Authors: (1); (1); (1); (2); (1); (1)
Author affiliation:(1) School of Technology, Beijing Forestry University, Beijing; 100083, China; (2) College of Engineering, China Agricultural University, Beijing; 100083, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:1-14
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:151
Main heading:Deposition
Controlled terms:Drops - Image processing - Pesticides - Plants (botany) - Wetting
Uncontrolled terms:Deposition behaviours - Drift - Droplet deposition - Droplet group - Interface behavior - Pesticide deposition - Pesticide droplets - Single droplet - Spray field - Target surface
Classification code:723.2 Data Processing and Image Processing - 802.3 Chemical Operations - 803 Chemical Agents and Basic Industrial Chemicals

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395501
Title:Monitoring of sugar beet growth using canopy spectrum and structural characteristics with UAV images
Title of translation:基于无人机影像的冠层光谱和结构特征监测甜菜长势
Authors: (1); (1); (1); (2); (3); (1); (1)
Author affiliation:(1) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China; (2) Institute of Biotechnology, Inner Mongolia Academy of Science and Technology, Hohhot; 010010, China; (3) College of Agriculture, Inner Mongolia Agricultural University, Hohhot; 010019, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:90-98
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:37
Main heading:Regression analysis
Controlled terms:Antennas - Costs - Crops - Decision trees - Forecasting - Least squares approximations - Mean square error - Sugar beets - Throughput - Tubes (components) - Unmanned aerial vehicles (UAV)
Uncontrolled terms:Canopy characteristics - Fresh weight - Partial least square regression - Partial least squares regression models - Plant analysis - Random forest regression - Random forests - Root tubers - Structural characteristics - Sugar content
Classification code:619.1 Pipe, Piping and Pipelines - 652.1 Aircraft, General - 821.4 Agricultural Products - 911 Cost and Value Engineering; Industrial Economics - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 921.6 Numerical Methods - 922.2 Mathematical Statistics - 961 Systems Science
Numerical data indexing:Percentage 7.30E+00% to 1.90E+01%, Percentage 7.60E+00% to 1.70E+01%, Percentage 7.60E+00% to 1.90E+01%, Percentage 8.80E+00% to 2.00E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395542
Title:Monitoring of maize phenotypic traits using super-resolution reconstruction and multimodal data fusion
Title of translation:基于超分辨率重建和多模态数据融合的玉米表型性状监测
Authors: (1); (1); (1); (1); (1)
Author affiliation:(1) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:169-178
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:32
Main heading:Unmanned aerial vehicles (UAV)
Controlled terms:Antennas - Errors - Image acquisition - Image compression - Image enhancement - Image quality - Image reconstruction - Image resolution - Mean square error - Plants (botany) - Remote sensing - Signal to noise ratio - Wavelet transforms
Uncontrolled terms:Aboveground biomass - High-throughput phenotyping - Maize - Multimodal data fusion - Phenotypic traits - Point-clouds - Reconstructed image - Remote-sensing - Root mean square errors - Super-resolution reconstruction
Classification code:652.1 Aircraft, General - 716.1 Information Theory and Signal Processing - 723 Computer Software, Data Handling and Applications - 921.3 Mathematical Transformations - 922.2 Mathematical Statistics
Numerical data indexing:Mass 1.90E-01kg, Percentage 6.40E+00%, Size 3.00E+01m, Size 3.90E-02m, Size 6.00E+01m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395647
Title:Voice recognition of abnormal state of pigs based on improved CNN
Title of translation:采用改进CNN对生猪异常状态声音识别
Authors: (1, 2); (1); (1); (1); (3)
Author affiliation:(1) School of Artificial Intelligence, Hebei University of Technology, Tianjin; 300130, China; (2) Engineering Research Center of Intelligent Rehabilitation Device and Detection Technology, Ministry of Education, Tianjin; 300130, China; (3) Tianjin Mojieke Intelligent Technology Co., Ltd., Tianjin; 300130, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:187-193
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:26
Main heading:Convolution
Controlled terms:Acoustic noise - Audio acoustics - Cloud computing - Complex networks - Convolutional neural networks - Fast Fourier transforms - Mammals - Spectrographs - Transmission control protocol
Uncontrolled terms:Abnormal noise - Abnormal sounds - Cloud servers - Convolutional block attention module - Convolutional neural network - Efficient channel attention network, - Efficient channels - Mel frequencies - Spectrograms - Squeeze and excitation network
Classification code:716.1 Information Theory and Signal Processing - 722 Computer Systems and Equipment - 722.3 Data Communication, Equipment and Techniques - 722.4 Digital Computers and Systems - 723 Computer Software, Data Handling and Applications - 741.3 Optical Devices and Systems - 751.1 Acoustic Waves - 751.4 Acoustic Noise - 921.3 Mathematical Transformations
Numerical data indexing:Frequency 3.20E+04Hz, Percentage 1.00E+02%, Percentage 9.446E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395514
Title:Effects of LED light on the ripening regulation of green mature banana during storage and transportation
Title of translation:LED光照对青熟香蕉贮运中后熟调控的影响
Authors: (1, 2); (1, 2, 3); (1, 2, 3); (1, 2); (1, 2); (1, 2)
Author affiliation:(1) Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (2) Key Laboratory of Agro-Products Postharvest Handling, Ministry of Agriculture and Rural Affairs, Beijing; 100121, China; (3) College of Life Science and Food Engineering, Hebei University of Engineering, Handan; 056038, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:295-302
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:44
Main heading:Citrus fruits
Controlled terms:Cellulose - Color - Colorimetry - Ethylene - Light emitting diodes - Starch - Sugars
Uncontrolled terms:Green light - Green mature banana - LED lighting - LED lights - Preservation - Red light - Ripening - Ripening regulation - Storage and transportations - Sugar content
Classification code:714.2 Semiconductor Devices and Integrated Circuits - 741.1 Light/Optics - 804.1 Organic Compounds - 811.3 Cellulose, Lignin and Derivatives - 815.1.1 Organic Polymers - 821.4 Agricultural Products - 941.4 Optical Variables Measurements
Numerical data indexing:Age 1.096E-02yr, Age 2.192E-02yr, Age 5.48E-03yr, Force 1.00E-01N, Force 2.50E+00N, Percentage 2.397E+01%, Percentage 2.42E+01%, Percentage 5.171E+01%, Size 4.00E-07m to 4.40E-07m, Size 4.40E-07m to 5.05E-07m, Size 5.05E-07m to 5.65E-07m, Size 5.65E-07m to 6.05E-07m, Size 6.05E-07m to 6.40E-07m, Size 6.40E-07m to 7.00E-07m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395568
Title:Lodging resistance prediction of maize varieties based on support vector machine and ReliefF algorithm
Title of translation:基于支持向量机和ReliefF算法的玉米品种抗倒伏预测
Authors: (1, 2); (1, 2); (1, 2); (1, 2); (1, 2); (1, 2); (1, 2); (1, 2)
Author affiliation:(1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Soil-Machine-Plant System Technology of Ministry of Agriculture, Beijing; 100083, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:226-233
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Support vector machines
Controlled terms:Classification (of information) - Feature extraction - Grain (agricultural product) - Hyperspectral imaging - K-means clustering - Principal component analysis - Spectroscopy - Vegetation
Uncontrolled terms:Lodging resistance - Lodging resistant - Maize - Principal-component analysis - ReliefF - Support vector machine models - Support vectors machine - Test sets - Training sets - Variety
Classification code:716.1 Information Theory and Signal Processing - 723 Computer Software, Data Handling and Applications - 746 Imaging Techniques - 821.4 Agricultural Products - 903.1 Information Sources and Analysis - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 8.417E+01%, Percentage 8.50E+01%, Percentage 8.583E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395511
Title:Design of the blockchain multi-chain traceability supervision model for coarse cereal supply chain
Title of translation:杂粮供应链区块链多链追溯监管模型设计
Authors: (1, 2); (1, 2); (1, 2); (1, 2); (1, 2)
Author affiliation:(1) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (2) National Engineering Laboratory for Quality and Safety Traceability Technology and Application of Agricultural Products, Beijing; 100097, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:323-332
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Supply chains
Controlled terms:Agricultural products - Authentication - Cryptography - Cultivation - Digital storage - Distributed computer systems - Distributed ledger - Food safety - Heavy metals - Internet of things - Life cycle - Network architecture - Network protocols - Peer to peer networks - Radio frequency identification (RFID) - Smart contract - Terminology - Wireless sensor networks
Uncontrolled terms:Block-chain - Data regulatory - Hyperledg fabric - Identity authentication - Multi-chain - Quality and safeties - Real- time - Regulatory authorities - Traceability - Traceability systems
Classification code:461.6 Medicine and Pharmacology - 531 Metallurgy and Metallography - 716.3 Radio Systems and Equipment - 722 Computer Systems and Equipment - 722.1 Data Storage, Equipment and Techniques - 722.3 Data Communication, Equipment and Techniques - 722.4 Digital Computers and Systems - 723 Computer Software, Data Handling and Applications - 731.1 Control Systems - 821.3 Agricultural Methods - 821.4 Agricultural Products - 822.3 Food Products - 902.3 Legal Aspects - 911.3 Inventory Control - 912 Industrial Engineering and Management - 913 Production Planning and Control; Manufacturing
Numerical data indexing:Percentage 8.239E+01%, Percentage 8.253E+01%, Time 4.15E-01s, Time 8.71E-01s

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395546
Title:Calibration of the discrete element parameters for the soil model of cotton field after plowing in Xinjiang of China
Title of translation:新疆棉田耕后土壤模型离散元参数标定
Authors: (1, 2); (1, 2); (1, 2); (1, 2); (1, 2); (1, 2)
Author affiliation:(1) Mechanical Equipment Research Institute, Xinjiang Academy of Land Reclamation Sciences, Shihezi; 832000, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832000, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:63-70
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Soils
Controlled terms:Agricultural machinery - Calibration - Compressive strength - Crops - Finite difference method - Optimization - Recovery - Restoration - Software testing - Soil mechanics - Soil testing - Trenching
Uncontrolled terms:Angle of repose - Contact parameters - Discrete elements - Discrete elements method - Fertilisation - Parameters calibrations - Sliding friction - Soil-soil - Stratified fertilization - Trenching and mulching
Classification code:483.1 Soils and Soil Mechanics - 619.1 Pipe, Piping and Pipelines - 723.5 Computer Applications - 821.1 Agricultural Machinery and Equipment - 821.4 Agricultural Products - 921.5 Optimization Techniques - 921.6 Numerical Methods
Numerical data indexing:Percentage 1.02E+01%, Percentage 1.70E+00%, Percentage 2.50E+00%, Percentage 7.04E+00%, Percentage 7.95E+00%, Size 7.00E+03m

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395515
Title:Construction and empirical analysis of the evaluation index system for the water-saving level of large-sized irrigation districts
Title of translation:大型灌区节水水平评价指标体系构建与实证
Authors: (1, 2); (1, 2); (3); (3); (1, 2); (1, 4)
Author affiliation:(1) Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang; 453002, China; (2) Graduate School of Chinese Academy of Agricultural Sciences, Beijing; 100081, China; (3) China Irrigation and Drainage Development Center, Beijing; 100054, China; (4) Key Laboratory of Watersaving Irrigation Engineering, Ministry of Agriculture and Rural Affairs, Xinxiang; 453002, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:99-107
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:43
Main heading:Irrigation
Controlled terms:Drainage - Ecology - Human resource management - Hydraulic structures - Information management - Irrigation canals - Water conservation - Water management - Water supply
Uncontrolled terms:Index optimization - Indices systems - Irrigation districts - Large-sized - Large-sized irrigation district - Optimisations - Water consumption - Water-saving - Water-saving level - Waters resources
Classification code:444 Water Resources - 446.1 Water Supply Systems - 454.3 Ecology and Ecosystems - 821.3 Agricultural Methods - 912.2 Management - 912.4 Personnel
Numerical data indexing:Age 1.00E+01yr, Percentage 3.286E+01%, Percentage 3.50E+01%, Percentage 8.642E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395562
Title:Navigation path recognition between crop ridges based on semantic segmentation
Title of translation:基于语义分割的作物垄间导航路径识别
Authors: (1, 2); (1, 2); (1, 2); (3); (1, 2); (1, 2); (1, 4, 5); (1, 2)
Author affiliation:(1) College of Biosystem Engineering and Food Science, Zhejiang University, Hangzhou; 310058, China; (2) Key Laboratory of Agricultural Products Processing Equipment, Ministry of Agriculture and Rural Affairs, Hangzhou; 310058, China; (3) School of Mathematical Sciences, Zhejiang University, Hangzhou; 310058, China; (4) School of Mechanical and Electrical Engineering, Zaozhuang University, Zaozhuang; 277101, China; (5) Xinduo Group Co., Ltd., Yongkang; 321300, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:179-186
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Crops
Controlled terms:Cotton - Deep learning - E-learning - Navigation - Semantic Segmentation - Semantics
Uncontrolled terms:Deep learning - Images processing - Least squares regression - Navigation lines - Navigation paths - Path recognition - Real time performance - Semantic segmentation - Transfer learning - Yaw angles
Classification code:461.4 Ergonomics and Human Factors Engineering - 723.4 Artificial Intelligence - 821.4 Agricultural Products
Numerical data indexing:Percentage 6.24E+00%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395590
Title:Optimizing irrigation and nitrogen management for potato production under multi-objective production conditions
Title of translation:不同生产目标条件的马铃薯水氮管理优化
Authors: (1); (1); (2); (1); (1); (1); (1)
Author affiliation:(1) Engineering Technology Research Center, Geographic Information Development and Application of Hebei, Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang; 050011, China; (2) College of Resources and Environmental Sciences, China Agricultural University, Beijing; 100193, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:108-116
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:34
Main heading:Irrigation
Controlled terms:Crops - Cultivation - Economic and social effects - Economics - Efficiency - Nitrogen fertilizers - Seed - Soil moisture - Water supply
Uncontrolled terms:'Dry' [ - Agro-pastoral ecotones - Crop production - Economic benefits - Fertilisation - Income - N fertilizers - Optimal combination - Water use efficiency - Yield
Classification code:446.1 Water Supply Systems - 483.1 Soils and Soil Mechanics - 804 Chemical Products Generally - 821.2 Agricultural Chemicals - 821.3 Agricultural Methods - 821.4 Agricultural Products - 913.1 Production Engineering - 971 Social Sciences
Numerical data indexing:Mass 9.00E+01kg, Mass 9.00E+02kg, Mass 9.22E+01kg, Size 1.00E-02m to 1.00E-01m, Size 1.00E-02m, Size 1.00E00m, Size 1.16E-01m, Size 5.08E-02m, Size 5.12E-01m, Size 8.70E-02m, Mass 2.10E+02kg, Mass 3.00E+01kg to 2.10E+02kg, Mass 3.00E+01kg, Mass 3.00E+01kg to 9.00E+01kg, Mass 5.00E+02kg, Mass 6.00E+01kg to 1.20E+02kg, Mass 6.00E+01kg

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395555
Title:Quality inspection of Spathiphyllum plug seedlings based on the side view images of the seedling stem under the leaves
Title of translation:基于叶片下苗茎侧视图像的白掌穴盘苗品质检测
Authors: (1); (2); (3); (4); (4); (3); (3, 5)
Author affiliation:(1) College of Electronic Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) College of Electromechanical Engineering, China University of Petroleum(East China), Qingdao; 266580, China; (3) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (4) Guangzhou Sky Mechanical & Electrical Technology Co., Ltd., Guangzhou; 510642, China; (5) Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou; 510642, China
Corresponding authors:;
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:194-201
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:33
Main heading:Computer vision
Controlled terms:Agricultural machinery - Cameras - Efficiency - Fruits - Inspection - Seed - Vegetables - Wages
Uncontrolled terms:Critical value - Leaf covering - Machine-vision - Plug seedling - Projection area - Protected horticulture - Quality detection - Quality inspection - STEM images - Top views
Classification code:723.5 Computer Applications - 741.2 Vision - 742.2 Photographic Equipment - 821.1 Agricultural Machinery and Equipment - 821.4 Agricultural Products - 912.4 Personnel - 913.1 Production Engineering
Numerical data indexing:Percentage 8.50E+01%, Percentage 9.792E+01%, Size 1.00E-02m, Velocity 4.50E-02m/s, Velocity 6.00E-02m/s

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395631
Title:Dynamic reconfiguration method of rural active distribution network based on regional division
Title of translation:基于区域划分的农村有源配电网动态重构方法
Authors: (1); (1); (1); (1); (1)
Author affiliation:(1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:248-255
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Dynamic models
Controlled terms:Genetic algorithms - Graph theory - Planning - Rural areas - Wind power
Uncontrolled terms:Active distributions - Dynamic re-configuration - Energy - Network dynamic reconfiguration - Network dynamics - Network structures - Network-based - Regional divisions - Rural active distribution network - Rural distribution networks
Classification code:615.8 Wind Power (Before 1993, use code 611 ) - 912.2 Management - 921 Mathematics - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory
Numerical data indexing:Percentage 1.609E+01%, Percentage 5.532E+01%, Percentage 7.141E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395565
Title:Development of potato seed-metering state monitoring system based on space capacitance sensors
Title of translation:基于空间电容传感器的马铃薯排种状态监测系统研制
Authors: (1); (1); (1); (1); (1); (1); (1); (2)
Author affiliation:(1) College of Mechatronic Engineering, Gansu Agricultural University, Lanzhou; 730070, China; (2) Gasu Polytechnic College of Animal Husbandry & Engineering, Wuwei; 733006, China
Corresponding author:
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:34-43
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:31
Main heading:Capacitance
Controlled terms:Monitoring - Plates (structural components) - Regression analysis - Seed - Testing
Uncontrolled terms:Capacitance sensors - Capacitor plates - Monitoring system - Potato - Seed metering - Seed metering status - Simple structures - Space capacitance - State monitoring - Temperature and humidities
Classification code:408.2 Structural Members and Shapes - 701.1 Electricity: Basic Concepts and Phenomena - 821.4 Agricultural Products - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 1.00E00%, Percentage 2.33E+00%, Percentage 2.78E+00%, Percentage 3.00E+00%, Percentage 5.00E+00% to 7.00E+00%, Percentage 5.00E+01%

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395567
Title:Application of BIM technology in Venlo greenhouse design
Title of translation:BIM技术在Venlo温室设计中的应用分析
Authors: (1, 2); (2, 3); (2, 3); (2, 3); (2, 3); (2, 3)
Author affiliation:(1) College of Landscape Architecture and Art, Northwest A&F University, Yangling; 712100, China; (2) Key Laboratory of Northwest Facilities Horticultural Engineering, Ministry of Agriculture and Rural Affairs, Yangling; 712100, China; (3) College of Horticulture, Northwest A&F University, Yangling; 712100, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:256-265
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract"></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:48
Main heading:Architectural design
Controlled terms:Greenhouses - Information theory - Structural design - Topography - Visualization
Uncontrolled terms:'current - Building information modeling - Building Information Modelling - Design-process - Greenhouse design - Model creation - Modeling technology - Modern agricultures - Revit - Schematic design
Classification code:402 Buildings and Towers - 408.1 Structural Design, General - 716.1 Information Theory and Signal Processing - 821.6 Farm Buildings and Other Structures - 951 Materials Science

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395567
Title:Application of BIM technology in Venlo greenhouse design
Title of translation:BIM技术在Venlo温室设计中的应用分析
Authors:Zhang, Yong (1, 2); Chen, Yu (2, 3); Zhu, Xiaohong (2, 3); Xu, Lianghe (2, 3); Zhang, Kexin (2, 3); Zou, Zhirong (2, 3)
Author affiliation:(1) College of Landscape Architecture and Art, Northwest A&F University, Yangling; 712100, China; (2) Key Laboratory of Northwest Facilities Horticultural Engineering, Ministry of Agriculture and Rural Affairs, Yangling; 712100, China; (3) College of Horticulture, Northwest A&F University, Yangling; 712100, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:256-265
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">The current design of the greenhouse cannot fully meet the high requirement of modern agriculture in recent years. It is necessary to deal with incoherent information, repetitive modelling, frequent revision of drawings, and manual extraction of variables during the design process. In this study, a Building Information Modeling (BIM) approach was proposed to the design of Venlo greenhouses. The design process consisted of schematic design, model creation, and design output. Before that, some specific configuration needed to be done. A systematic approach was established to apply the BIM technology for the Venlo greenhouse at different stages of the design process. Special software was then selected to create the greenhouse BIM. A BIM-based workflow was also constructed for the design, analysis, drafting, and material statistics of the glass greenhouse. Furthermore, a family library of the parametric component was created to screen different templates, according to the characteristics of Venlo greenhouse components. Subsequently, the site was arranged using the Revit's topography and volume modules in the schematic design. A visual analysis of climate data in the site was carried out using Ladybug Tools. The hours of direct sunlight on the winter solstice were also compared to determine the direction of the greenhouse. Additionally, the operator was created in Grasshopper to process the meteorological and the geometric data of greenhouse, in order to calculate the cooling and heating loads, as well as the maximum ventilation of greenhouse, thereby determining the equipment parameters. In the model creation, the elevation and axis networks were created in Revit for the positioning of the structural frame family, according to the defined scheme. A structural model was automatically generated and then exported to the Dlubal RFEM interface for the displacement and strength verification, where the specification of the frame was adjusted in real time. Afterwards, the components were deepened with the open cuts from the Revit family module, the steel module, and Advance Steel. The rest of the production systems were also created in turn after the structural framework, such as the enclosure, natural ventilation, and irrigation system. Moreover, a comprehensive evaluation of the model and systems were coordinated in Navisworks, according to the generated reports of collision detection. In the design output stage, the drawings were created quickly, where the comments were added in the views, further to drag into the title bar. The simple components were generated from the component view and complex assemblies, such that the trusses were created with Advance Steel. Material statistics were also completed separately using a family category. As such, the model was imported into the Lumion for rendering and animation using a plug-in. Anyway, the smart BIM model of the greenhouse was then created, together with a visual display of component installation. The BIM technology can be expected to break through the design chain. Specifically, the multiple uses of one model, simultaneous analysis, and automatic bill of materials statistics can greatly reduce the workload of drawing changes, and save one-third of the time, compared with the conventional. Consequently, the design process of Venlo greenhouse can be optimized to facilitate communication among multiple parties, while strengthening the management and application of project information, particularly for higher efficiency of project construction. The finding can also offer a new design approach to the greenhouse installation.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:48
Main heading:Architectural design
Controlled terms:Greenhouses - Information theory - Structural design - Topography - Visualization
Uncontrolled terms:'current - Building information modeling - Building Information Modelling - Design-process - Greenhouse design - Model creation - Modeling technology - Modern agricultures - Revit - Schematic design
Classification code:402 Buildings and Towers - 408.1 Structural Design, General - 716.1 Information Theory and Signal Processing - 821.6 Farm Buildings and Other Structures - 951 Materials Science
DOI:10.11975/j.issn.1002-6819.2021.20.029

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395535
Title:Named entity recognition in human nutrition and health domain using rule and BERT-FLAT
Title of translation:采用融合规则与BERT-FLAT模型对营养健康领域命名实体识别
Authors:Zheng, Limin (1); Ren, Lele (2)
Author affiliation:(1) Beijing Laboratory of Food Quality and Safety, Beijing; 100083, China; (2) College of Information and Electrical Engineering, China Agriculture University, Beijing; 100083, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:211-218
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A nutritious and healthy diet can be widely expected to reduce the incidence of disease, while improving body health after the disease occurs. The nutritional diet knowledge can be acquired mostly through the Internet in recent years. However, reliable and integrated information is highly difficult to discern using time-consuming searching of the huge amount of Internet data. It is an urgent need to integrate the complicated data, and then construct the knowledge graph of nutrition and health, particularly with timely and accurate feedback. Among them, a key step is to accurately identify entities in nutritional health texts, providing effective location data support to the construction of knowledge graphs. In this study, a BRET+BiLSTM+CRF (Bidirectional Encoder Representations from Transformers + Bi-directional Long Short-Term Memory + Conditional Random Field) model was first used with location information. It was found that the precision of the model was 86.56%, the recall rate was 91.01%, and the F1 score was 88.72%, compared with the model without location information, indicating improved by 1.55, 0.20, and 0.32 percentage points. A named entity recognition was also proposed to accurately obtain six types of entities in text: food, nutrients, population, location, disease, and efficacy in the field of human nutritional health, combining rules with BERT-FLAT (Bidirectional Encoder Representations from Transformers-Flat Lattice Transformer) model. Firstly, the character and vocabulary information were stitched together and pre-trained in the BERT model to improve the recognition ability of the model to entity categories. Then, a position code was created for the head and tail position of each character and vocabulary, where the entity position was located with the help of a position vector, in order to improve the recognition of entity boundary. A long-distance dependency was also captured using the Transformer model. Specifically, the output of the BERT model was embedded into the Transformer as a character-embedding conjunction word, thus for the character-vocabulary fusion. Then the text prediction sequence was obtained from the CRF layer. Finally, seven rules were formulated, according to the text characteristics in the field of nutrition and health, where the prediction sequence was modified according to the rules. The experimental results showed that the F1 score of the BERT-FLAT model was 88.99%. The BERT model combined with the word fusion performed the best, compared with that without the Bert model, indicating an effective recognition performance. Correspondingly, the named entity recognition model in the field of nutrition and health using fusion rules and the BERT-FLAT model presented an accuracy rate of 95.00%, a recall rate of 88.88%, and an F1 score of 91.81%. The F1 score increased by 2.82 percentage points than before. The finding can provide an effective entity recognition in the field of human nutrition and health.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:34
Main heading:Signal encoding
Controlled terms:Character recognition - Encoding (symbols) - Forecasting - Genes - Knowledge graph - Location - Long short-term memory - Natural language processing systems - Nutrition - Random processes
Uncontrolled terms:Attention mechanisms - BERT model - F1 scores - Human health - Human nutrition - Knowledge graphs - Location information - Named entity recognition - Self-attention mechanism - Transformer modeling
Classification code:461.2 Biological Materials and Tissue Engineering - 461.7 Health Care - 716.1 Information Theory and Signal Processing - 723.2 Data Processing and Image Processing - 723.4 Artificial Intelligence - 922.1 Probability Theory
Numerical data indexing:Percentage 8.656E+01%, Percentage 8.872E+01%, Percentage 8.888E+01%, Percentage 8.899E+01%, Percentage 9.101E+01%, Percentage 9.181E+01%, Percentage 9.50E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.024

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395589
Title:Maize straw motion law in subsoiling operation using discrete element method
Title of translation:基于离散元法的深松作业玉米秸秆运动规律
Authors:Zhao, Shuhong (1); Gao, Lianlong (1); Yuan, Yiwen (1); Hou, Leitao (1); Zhang, Xin (1); Yang, Yueqian (1)
Author affiliation:(1) School of Engineering, Northeast Agricultural University, Harbin; 150030, China
Corresponding author:Yang, Yueqian(yangyueqian@126.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:53-62
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Sowing stubbles with straw in ridges have seriously caused the entanglement, blockage, and resistance to the subsoiler and subsequent machine tool when returning corn straws to the field in the northeast areas of China. The purpose of this study was to establish a discrete element model of subsoiler-soil-straw-stubble for the motion behavior of straw during subsoiling operation, thereby exploring the movement and mechanical characteristics of straw under different conditions. The soil bin was also built as a common ridge in Northeast China. Among them, the straw was assumed as a rigid body, whereas, the breakable adhesive stubble was an unbreakable rigid body. The simulation and test data were then selected to investigate the motion mechanism of straws. Specifically, the tracking movement of straw was obtained as the simulation data. A high-speed camera was also utilized to record the movement data of straw in the field test. As such, the large variation in the movement of straw was better simulated during subsoiling operation, particularly in the complex field environment. Four influencing factors were achieved to represent the straw plucking away from the ridge in the operation of subsoiling, including the distance between the straw and the center of the ridge, the angle between straw and machine, the state of stubble (cutting in the middle of stubble, cutting on one side of stubble, picking up of stubble and no stubble), and the interaction between straws. Correspondingly, the displacement and torque of straws on ridges were obtained to determine the disturbance-specific resistance (the ratio of straw disturbance moment to subsoiler resistance) under the action of the subsoiler. The simulation results show that the distance between the straw and the center of the ridge presented the greatest influence on the horizontal and lateral movement of straws, where the horizontal-lateral displacement of straw decreased with the increase of the angle between the straw and machine. More importantly, there was the largest displacement in the forward direction of straw, when the angle of straw was 45°. The primary and secondary order of stubble state affecting straw displacement was as follows: stubble pick up, stubble side cutting, no stubble, stubble middle cutting. Especially, there was the greatest influence of the interaction between the straws on the forward direction of straws, when the distance between the straw and the center of the ridge was 60 mm. Once more than 60 mm, the displacement tended to increase in the forward direction of straws. In addition, the torque of straws was calculated to explore the rotation of straw in simulation tests. It was found that the overall trend was as follows: the peak value was generated after the stable operation, and then tended to be stable. Anyway, there was a great influence of stubble on the torque of straw. The errors of the total displacement, horizontal-lateral displacement and forward displacement obtained by the simulation model with the test values were 0.36% -9.67%, 0.16% -12.31%, and 0.56% -10.11%, respectively. The error of straw torque was also 0.16% to 11.06%. The error between the test and simulation value was within the allowable range, indicating a similar changing trend. Consequently, the test verified the rationality and feasibility of discrete element simulation. The finding can greatly contribute to understanding the mechanism of straw during subsoiling, particularly to the reasonable design of subsoil machinery in modern agriculture.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:32
Main heading:Finite difference method
Controlled terms:Adhesives - Friction - High speed cameras - Machine tools - Rigid structures
Uncontrolled terms:Discrete elements method - Lateral displacements - Maize straw - Motion law - Rigid body - Simulation - Simulation data - Straw movement - Subsoiling - Test
Classification code:408 Structural Design - 603.1 Machine Tools, General - 742.2 Photographic Equipment - 921.6 Numerical Methods
Numerical data indexing:Percentage 1.60E-01% to 1.106E+01%, Percentage 1.60E-01% to 1.231E+01%, Percentage 3.60E-01% to 9.67E+00%, Percentage 5.60E-01% to 1.011E+01%, Size 6.00E-02m
DOI:10.11975/j.issn.1002-6819.2021.20.006

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395628
Title:Construction of the green development indicators for agriculture and its prediction in the 14th Five-Year Plan in China
Title of translation:中国农业绿色发展指标体系构建及其"十四五"趋势预判
Authors:Su, Kai (1, 2); Meng, Haibo (1); Zhang, Hui (1)
Author affiliation:(1) Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (2) Anxi College of Tea Science, Fujian Agriculture and Forestry University, Fuzhou; 350002, China
Corresponding author:Zhang, Hui(zhanghui@aape.org.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:287-294
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">The ever-increasing needs for a better life have proposed much higher requirements for agricultural development, as socialism with Chinese characteristics has entered a new era. The Agricultural Green Development (AGD) has been the re-creation under the Sinicization for the concept of sustainable development. The construction of green development indicators for agriculture can greatly contribute to quantitatively valuating the AGD level, particularly for path exploration and policy-making. Accordingly, this study aims to first construct the evaluation index system of AGD in China. Then, the entropy, Principal Component Analysis (PCA), and Analytic Hierarchy Process (AHP) were applied to calculate the weight value of each indicator. As such, a combination weighting was used to calculate the final comprehensive weight value of each indicator to evaluate the AGD level in China from 2007 to 2019. Finally, a grey Verhulst model was adopted to predict the development trend in the 14th Five-Year Plan. The findings of this study revealed that China's AGD level showed a steady upward trend, and gradually moved towards the path of green development during 2007-2019. The comprehensive index of AGD rose from 26.20 in 2007 to 70.76 in 2019, with an average annual increase of 13.08%. Among them, the comprehensive index of AGD in 2017, 2018, and 2019 increased by 4.5%, 1.8%, and 5.1%, respectively, higher than the average level from 2013 to 2016. This was because, 1) a series of important policies were released to promote the AGD in recent years, including the relevant mechanism for AGD, the national AGD pilot zones, the supporting capacity of science and technology. 2) The agricultural development was oriented towards the path of green development during policy decision-making. More importantly, the weight value of the first-level index "Resource conservation and efficient utilization" was the largest (0.386), and the rest of the three first-level indicators were ranked in descending order "Policy support and science & technology support" (0.223), "Natural resources and ecological security" (0.212) and "High-quality products and affluence" (0.179). 3) China's AGD was predicted to enter the fast lane during the 14th Five-Year Plan, where the comprehensive index of AGD reached 77.9, an increase of 11.67% over 2019. It was also found that there were much larger weight values for the indicators of energy consumption per unit of agricultural output, carbon base productivity, and R&D investment intensity. It inferred that scientific and technological innovation can be an effective way to reduce resource consumption for higher efficient use, which was the power source for AGD. Therefore, three recommendations can be addressed during this time: 1) To further improve the system and mechanism of AGD; 2) To explore diversified agricultural and ecological compensation (e.g., carbon compensation), and 3) to strengthen the tackling of key green technologies (e.g., green technology for higher production and efficiency of crops, green and low-carbon planting and breeding technology). This finding can provide potential decision-making support to promote the AGD for the construction of the evaluation index system.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:35
Main heading:Agriculture
Controlled terms:Analytic hierarchy process - Conservation - Decision making - Ecology - Environmental protection - Hierarchical systems - Planning - Principal component analysis - Public policy - Sustainable development
Uncontrolled terms:Combination weighting method - Composite index - Composite index system - Five-year plans - Green development - High quality - High-quality development - Indices systems - Verhulst model - Weight values
Classification code:454.2 Environmental Impact and Protection - 454.3 Ecology and Ecosystems - 821 Agricultural Equipment and Methods; Vegetation and Pest Control - 912.2 Management - 922.2 Mathematical Statistics - 961 Systems Science - 971 Social Sciences
Numerical data indexing:Percentage 1.167E+01%, Percentage 1.308E+01%, Percentage 1.80E+00%, Percentage 4.50E+00%, Percentage 5.10E+00%, Size 5.09778E+01m to 1.797304E+00m, Size 6.6548E-01m
DOI:10.11975/j.issn.1002-6819.2021.20.032

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395547
Title:Simulation of agricultural equipment load using MCMC with optimal state number
Title of translation:利用优选状态数的MCMC模拟农机装备负载
Authors:Yang, Zihan (1); Song, Zhenghe (1)
Author affiliation:(1) Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, China Agricultural University, Beijing; 100083, China
Corresponding author:Song, Zhenghe(songzhenghe@cau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:15-22
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">The selection of state number depends highly on the subjective experience in the traditional Markov Chain Monte Carlo (MCMC). However, an inappropriate value of state number can lead to a great reduction in the accuracy of load simulation, even an increase in the running time during the simulation of agricultural equipment loads. This study aims to clarify the effect of state number on the simulation when the MCMC was applied to agricultural equipment load. Specifically, the mean error, standard deviation error, and deviation of rain flow matrix between the simulated and original load decreased rapidly to stabilize, as the state number increased. Moreover, the indicators were not generalizable, if there was no significance between them. An optimization of state number was also proposed using pseudo damage consistency. As such, the damage consistency between the simulated and original load gradually improved and smoothed out, as the state number increased, whereas, the rate of increase in the operation time continued to increase. The optimal state number was calculated to satisfy the damage consistency and minimum operation time, where a threshold value was set for the pseudo damage factor. Furthermore, the field tests were carried out for both tractor ploughing and soil preparation. The specific parameters were measured to validate, including the front axle vibration, front axle stress, and driveshaft torque load. The vibration loads were also utilized to apply for the tractor front drive axle during ploughing operations. It was found that the MCMC using optimal state number can be expected torealize the load simulation with pseudo damage differences within 1%. Furthermore, there were more significant differences between the load segments in the adjustment stage, where the optimal state numbers for each load segment were more dispersed than that in the operation stage. A cyclic simulation was also developed for the loads of key components, according to the operational characteristics of a tractor. Subsequently, the MCMC cycle simulations were also performed on the front axle vibration loads for ploughing. The results show that the simulated load retained the alternating switching between the operating and adjustment stages under tractor ploughing. The same procedure was used to simulate the stress load on the front axle under ploughing, where the torque was separately loaded on the driveshaft under soil preparation. The statistical characteristic indicators were selected, including the mean, standard deviation, and the maximum load cycle amplitude for each load segment. The deviation range of each statistical eigen value was also obtained, compared with the original. The eigen values simulation for each load segment was in a higher agreement with the original eigen values. The generality was further validated when applied to the load simulation of agricultural equipment with the objective of load spectrum preparation. Consequently, the MCMC using optimal state number was better matched to the target requirements of load spectrum preparation, compared with the conventional. The finding can also effectively reduce the computational cost for the higher accuracy during load simulation of agricultural machinery.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Monte Carlo methods
Controlled terms:Agriculture - Axles - Errors - Loads (forces) - Markov processes - Soils - Tractors (agricultural) - Tractors (truck)
Uncontrolled terms:Agricultural equipment - Load - Load simulation - Markov chain Monte Carlo - Markov Chain Monte-Carlo - MonteCarlo methods - Optimal state - Optimal state number - Pseudo damage - Simulation
Classification code:408 Structural Design - 483.1 Soils and Soil Mechanics - 663.1 Heavy Duty Motor Vehicles - 821 Agricultural Equipment and Methods; Vegetation and Pest Control - 821.1 Agricultural Machinery and Equipment - 922.1 Probability Theory - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 1.00E00%
DOI:10.11975/j.issn.1002-6819.2021.20.002

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395691
Title:Effects of different extraction methods on phenolic compounds and antioxidant activity in Hemerocallis flower
Title of translation:不同提取方式对萱草花中酚类物质及抗氧化活性的影响
Authors:Tian, Huaixiang (1); Chen, Shuang (1); Chen, Xiaoyan (1); Yu, Haiyan (1); Huang, Juan (1); Yuan, Haibin (1); Chen, Chen (1)
Author affiliation:(1) Faculty of Fragrance, Fragrance and Cosmetics, Shanghai Institute of Technology, Shanghai; 201418, China
Corresponding author:Chen, Chen(chenchen@sit.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:303-312
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Hemerocallis fulva is one of the most popular flowers rich in bioactive substances, such as polyphenols, flavonoids, and alkaloids anthraquinones, particularly on antioxidant, antidepressant and anticancer. The extraction of phenolic compounds and antioxidant properties can also greatly contribute to the popularization of H. flower in the agricultural industry. However, only a few reports were focused on the extraction, forms and antioxidant activities of phenolic compounds in the H. flower. The present study aims to explore the effects of different extraction on the content, composition and antioxidant activity of phenolic compounds in various Hemerocallis flowers. Five kinds of flowers with different colors (yellow, orange, red-orange, jujube red, and bright red) were selected as raw materials. Three processing treatments (ultrasound, enzymolysis-ultrasound, and fermentation-ultrasound) were also utilized to determine the content of total flavonoids, total polyphenols, and scavenging rate of free radicals. Furthermore, high-performance liquid chromatography was adopted to identify the free, conjugated, and bound fractions of phenolic compounds, where the relationship was also established between phenolic compounds and antioxidant activity. Specifically, the types of total flavonoids and polyphenols were as follows: 'Hongyingwu', '63#', 'Jianzhuanglilan', 'Meiguixiniu', and 'Taiyangwu'. The results showed that there was a significant difference (P<0.05) of antioxidant activity in the different varieties of flowers, where the antioxidant activity was positively correlated with phenolic content. Furthermore, the antioxidant activities of flowers depended mainly on the varieties and extraction. More importantly, the vitamin C equivalents of DPPH (1,1-diphenyl-2-picrylhydrazyl) were 44.32, 40.63, 38.24, 37.64, and 35.60 mg/g, respectively, for the 'Hongyingwu', '63#', 'Jianzhuanglilan', 'Meiguixiniu' and 'Taiyangwu' under the fermentation-ultrasonic processing. The corresponding ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) vitamin C equivalents were 39.74, 36.24, 30.88, 28.38 and 24.88 mg/g, respectively. The vitamin C equivalent of DPPH of 'Hongyingwu' increased from 38.24 mg/g by ultrasonic extraction to 41.49 mg/g by enzymatic ultrasonic extraction and 44.32 mg/g by fermentation-ultrasonic extraction. The vitamin C equivalent of ABTS of 'Hongyingwu' increased from 31.82 mg/g by ultrasonic extraction to 35.12 mg/g by enzymatic ultrasonic extraction and 39.74 mg/g by fermentation-ultrasonic extraction. Among the three fractions, the content of phenolic compounds in the free fraction was the highest, accounting for more than 75% of the total contents. Enzymatic hydrolysis and fermentation significantly (P<0.05) improved the contents of most phenolic compounds in the free fraction of 'Hongyingwu'. Particularly, the p-Coumaric acid was newly detected, while the free quercetin content after fermentation reached three times that of the original. The Vitamin C equivalent of DPPH and ABTS free radical scavenging rate of free phenols increased from 40.53 and 35.57 mg/g for ultrasonic processing to 48.20 and 47.40 mg/g for fermentation-ultrasonic processing, respectively. Correlation analysis demonstrated that the chlorogenic acid, caffeic acid, quercetin, and rutin in the free fraction were highly correlated with the antioxidant activity, indicating a great contribution to antioxidant activity. The finding can provide a theoretical basis for the development and utilization of H. flower in functional foods and cosmetics.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:38
Main heading:Extraction
Controlled terms:Antioxidants - Citrus fruits - Fermentation - Flavonoids - Free radicals - High performance liquid chromatography - Ketones - Phenols - Plants (botany) - Pyrene - Ultrasonics
Uncontrolled terms:Antioxidant activities - Free fraction - Free phenol - Hemerocallis - Hemerocallis flower - Phenolic antioxidant - Phenolic compounds - Ultrasonic extraction - Ultrasonic processing - Vitamin C
Classification code:753.1 Ultrasonic Waves - 802.3 Chemical Operations - 803 Chemical Agents and Basic Industrial Chemicals - 804 Chemical Products Generally - 804.1 Organic Compounds - 804.2 Inorganic Compounds - 821.4 Agricultural Products
Numerical data indexing:Percentage 7.50E+01%, null 2.488E+01null, null 2.838E+01null, null 3.182E+01null, null 3.512E+01null, null 3.557E+01null, null 3.56E+01null, null 3.824E+01null, null 3.974E+01null, null 4.053E+01null, null 4.149E+01null, null 4.432E+01null, null 4.74E+01null, null 4.82E+01null
DOI:10.11975/j.issn.1002-6819.2021.20.034

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395511
Title:Design of the blockchain multi-chain traceability supervision model for coarse cereal supply chain
Title of translation:杂粮供应链区块链多链追溯监管模型设计
Authors:Yu, Huajing (1, 2); Xu, Daming (1, 2); Luo, Na (1, 2); Xing, Bin (1, 2); Sun, Chuanheng (1, 2)
Author affiliation:(1) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (2) National Engineering Laboratory for Quality and Safety Traceability Technology and Application of Agricultural Products, Beijing; 100097, China
Corresponding authors:Sun, Chuanheng(sunch@nercita.org.cn); Sun, Chuanheng(sunch@nercita.org.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:323-332
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A coarse cereal is one of the most important crops rich in nutrients. However, the frequently-occurred issues on food quality and safety have seriously endangered the trust in recent years, for example, the abuse of chemicals, heavy metals exceeding the standard, and harmful germs. Therefore, a traceability system is an urgent need for coarse cereals, in order to bridge the trust between farms and consumers, where the source of agricultural coarse foods can be rapidly traced through multi-party efficient collaboration. Most current traceability systems focus on recording data using bar or QR codes, radio frequency identification, and wireless sensor networks. But the tracing information is broken easily between upstream and downstream, leading to the blur transferred data, particularly on the long and scattered supply-chain of agricultural foods, including cultivation, processing, logistics, storage, and sales. Furthermore, the traditional traceability system cannot efficiently supervise the data records of each company, when quality and safety issues occur. As such, it is impossible to recall the problematic foods in time, much less to accurately locate the responsible party. Fortunately, blockchain technology can be utilized to integrate the distributed architecture, storage, and verification in the block, peer-to-peer network protocols, encryption, consensus mechanisms, identity authentication, and smart contracts. The data disclosure can also be used to enhance trust with fewer intermediate links. Therefore, this study aims to deal with the long supply-chain of coarse cereals, many trace entities, the differentiate share of data ledger, and the real-time monitoring of on-chain data. A novel traceability system was designed to implement the supervisable food products using the multi-chain architecture of blockchain and supply chain in coarse cereal. The forward and reverse traceability data was also collected ranging from the planting, processing, warehousing, transportation, and sales, using cameras, sensors, Beidou positioning devices, and IoT devices in real-time. Moreover, a systematic investigation was made on the business process and supervision characteristics of the supply-chain, as well as the full life cycle of coarse cereal. In addition, a new architecture of supervision-oriented multi-chain data storage was proposed for the actual production of coarse cereal. Specifically, the off-chain CouchDB state database was selected to store the key-value traceability data, particularly on the key-index instead of traversal query to improve the query efficiency. More importantly, a network access mechanism was designed using the regulatory authority, further to realize the collaborative supervision on- and off-chain through smart contracts. Correspondingly, blockchain technology was used to ensure the deep connection of various production factor resources with the real economy of coarse cereal. Anyway, the supply chain of coarse cereal integrated with the blockchain was utilized to strengthen the multi-party collaboration through mutual identity authentication, especially on data expansion, data sharing, and supervision. In terms of security, the average change rate of ciphertext in the enterprise network authorization diffusivity test was 82.53%, the average change rate of ciphertext in the enterprise network authorization correlation test was 82.39%, indicating higher security and less confusion. In terms of efficiency, the average time for consumers to query public traceability data was 0.415 s, and the average time for regulators to call cross-link port to query enterprise sensitive traceability data was 0.871 s. Furthermore, an actual traceability system was implemented to verify the model using Hyperledger Fabric for data privacy protection, data differentiation sharing, and the penetration supervision of traceability data, together with the real-time management, and control of traceability nodes. The in-depth mining was realized for the value of coarse cereal traceability big data, and sustainable development of the traced network. As such, farmers can receive professional or industrial policy guidance, whereas, companies can obtain the market trends and price conditions in real-time, and regulatory authorities can accurately control traceability data and transaction behavior. The finding can greatly improve the quality and safety of coarse cereal, production efficiency, and economic benefits.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Supply chains
Controlled terms:Agricultural products - Authentication - Cryptography - Cultivation - Digital storage - Distributed computer systems - Distributed ledger - Food safety - Heavy metals - Internet of things - Life cycle - Network architecture - Network protocols - Peer to peer networks - Radio frequency identification (RFID) - Smart contract - Terminology - Wireless sensor networks
Uncontrolled terms:Block-chain - Data regulatory - Hyperledg fabric - Identity authentication - Multi-chain - Quality and safeties - Real- time - Regulatory authorities - Traceability - Traceability systems
Classification code:461.6 Medicine and Pharmacology - 531 Metallurgy and Metallography - 716.3 Radio Systems and Equipment - 722 Computer Systems and Equipment - 722.1 Data Storage, Equipment and Techniques - 722.3 Data Communication, Equipment and Techniques - 722.4 Digital Computers and Systems - 723 Computer Software, Data Handling and Applications - 731.1 Control Systems - 821.3 Agricultural Methods - 821.4 Agricultural Products - 822.3 Food Products - 902.3 Legal Aspects - 911.3 Inventory Control - 912 Industrial Engineering and Management - 913 Production Planning and Control; Manufacturing
Numerical data indexing:Percentage 8.239E+01%, Percentage 8.253E+01%, Time 4.15E-01s, Time 8.71E-01s
DOI:10.11975/j.issn.1002-6819.2021.20.036

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395515
Title:Construction and empirical analysis of the evaluation index system for the water-saving level of large-sized irrigation districts
Title of translation:大型灌区节水水平评价指标体系构建与实证
Authors:Fan, Xichao (1, 2); Qin, Jingtao (1, 2); Xu, Lei (3); Liu, Siruo (3); Gu, Shaowei (1, 2); Lyu, Mouchao (1, 4)
Author affiliation:(1) Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang; 453002, China; (2) Graduate School of Chinese Academy of Agricultural Sciences, Beijing; 100081, China; (3) China Irrigation and Drainage Development Center, Beijing; 100054, China; (4) Key Laboratory of Watersaving Irrigation Engineering, Ministry of Agriculture and Rural Affairs, Xinxiang; 453002, China
Corresponding authors:Lyu, Mouchao(lvmouchao@aliyun.com); Lyu, Mouchao(lvmouchao@aliyun.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:99-107
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">About 215 billion cubic metres of water has been consumed by large and medium-sized irrigation districts in recent years, particularly over 35% quantity of the total water consumption in China. The irrigation district has been the main field of agricultural water-saving construction. Therefore, it is necessary to accurately assess the water-saving level in modern irrigation districts. In this study, an index system was established to evaluate the water-saving level in large-scale irrigation districts. Five aspects were considered, including engineering water-saving, farmland water-saving, water use management, water resources protection, and water use benefit. Eight standards were selected, such as measurability, vulnerability, predictability, typicality, controllability, integrity, responsiveness, and stability. A screening model was constructed to identify the indexes to be shortlisted or not. Subsequently, 23 indexes from the 70 primary indexes, 86.42% of the information was expressed by 32.86% of the elementary indexes, indicating the concise and adequate index system. The final indexes were formed, including the backbone canal lining ratio, the completion rate of engineering projects, backbone canal intact rate, backbone hydraulic structures intact percentage, water utilization coefficient of canal system, high-efficient water-saving irrigation coverage percentage, field water utilization coefficient, multi-cropping index, gross irrigation water consumption per mu, real collection rate of water charges, water user association coverage rate, allocation rate of water measuring equipment on lateral gate, 2 fees implementation rate, number of management personnel per 10 000 mu, proportion of management personnel with junior college degree or above, informationization coverage rate, proportion of irrigation water in total water consumption, drainage ditch intact rate, water ecological monitoring system coverage rate, proportion of ecological water in the total water consumption, grain yield produced by 1m³ irrigation water, proportion of primary industry production in irrigation district, and water consumption per-10 000-yuan-GDP. Four large-scale irrigation districts (Qucun, Penglou, Guangli, and Dagong) are all located along the Yellow River in Henan Province. The indexe system was then investigated empirically to determine the water-saving level. The water-saving level indexes for the four objective Irrigation Districts were 0.666 (Qucun), 0.730 (Penglou), 0.657 (Guangli), and 0.616 (Dagong), respectively. On the whole, the score of the water-saving level index was ranked in the descending order of Penglou, Qucun, Guangli, and Dagong. The scores of the 5 secondary indexes showed that Penglou achieved the best effect of engineering water-saving, whereas, Dagong was a negative example. This was due to the well-matched infrastructure engineering, where the backbone canal system was of systematic construction and renovation in the past 10 years. Guangli performed relatively lower than the rest because the high-efficient coverage percentage of water-saving irrigation was rather weak and the gross consumption of irrigation water per mu was pretty high, particularly for the long-term goals of farmland water-saving. There was no significant difference in the score of water use management level among the four irrigation districts, but their agriculture water rate, water user association promotion, and water measuring facilities setting, all needed to be rather improved. Water resources protection was the common weakness of the four irrigation districts, indicating the concept of project construction without considering ecological protection over the past years. Consequently, five recommendations can be addressed to further improve the water-saving level in the irrigation districts. 1) To coordinate the backbone and field construction, 2) To establish the new water-saving system under the agricultural water price reform, 3) To strengthen the dredging and transformation of drainage ditches, 4) To improve the water resources and environment monitoring network, 5) To promote the efficient saving on water irrigation, particularly for the planting area of cash crops. The findings can provide an effective way to scientifically evaluate the water-saving construction in large-scale irrigation districts, thereby promoting the process of agricultural water-saving in China.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:43
Main heading:Irrigation
Controlled terms:Drainage - Ecology - Human resource management - Hydraulic structures - Information management - Irrigation canals - Water conservation - Water management - Water supply
Uncontrolled terms:Index optimization - Indices systems - Irrigation districts - Large-sized - Large-sized irrigation district - Optimisations - Water consumption - Water-saving - Water-saving level - Waters resources
Classification code:444 Water Resources - 446.1 Water Supply Systems - 454.3 Ecology and Ecosystems - 821.3 Agricultural Methods - 912.2 Management - 912.4 Personnel
Numerical data indexing:Age 1.00E+01yr, Percentage 3.286E+01%, Percentage 3.50E+01%, Percentage 8.642E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.011

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395646
Title:Spatio-temporal variations of wheat, rice and maize straw in major grain-producing counties of Anhui Province and utilization potential of straw nutrient returning to field
Title of translation:安徽省县域麦稻玉米秸秆时空分异特征与还田养分输入量测算
Authors:Chai, Rushan (1); Cheng, Qipeng (1); Chen, Xiang (2); Luo, Laichao (1); Ma, Chao (1); Zhang, Liangliang (1); Zhang, Ligan (1); Li, Jincai (2); Gao, Hongjian (1)
Author affiliation:(1) College of Resources and Environment, Anhui Agricultural University/Anhui Province Key Lab of Farmland Ecological Conservation and Pollution Prevention, /Key Lab of Jianghuai Arable Land Resources Protection and Eco-restoration, Hefei; 230036, China; (2) College of Agronomy, Anhui Agricultural University, Hefei; 230036, China
Corresponding author:Gao, Hongjian(hjgao@ahau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:234-247
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Anhui Province of China is one of the most important agricultural production bases with abundant grain crop straw resources. It is necessary to clarify the temporal and regional characteristics of theoretical and crop residues for the differentiated development of fully quantitative utilization in straw sources in major grain-producing counties. Accurate evaluation of utilization potential to straw nutrient resources can essentially contribute to balancing the regulation of soil nutrients under straw returning. In this study, a systematic investigation was made on the spatiotemporal variation of wheat, rice and maize straw in major grain-producing counties of Anhui Province and utilization potential of a straw nutrient return to the field. The result showed that the total output of straw resources presented a slowly rising trend from 2011 to 2019. However, the straw production during 2011-2019 presented significant differences among three major grain crops, where the wheat straw firstly increased and then remained stable, while the rice straw was relatively stable with small fluctuation, and the maize straw showed an outstanding ascending. The theoretical amount of three main grain crop straws were 38.78 million tons in 2019, among which the wheat, rice, and maize straws accounted for 47.3%, 36.3%, and 16.4%, respectively. The wheat straw (73.0%) and maize straw (88.3%) were mainly concentrated in the North area of the Huai River. The rice straw was mainly distributed in the area between the Yangtze and the Huai River (41.7%), Western Anhui Province (21.3%), and the edge area of the Yangtze River (19.7%). The distribution of total straw yields from the three main grain crops in different agricultural areas was ranked as follows: North area of the Huai River (52.5%) > Area between the Yangtze and the Huai River (24.3%) > Western Anhui Province (10.5%) > Edge area of the Yangtze River (9.1%) > Southern Anhui Province (3.6%). The straw resources in 2019 were 13.38, 10.41, and 5.42 million tons for wheat, rice, and maize, respectively. The straw resources per unit sown area in the north area of the Huai River of Anhui Province were 4 505-6 310 and 4 171-5 395 kg/hm<sup>2</sup> for wheat and maize, respectively. The rice straw per unit sown area were 4 487-5 326, 4 570-5 028, and 4 329-5 778 kg/hm<sup>2</sup> for the Area between the Yangtze and the Huai River, Western Anhui Province and the Edge area of the Yangtze River, respectively. Furthermore, the contents of N, P<inf>2</inf>O<inf>5,</inf> and K<inf>2</inf>O were 0.253, 0.109, and 0.901 million tons, respectively, for the main grain crop straws in 2019. In the North area of Huai River of Anhui province, the nutrient inputs by wheat straw incorporation were N 35.8-50.1, P<inf>2</inf>O<inf>5</inf> 14.1-19.8, and K<inf>2</inf>O 139.8-195.8 kg/hm<sup>2</sup>, respectively, and the nutrient inputs under maize straw return scenario were N 42.7-55.2, P<inf>2</inf>O<inf>5</inf> 16.9-21.8 and K<inf>2</inf>O 93.4-120.9 kg/hm<sup>2</sup>, respectively. In the primary rice-growing regions (Area between the Yangtze and the Huai River, Western Anhui Province, and Edge area of the Yangtze River), the soil nutrient inputs from rice straw incorporation were N 38.0-50.8, P<inf>2</inf>O<inf>5</inf> 18.8-25.0, and K<inf>2</inf>O 151.6-202.3 kg/hm<sup>2</sup>, respectively. The finding can offer a great practical significance to improve the comprehensive utilization rate of straw resources, and further promote the green and high-quality development of agriculture for major grain-producing counties in Anhui Province of China.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:43
Main heading:Straw
Controlled terms:Crops - Grain (agricultural product) - Nutrients - Rivers
Uncontrolled terms:Anhui province - Grain crops - Huai rivers - Maize straw - Nutrients input - Rice straws - Spatiotemporal distributions - Straw incorporations - Wheat straws - Yangtze River
Classification code:821.4 Agricultural Products - 821.5 Agricultural Wastes
Numerical data indexing:Percentage 8.83E+01%, Percentage 9.10E+00%, Percentage 7.30E+01%, Mass 1.398E+02kg to 1.958E+02kg, Mass 1.516E+02kg to 2.023E+02kg, Mass 3.95E+02kg, Mass 7.78E+02kg, Mass 9.34E+01kg to 1.209E+02kg, Percentage 1.05E+01%, Percentage 1.64E+01%, Percentage 1.97E+01%, Percentage 2.13E+01%, Percentage 2.43E+01%, Percentage 3.60E+00%, Percentage 3.63E+01%, Percentage 4.17E+01%, Percentage 4.73E+01%, Percentage 5.25E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.027

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395546
Title:Calibration of the discrete element parameters for the soil model of cotton field after plowing in Xinjiang of China
Title of translation:新疆棉田耕后土壤模型离散元参数标定
Authors:Song, Shaolong (1, 2); Tang, Zhihui (1, 2); Zheng, Xuan (1, 2); Liu, Jinbao (1, 2); Meng, Xiangjin (1, 2); Liang, Yuchao (1, 2)
Author affiliation:(1) Mechanical Equipment Research Institute, Xinjiang Academy of Land Reclamation Sciences, Shihezi; 832000, China; (2) Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi; 832000, China
Corresponding authors:Liu, Jinbao(jinbao1226@126.com); Liu, Jinbao(jinbao1226@126.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:63-70
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A multi-layer fertilization has been considered as an efficient way to meet the needs of fertilizers at different growth stages of crops. A layered fertilization device is usually used for the process of ditching and covering soil after ploughing. In this case, the movement of soil particles is very complicated. In this study, an EDEM discrete element software was used to simulate the process of soil accumulation and sliding in the layered fertilization area, in order to calibrate soil contact parameters. A Hertz-Mindlin non-slip model was selected to simulate the contact surface of soil-soil and soil-layered fertilization device (65 Mn steel), according to the soil characteristics of cotton fields after ploughing. Three common shapes of soil particles were represented by dual surface, square four, and straight four. The calibration parameters were also selected to determine the ranges. Specifically, the static friction coefficient, rolling friction coefficient, and collision recovery coefficient between soil-soil and soil-65 Mn steel were used as test factors, while the soil angle of repose, and sliding friction angle of soil-Mn steel were used as evaluation indicators. The universal rotation center combination test was conducted to verify the model. The Design-Expert software was then utilized to perform the regression on the test data. The results showed that the coefficient of recovery from the collision of soil-soil and soil-65 Mn steel presented no significant effect on the angle of repose and sliding friction of soil. Taking the measured soil angle of repose and the sliding friction angle between the soil and 65 Mn steel as the optimization objectives, an optimal combination of discrete element contact parameters was obtained: the coefficient of restoration between soils was 0.48, the coefficient of rolling friction between soils was 0.56, the coefficient of static friction between soils was 0.24, the coefficient of restitution between the soil and 65 Mn steel was 0.5, the coefficient of rolling friction between soil and 65 Mn steel was 0.1, and the coefficient of static friction between soil and 65 Mn steel was 0.31. A soil accumulation test and the sliding test were also compared with the actual test, in order to verify the accuracy of the optimized parameters. The relative errors of the two tests were 1.7% and 2.5%, respectively, under the optimal combination of calibration parameters. Consequently, the discrete elements can be expected to simulate the ditching and soil covering process of the layered fertilization device. The relative errors of simulation and field test were 10.2%, and 7.95%, respectively, at the operating speed of 5, 6, and 7 km/h of layered fertilization device. Among them, the error of 7.04% was within the acceptable range. Consequently, the simulation and field test presented basically the same effect of ditching and covering soil, indicating the high accuracy and reliability for the calibration of soil contact parameters. The finding can provide strong theoretical and technical support for the later research on drag reduction of layered fertilization devices.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Soils
Controlled terms:Agricultural machinery - Calibration - Compressive strength - Crops - Finite difference method - Optimization - Recovery - Restoration - Software testing - Soil mechanics - Soil testing - Trenching
Uncontrolled terms:Angle of repose - Contact parameters - Discrete elements - Discrete elements method - Fertilisation - Parameters calibrations - Sliding friction - Soil-soil - Stratified fertilization - Trenching and mulching
Classification code:483.1 Soils and Soil Mechanics - 619.1 Pipe, Piping and Pipelines - 723.5 Computer Applications - 821.1 Agricultural Machinery and Equipment - 821.4 Agricultural Products - 921.5 Optimization Techniques - 921.6 Numerical Methods
Numerical data indexing:Percentage 1.02E+01%, Percentage 1.70E+00%, Percentage 2.50E+00%, Percentage 7.04E+00%, Percentage 7.95E+00%, Size 7.00E+03m
DOI:10.11975/j.issn.1002-6819.2021.20.007

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395647
Title:Voice recognition of abnormal state of pigs based on improved CNN
Title of translation:采用改进CNN对生猪异常状态声音识别
Authors:Geng, Yanli (1, 2); Song, Pengshou (1); Lin, Yanbo (1); Ji, Yankai (1); Yang, Shucai (3)
Author affiliation:(1) School of Artificial Intelligence, Hebei University of Technology, Tianjin; 300130, China; (2) Engineering Research Center of Intelligent Rehabilitation Device and Detection Technology, Ministry of Education, Tianjin; 300130, China; (3) Tianjin Mojieke Intelligent Technology Co., Ltd., Tianjin; 300130, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:187-193
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Sound has been widely used to monitor the health and body conditions of pigs. But the manual monitoring cannot meet the high demand in modern agriculture at present, including zoonotic diseases, misjudgments of pig diseases, and time- and labor-consuming. In this study, a real-time collection module of pig sound was designed to rapidly recognize the abnormal state using an improved convolutional neural network (CNN). A 4G communication was used to upload the collected pig sound into the cloud server. A TCP/IP communication protocol was also selected, where the acquisition end was set as a TCP client and the uninterrupted data to the server. Specifically, the TCP cloud server was utilized to block the specified port, and then start the transfer data after the client was connected successfully. The server also sent a restart command to the client, to ensure data alignment. The sound acquisition was realized via a single channel, where the sampling frequency was 32 kHz, while the quantization digit was 16 bits. Correspondingly, the raw data of various abnormal sounds of pigs (sickness, fighting, and Hunger) were collected, according to the experts of pig breeding. Some operations were used to preprocess the data, including framing, windowing, de-nosing, and endpoint detection. As such, a voice data set of abnormal status was built. Subsequently, the Mel spectrogram of various sounds was extracted under the parameters of 128-dimensional mel frequency, 2048 points of Fast Fourier Transform (FFT) points, and 512 points of window shift. A classification model of the signal acquisition was then constructed using the feature of Mel spectrogram for pig sound signals. Therefore, a local feature learning unit was designed using an improved CNN, indicating fewer weights and lower network complexity than fully connected networks. Four layers of local feature units were constructed, where the number of convolution kernels in each layer was 64-64-128-128. Nevertheless, the local location and various redundant information were inevitably generated, when CNN had acquired each image. Three types of attention mechanisms were used to improve CNN, including Squeeze and Excitation Network (SE_NET), Efficient Channel Attention Networks, (ECA_NET), and Convolutional Block Attention Module (CBAM). A fully connected network with three neurons and an activation function of Softmax was also used to recognize abnormal sounds of pigs. The CBAM was then optimized to propose the CBAM-CNN using the ECA_NET improved SE_NET. The experimental results show that the optimal combination of parameters in pig voice recognition was 128 dimensional Mel frequency, 2048 point FFT, 1/4 window shift, and the optimal network model was _CBAM-CNN. The optimal recognition accuracy reached 94.46%, and the accuracy of pig squeal recognition reached 100%, better than before. The attention mechanism was also improved the model recognition, while reducing model complexity. A better recognition was achieved using the smaller size of _CBAM-CNN model, compared with CBAM-CNN. The accuracy of _CBAM-CNN model was 94.46% for the sound recognition of abnormal pigs. This finding can provide the accurate monitoring of abnormal behaviors of pigs in the process of breeding, thereby constructing intelligent and modern pig farms.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:26
Main heading:Convolution
Controlled terms:Acoustic noise - Audio acoustics - Cloud computing - Complex networks - Convolutional neural networks - Fast Fourier transforms - Mammals - Spectrographs - Transmission control protocol
Uncontrolled terms:Abnormal noise - Abnormal sounds - Cloud servers - Convolutional block attention module - Convolutional neural network - Efficient channel attention network, - Efficient channels - Mel frequencies - Spectrograms - Squeeze and excitation network
Classification code:716.1 Information Theory and Signal Processing - 722 Computer Systems and Equipment - 722.3 Data Communication, Equipment and Techniques - 722.4 Digital Computers and Systems - 723 Computer Software, Data Handling and Applications - 741.3 Optical Devices and Systems - 751.1 Acoustic Waves - 751.4 Acoustic Noise - 921.3 Mathematical Transformations
Numerical data indexing:Frequency 3.20E+04Hz, Percentage 1.00E+02%, Percentage 9.446E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.021

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395514
Title:Effects of LED light on the ripening regulation of green mature banana during storage and transportation
Title of translation:LED光照对青熟香蕉贮运中后熟调控的影响
Authors:Liu, Bangdi (1, 2); Zhang, Yali (1, 2, 3); Ke, Zehua (1, 2, 3); Sun, Jing (1, 2); Zhou, Xinqun (1, 2); Sun, Jie (1, 2)
Author affiliation:(1) Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (2) Key Laboratory of Agro-Products Postharvest Handling, Ministry of Agriculture and Rural Affairs, Beijing; 100121, China; (3) College of Life Science and Food Engineering, Hebei University of Engineering, Handan; 056038, China
Corresponding authors:Sun, Jing(cynthiasj@163.com); Sun, Jing(cynthiasj@163.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:295-302
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">The purpose of this research was to clarify the effects of monochromatic lights with different fixed bands on the post-ripeness regulation in typical respiration fruits. Specifically, a systematic investigation was made on the effects of red, orange, yellow, green, blue, and purple LED lights on delaying and accelerating low maturity bananas ripening during simulated storage and transportation at room temperature (20±0.7 ℃). The low maturity of bananas ripening and quality changes were observed under different colors of LED lighting treatment. The results showed that the >440-505 nm blue and 400-440 nm violet LED light greatly contributed to inhibiting the intensity respiratory of banana and release quantity of ethylene. Two colors of LED light were utilized to effectively delay the shelf storage time of banana for 2 days, while decreasing the color turn and decomposition of cellulose and starch. Subsequently, the final firmness of bananas under the blue and purple lighting treatment after 8 days was 2.5 and 0.1 N higher than the CK group. In addition, the total sugars content of bananas in the blue lighting group was 51.71% of CK. Hence, better preservation was achieved under the blue and purple LED lighting treatment, where the bananas post-ripening was inhibited to prolong the freshness preservation period. The >640-700 nm red and >605-640 nm orange LED lighting treatments were utilized to effectively promote 2 days earlier on bananas respiration and ethylene peak. In addition, the red light was used to increase the respiratory peak by 24.20% and the ethylene release peak by 23.97%, compared with the CK group. More importantly, the peel color of bananas turned more outstandingly under red and orange light, and the total color difference (ΔE) reached 94.70 and 83.25 at full ripeness. The red-orange light was also employed to stimulate the decomposition of starch and cellulose, thus speeding up the accumulation of bananas soluble sugar and softening. Therefore, it was found that both red and orange LED lights were selected to effectively accelerate the ripening of bananas. Among them, the orange light was used as an accurate of ripening, due to its intensity less than the red light. Additionally, the bananas exposed to yellow and green LED lighting showed premature rotting and post-ripening disorder. Moreover, the banana peels rotted seriously after 4 days, but the color differences (ΔE) of peels were 40.35 and 46.23 less than those of the CK group. Particularly, the>565-605 nm yellow and >505-565 nm green light also prevented the rapid decline of banana firmness, but accelerated the cellulose decomposition, compared with the CK group. At the same time, the pectin contents in the yellow and green light group were lower than those in CK. The changes of cellulose, pectin, and hardness varied in the groups. A comprehensive analysis was performed on the texture, sugar content, and respiration of bananas. It was found that the six LED light colors treatments were used to delay ripening, promote ripening and disturb ripening. Correspondingly, the red light was selected to promote banana ripening faster, the orange light to promote banana ripening slower, the blue light to inhibit post-ripening and delayed senescence better than purple light, the yellow and green light to disrupt the normal post-ripening of banana. In conclusion, monochromatic LED lighting can be widely expected to serve as physical preservation to delay or accelerate ripeness in the process of storage and transportation of bananas. This finding can provide a theoretical basis for the ripening regulation on more respiration fruits and vegetables.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:44
Main heading:Citrus fruits
Controlled terms:Cellulose - Color - Colorimetry - Ethylene - Light emitting diodes - Starch - Sugars
Uncontrolled terms:Green light - Green mature banana - LED lighting - LED lights - Preservation - Red light - Ripening - Ripening regulation - Storage and transportations - Sugar content
Classification code:714.2 Semiconductor Devices and Integrated Circuits - 741.1 Light/Optics - 804.1 Organic Compounds - 811.3 Cellulose, Lignin and Derivatives - 815.1.1 Organic Polymers - 821.4 Agricultural Products - 941.4 Optical Variables Measurements
Numerical data indexing:Age 1.096E-02yr, Age 2.192E-02yr, Age 5.48E-03yr, Force 1.00E-01N, Force 2.50E+00N, Percentage 2.397E+01%, Percentage 2.42E+01%, Percentage 5.171E+01%, Size 4.00E-07m to 4.40E-07m, Size 4.40E-07m to 5.05E-07m, Size 5.05E-07m to 5.65E-07m, Size 5.65E-07m to 6.05E-07m, Size 6.05E-07m to 6.40E-07m, Size 6.40E-07m to 7.00E-07m
DOI:10.11975/j.issn.1002-6819.2021.20.033

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395568
Title:Lodging resistance prediction of maize varieties based on support vector machine and ReliefF algorithm
Title of translation:基于支持向量机和ReliefF算法的玉米品种抗倒伏预测
Authors:Zhang, Tianliang (1, 2); Zhang, Dongxing (1, 2); Cui, Tao (1, 2); Yang, Li (1, 2); Ding, Youqiang (1, 2); Xie, Chunji (1, 2); Du, Zhaohui (1, 2); Zhong, Xiangjun (1, 2)
Author affiliation:(1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Soil-Machine-Plant System Technology of Ministry of Agriculture, Beijing; 100083, China
Corresponding authors:Yang, Li(yl_hb68@126.com); Yang, Li(yl_hb68@126.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:226-233
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Maize is one of the main food crops in the world. The lodging of maize has posed a serious challenge on the yield and mechanized harvesting in modern agriculture. Current identification methods cannot fully meet the lodging resistance and long breeding cycle of maize varieties, due to the time-consuming and laborious tasks. In this study, hyperspectral imaging technology was combined with statistical learning to predict the lodging resistance of maize varieties during the vegetative growth period. A field trial was also carried out in 2018 and 2019. The hyperspectral images were then collected for the top leaves of 8 corn varieties with and without lodging resistance at the 9-leaf stage. The experimental procedure was as follows. A threshold segmentation was first utilized to identify the leaf area. The K-means clustering was then used to divide the leaf into three areas: normal reflection, dark reflection, and leaf vein area. The average spectral curve was finally extracted in the normal reflection area, in order to analyze the data characteristics of lodging-resistant and lodging samples. The Kennard Stone was selected to sort the sample data of each species. Two parts of the set sample were also divided, including the training and test set at a ratio of 3:1. The division of each variety was integrated into the final training and test set data, in order to obtain an evenly distributed dataset of each variety. As such, there were 378 training and 120 test set samples in the 2018 test, while there were 383 training and 120 test set samples in the 2019 test. The filtering feature selection Relevant Features (ReliefF) and Principal Component Analysis (PCA) were selected to mine the spectral classification features of lodging-resistant varieties and lodging varieties. Specifically, a different number of the nearest neighbors in ReliefF was set to determine some features, according to the stability of feature variables. The redundant features were often selected with a high correlation in adjacent bands. Correspondingly, the PCA was first performed on the spectral data, thereby selecting principal components without redundant features using the ReliefF. The classification models of ReliefF- Support Vector Machine (SVM) and PCAReliefF-SVM were established, where the original spectral data features were selected by the ReliefF, and the principal component features were selected by the PCAReliefF. The grid search was also selected to optimize the penalty and kernel parameters in the SVM model for a better prediction of the model. First, cross-validation was used on the training set data to optimize the number of selected features. 40 and 50 features in the trials in 2018 and 2019 were selected to build the model, in order to balance the accuracy of the model and the complexity of calculation. All the samples were then used in the training set, where the final parameters were used for model training. The accuracy rates of prediction in the PCAReliefF-SVM model were 85.00% and 85.83% in 2018 and 2019, respectively. In the ReliefF-SVM model, the prediction accuracy rates were 84.17% and 84.17% in 2018 and 2019, respectively. It indicated that the PCAReliefF-SVM model performed better prediction. The ROC curve was also used to evaluate the performance of the model. It was found that the ROC curve in the PCAReliefF-SVM modeling almost completely "enclosed" the ROC curve in the ReliefF-SVM, indicating a better performance of the PCAReliefF-SVM model. As such, hyperspectral imaging was used for the early classification of maize varieties, particularly for the overwhelm resistance. Consequently, the findings can provide a reliable idea for the maize resistance to overwhelm using spectral extraction, feature analysis, and modeling prediction.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Support vector machines
Controlled terms:Classification (of information) - Feature extraction - Grain (agricultural product) - Hyperspectral imaging - K-means clustering - Principal component analysis - Spectroscopy - Vegetation
Uncontrolled terms:Lodging resistance - Lodging resistant - Maize - Principal-component analysis - ReliefF - Support vector machine models - Support vectors machine - Test sets - Training sets - Variety
Classification code:716.1 Information Theory and Signal Processing - 723 Computer Software, Data Handling and Applications - 746 Imaging Techniques - 821.4 Agricultural Products - 903.1 Information Sources and Analysis - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 8.417E+01%, Percentage 8.50E+01%, Percentage 8.583E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.026

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395501
Title:Monitoring of sugar beet growth using canopy spectrum and structural characteristics with UAV images
Title of translation:基于无人机影像的冠层光谱和结构特征监测甜菜长势
Authors:Wang, Qing (1); Che, Yingpu (1); Chai, Honghong (1); Shao, Ke (2); Yu, Chao (3); Li, Baoguo (1); Ma, Yuntao (1)
Author affiliation:(1) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China; (2) Institute of Biotechnology, Inner Mongolia Academy of Science and Technology, Hohhot; 010010, China; (3) College of Agriculture, Inner Mongolia Agricultural University, Hohhot; 010019, China
Corresponding author:Ma, Yuntao(yuntao.ma@cau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:90-98
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A sugar beet is one of the most important cash crops in northern China. It is a high demand for the rapid, accurate, and high-throughput acquisition of the fresh weight of aboveground and root, the sugar content of root, and the chlorophyll content of aboveground in the production of sugar beet. An Unmanned Aerial Vehicle (UAV) can serve as a significant approach, due to its flexibility, low cost, and high spatiotemporal resolution. In this study, a UAV equipped with digital and multispectral cameras was utilized to capture the images of sugar beet during the leaf clusters, root tuber, sugar growth, and accumulation period, thereby extracting the structural and spectral characteristics of the canopy. The estimation models were also established for the various indexes using the Random Forest Regression (RFR) and Partial Least Squares Regression (PLSR), including the fresh weight of shoot and root tuber, the sugar content of root tuber, and Soil Plant Analysis Development (SPAD) value during the whole period of sugar beet. The results showed that the RFR and PLSR model performed well to predict the fresh weight and sugar content of shoot and root tuber, with the coefficient of determination R<sup>2</sup> ranging from 0.9 to 0.94 and from 0.88 to 0.9, respectively, while the relative Root Mean Square Error (rRMSE) ranging from 7.6% to 17% and from 8.8% to 20%, respectively. Both models presented weak predictions for the SPAD values, where the R<sup>2</sup> values were only 0.66 and 0.67, respectively. Furthermore, a Permutation Importance (PIMP) was used to screen the more sensitive variables with the dominated impacts on the prediction, in order to reduce the size of the input variable set for the less cost and complexity of data collection. As such, the optimal prediction models of RFR and PLSR were achieved for the growth monitoring of sugar roots. It was found that excellent predictions were achieved on the fresh weight and sugar content of shoot and root tuber, with the R<sup>2</sup> value ranging from 0.89 to 0.94, and from 0.74 to 0.91, respectively, and the rRMSE value ranging from 7.3% to 19% and from 7.6% to 19%, respectively. Nevertheless, the RFR and PLSR model presented weak predictions for the SPAD values, where the R<sup>2</sup> values were only 0.65 and 0.68, respectively. Correspondingly, the accuracy of the RFR model was slightly better than that of the PLSR model. More importantly, the PIMP variable screening can be widely expected to reduce the complexity of data collection with optimal accuracy. Consequently, the canopy structure and spectral features obtained by UAVs can be utilized to quickly and accurately monitor the growth and sugar content of sugar beet. The finding can provide a strong reference to estimate the root active substances of tubers crops using UAV proximity.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:37
Main heading:Regression analysis
Controlled terms:Antennas - Costs - Crops - Decision trees - Forecasting - Least squares approximations - Mean square error - Sugar beets - Throughput - Tubes (components) - Unmanned aerial vehicles (UAV)
Uncontrolled terms:Canopy characteristics - Fresh weight - Partial least square regression - Partial least squares regression models - Plant analysis - Random forest regression - Random forests - Root tubers - Structural characteristics - Sugar content
Classification code:619.1 Pipe, Piping and Pipelines - 652.1 Aircraft, General - 821.4 Agricultural Products - 911 Cost and Value Engineering; Industrial Economics - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 921.6 Numerical Methods - 922.2 Mathematical Statistics - 961 Systems Science
Numerical data indexing:Percentage 7.30E+00% to 1.90E+01%, Percentage 7.60E+00% to 1.70E+01%, Percentage 7.60E+00% to 1.90E+01%, Percentage 8.80E+00% to 2.00E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.010

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395542
Title:Monitoring of maize phenotypic traits using super-resolution reconstruction and multimodal data fusion
Title of translation:基于超分辨率重建和多模态数据融合的玉米表型性状监测
Authors:Che, Yingpu (1); Wang, Qing (1); Li, Shilin (1); Li, Baoguo (1); Ma, Yuntao (1)
Author affiliation:(1) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China
Corresponding author:Ma, Yuntao(yuntao.ma@cau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:169-178
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">High-throughput phenotyping has posed an urgent challenge on plant genetics, physiology, and breeding at present. Particularly, traditional manual cannot meet the needs of high-throughput phenotyping for breeding, due mainly to time-consuming and labour-intensive work with a limited sample size. Alternatively, the Unmanned Aerial Vehicle (UAV) Remote Sensing can be widely expected to serve as an important tool for crop phenotypic parameters. The main reason can be the high temporal and spatial resolution, fast image acquisition, easy operation and portability, as well as relatively low cost. However, it is also inevitable to balance the flight height and image resolution or accuracy during image acquisition. Efficient techniques are urgently needed to reconstruct the high-resolution images without lossing the measurement accuracy, while improving the spatial resolution and image acquisition. In this study, the maize phenotypic traits were effectively monitored using super-resolution reconstruction and multimodal data fusion. The UAV image sequences of maize were also captured at seedling, 6th leaf, 12th leaf, tasseling, and milk stage. The super-resolution images were then reconstructed combined with the wavelet transform and bicubic interpolation. The reconstructed images presented higher reconstruction quality, less distortion with peak signal-to-noise ratio of 21.5, structure similarity of 0.81, and mean absolute error ratio of 6.4%. A lower error was also achieved for the plant height and biomass estimation with the root mean square error of 3.9 cm and 0.19 kg, respectively. Ground Sampling Distance (GSD) of the reconstructed image at a flight height of 60 m was similar to that of the original image at a flight height of 30 m. Subsequently, the UAV at a flight height of 60 m was utilized to scan 0.2 hm² larger fields per minute than that at a flight height of 30 m. The plant height, canopy coverage and vegetation index were also extracted from the original and reconstructed images. Leaf area index was calculated by point cloud reconstructed by oblique photography. The original shape of point cloud was remained, while point cloud was compressed for a higher efficiency using 3-D voxel filtering. Specifically, a better correlation was achieved, where the measured LAI was the slope of 0.72 and the root mean square error of 0.14. All canopy structure, spectrum and population structure parameters were then used to construct estimation models of above ground biomass using single characteristic parameter and multimodal data. A higher estimation accuracy of above ground biomass was obtained by multimodal data fusion, compared with a single parameter with the coefficient of determination was 0.83 and root mean square error of 0.19 kg. Therefore, a combination of image super-resolution reconstruction and multimodal data fusion can be widely expected to deal with the canopy saturation for higher spatial resolution and estimation accuracy, indicating fully meeting the demand for higher throughput of data acquisition. Meanwhile, the finding can provide a highly effective and novel solution to the estimation of above ground biomass. More importantly, the correlation between genotype and phenotype can also be extended to cultivate high-quality maize varieties suitable for mechanized production.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:32
Main heading:Unmanned aerial vehicles (UAV)
Controlled terms:Antennas - Errors - Image acquisition - Image compression - Image enhancement - Image quality - Image reconstruction - Image resolution - Mean square error - Plants (botany) - Remote sensing - Signal to noise ratio - Wavelet transforms
Uncontrolled terms:Aboveground biomass - High-throughput phenotyping - Maize - Multimodal data fusion - Phenotypic traits - Point-clouds - Reconstructed image - Remote-sensing - Root mean square errors - Super-resolution reconstruction
Classification code:652.1 Aircraft, General - 716.1 Information Theory and Signal Processing - 723 Computer Software, Data Handling and Applications - 921.3 Mathematical Transformations - 922.2 Mathematical Statistics
Numerical data indexing:Mass 1.90E-01kg, Percentage 6.40E+00%, Size 3.00E+01m, Size 3.90E-02m, Size 6.00E+01m
DOI:10.11975/j.issn.1002-6819.2021.20.019

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395532
Title:Research progress and prospect of pesticide droplet deposition characteristics
Title of translation:农药雾滴沉积特性研究进展与展望
Authors:Kang, Feng (1); Wu, Xiaoyi (1); Wang, Yaxiong (1); Zheng, Yongjun (2); Li, Shougen (1); Chen, Chongchong (1)
Author affiliation:(1) School of Technology, Beijing Forestry University, Beijing; 100083, China; (2) College of Engineering, China Agricultural University, Beijing; 100083, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:1-14
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Pesticide droplets can rebound, splash, and roll off the target surface during spraying, due mainly to insufficient wettability. The resulting environmental pollution has seriously threatened ecological stability and safety. However, the correlative mechanism of droplet deposition is still under exploration at present. It is necessary to explore the characteristics of effective droplet deposition for pest control. This study aims to review current researches on droplet deposition ranging from microdynamics of a single droplet and drift characteristics of the droplet group. The final deposition assessment and the bottleneck were also addressed, in order to clarify the research perspective of pesticide deposition. A single droplet model was essential to the impact mechanism of the droplet group because the pesticide droplets hit the target surface in the form of a single droplet during spraying. The previous reports on the deposition of the single droplet mainly contributed to the observation technologies, the influencing factors at the interface behavior of the single droplet, and the modeling of the single droplet hitting the target surface. However, the deposition behavior in the actual work depended mainly on the droplet distribution and canopy structure. There were two approaches to explore the deposition and drift characteristics in the spray field through the droplet group at present. One approach was that the observation and simulation were utilized to determine the movement of droplets in the spray field, thereby establishing the relationship between deposition behavior and amount. Another was to calculate the final deposition through actual experiments or simulation techniques, including the direct measurement of deposition on the surface of leaves, and the indirect measurement represented by the amount of drift in the air or on the ground. The research of droplet group was introduced to the distribution characteristics, deposition collection, and detection, as well as droplet group modeling. More importantly, a further combined modeling was necessary to accurately estimate the deposition behavior and the volume of deposited pesticides. The following suggestions can be drawn: 1) To establish the relationship between the single droplet and the droplet group modeling through the three-dimensional atomization field; 2) To estimate the amount of adhesion liquid after a single droplet hits the wall through image processing; 3) To explore the influence of wetted surfaces on deposition behavior; 4) To establish plant models in different growth periods. The finding can be widely expected to provide a strong reference for the research of pesticide deposition and pest control technologies.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:151
Main heading:Deposition
Controlled terms:Drops - Image processing - Pesticides - Plants (botany) - Wetting
Uncontrolled terms:Deposition behaviours - Drift - Droplet deposition - Droplet group - Interface behavior - Pesticide deposition - Pesticide droplets - Single droplet - Spray field - Target surface
Classification code:723.2 Data Processing and Image Processing - 802.3 Chemical Operations - 803 Chemical Agents and Basic Industrial Chemicals
DOI:10.11975/j.issn.1002-6819.2021.20.001

Database:Compendex
Compilation and indexing terms, Copyright 2022 Elsevier Inc.

Accession number:20215211395556
Title:Acoustic characteristics of the feeding pellets for Micropterus salmoides in circulating aquaculture
Title of translation:循环水养殖大口黑鲈摄食颗粒饲料的声学特征
Authors:Cao, Xiaohui (1, 2); Liu, Huang (2); Qi, Renyu (1, 2); Zhang, Chenglin (2); Liu, Shijing (2)
Author affiliation:(1) College of Fisheries and Life Science, Shanghai Ocean University, Shanghai; 201306, China; (2) Fishery Machinery and Instrument Research Institute, Chinese Academy of Fishery Sciences, Shanghai; 200092, China
Corresponding author:Liu, Huang(liuhuang@fmiri.ac.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:219-225
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A passive acoustic technology has been widely used to monitor the behavior of aquatic organisms for the intelligent feeding system in recent years. Taking six sizes of Micropterus salmoides as research objects, this study aims to acquire the acoustic signals of pellet feeding in circulating aquaculture using passive acoustic techniques. The signals were first identified to classify for the post-processing using simultaneous audio and video recordings during feeding. The feeding activity was then quantified to extract and screen the characteristic parameters from the acoustic signals. Six kinds of pre-processing were utilized for the feeding sound signals, including A/D conversion, denoise, pre-emphasis, windowed framing, and endpoint detection. A Fast Fourier transform, real-time, and Mel frequency cepstrum methods were also used to extract the time- and frequency-domain features of each swallowing signal in the complete feeding acoustic signal, in order to obtain the correlation between each acoustic feature parameter and the swallowing order. Specifically, the swallowing interval, the peak-to-peak value of voltage, and the maximum amplitude were extracted from the time-domain features. It was found that the swallowing interval was positively correlated with the order of swallowing (r >0.68), whereas, the maximum and range amplitude was negatively correlated with the order of swallowing (r <-0.61), but there was no significant difference between the correlation coefficient of three time-domain characteristic parameters. Furthermore, the maximum sum of power intensity and integral value was extracted from the power spectrum of each swallowing signal. Among them, P=0.05 was assumed as the basis to evaluate the integral value of power, where a more stable and reliable measurement was achieved for the characteristic parameters of feeding activity. In addition, the formant frequency and the average Mel cepstrum coefficient (AMFCC) were extracted to find each acoustic signal of feeding mainly in 4.2-7.4 kHz. More importantly, the third coefficient in AMFCC presented an outstanding and stable peak. Particularly, the feeding activity decreased significantly, as the feeding sequence increased. The extraction of power integral parameters depended significantly on subjective factors, although both time domain and frequency domain parameters presented an excellent correlation with the order of swallowing. The feature parameters of the time domain also behaved more reliable stability. Subsequently, the feature parameters for the activity of eating were screened out, according to the correlation between the acoustic feature parameters of ingestion and the order of swallowing. Correspondingly, the feature parameters of multi-feature fusion can be expected to better quantify the feeding activity, indicating the best choice for the swallowing interval and peak-to-peak value of voltage. The finding can also provide theoretical support to identify the sound signal of farmed fish in the intelligent feeding system.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:27
Main heading:Time domain analysis
Controlled terms:Acoustic waves - Aquaculture - Audio acoustics - Biomolecules - Fast Fourier transforms - Feeding - Frequency domain analysis - Meats - Video recording
Uncontrolled terms:Acoustic signals - Characteristics parameters - Feature parameters - Feeding activities - Feeding behavior - Feeding system - Micropteri salmoide - Micropterus - Passive acoustics - Sound signal
Classification code:461.9 Biology - 691.2 Materials Handling Methods - 716.4 Television Systems and Equipment - 751.1 Acoustic Waves - 801.2 Biochemistry - 821.3 Agricultural Methods - 822.3 Food Products - 921 Mathematics - 921.3 Mathematical Transformations
Numerical data indexing:Frequency 4.20E+03Hz to 7.40E+03Hz
DOI:10.11975/j.issn.1002-6819.2021.20.025

Accession number:20215211395549
Title:Monitoring of winter wheat growth under UAV using variation coefficient method and optimized neural network
Title of translation:变异系数法结合优化神经网络的无人机冬小麦长势监测
Authors:Xu, Yunfei (1); Cheng, Qi (1); Wei, Xiangping (2); Yang, Bin (1); Xia, Shasha (3); Rui, Tingting (1); Zhang, Shiwen (3)
Author affiliation:(1) School of Spatial Informatics and Geomatics Engineering, Anhui University of Science and Technology, Huainan; 232001, China; (2) Huaibei Mining (Group) Co. Ltd, Huaibei; 235001, China; (3) School of Earth and Environment, Anhui University of Science and Technology, Huainan; 232001, China
Corresponding author:Zhang, Shiwen(mamin1190@126.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:71-80
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Accurate and rapid acquisition of growth information has been one of the most important steps for winter wheat production in agricultural development and management decision-making. Most previous achievements focus on the monitoring of crop growth using Unmanned Aerial Vehicle (UAV) in recent years. Among them, the most extensive reports can be chlorophyll, biomass, plant height, and water content. Taking the winter wheat as the research object, this study aims to monitor the growth characteristics of the plant under a UAV using the Coefficient of Variation (CV) and optimized neural network. A Comprehensive Growth Monitoring Indicators (CGMI<inf>CV</inf>) was also considered to integrate with the CV and different indexes, including the biomass, plant height, plant water, and chlorophyll content. In addition, the multispectral data of UAV was obtained, such as red, green, red edge, and near-infrared band. Subsequently, 16 multispectral vegetation indices were selected to analyze the correlation between the vegetation index and CGMI<inf>CV</inf>, according to the characteristic band range of crops. The variance expansion factor was then calculated to screen the input variables of the model. Finally, six optimal vegetation indices were selected as the input variables of the model. As such, the growth model of winter wheat was established using the Partial Least Squares Regression (PLSR), Random Forest (RF), and Back Propagation Neural Networks (BPNN). Correspondingly, an optimal growth inversion model of winter wheat was achieved, including the determining coefficient (R<sup>2</sup>), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), according to the combined evaluation indexes. More importantly, Genetic Algorithm (GA) was utilized to optimize the growth inversion model for the whole region. The spatial distribution of winter wheat growth was then obtained in the study area. The results showed that the correlation between the CGMI<inf>CV</inf> of winter wheat was much higher than that of the single index, where the most outstanding one was the Soil Plant Analysis Development (SPAD). The best inversion model of CGMI<inf>CV</inf>-BPNN was achieved for the growth of winter wheat, where a determination coefficient R<sup>2</sup> was 0.71, and the accuracy of the model was 26.79% higher than that of the traditional one (CGMI<inf>mean</inf>-BPNN), fully meeting the current accuracy for the comprehensive monitoring of crop growth. The stability of the optimized CGMI<inf>CV</inf>-GA-BPNN model was significantly better than that of CGMI<inf>CV</inf> -BPNN. the mean relative error median was reduced by 22.22%, and the determination coefficient R<sup>2</sup> was also increased. The CGMI<inf>CV</inf>-GA-BPNN model was then applied for the growth distribution map of winter wheat in the whole study area. More than half of winter wheat was concentrated in grade III, followed by grade I. It inferred that the overall growth of winter wheat was relatively stable. At the same time, it was also found that the optimized CGMI<inf>CV</inf> -BPNN model can be used to integrate the multiple growth factors of winter wheat, indicating a better performance to quantify the growth monitoring of regional winter wheat. The findings can provide an important reference for the growth monitoring of winter wheat in crop production.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:47
Main heading:Unmanned aerial vehicles (UAV)
Controlled terms:Antennas - Backpropagation - Chlorophyll - Crops - Decision trees - Ecology - Errors - Forestry - Genetic algorithms - Infrared devices - Least squares approximations - Maximum likelihood - Mean square error - Neural networks - Remote sensing - Torsional stress - Vegetation
Uncontrolled terms:Back-propagation neural networks - Coefficient of variation method - Coefficients of variations - Comprehensive growth monitoring indicator - Growth monitoring - Monitoring indicators - Remote-sensing - Variation method - Vegetation index - Winter wheat
Classification code:454.3 Ecology and Ecosystems - 652.1 Aircraft, General - 723.4 Artificial Intelligence - 804.1 Organic Compounds - 821.0 Woodlands and Forestry - 821.4 Agricultural Products - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 921.6 Numerical Methods - 922.1 Probability Theory - 922.2 Mathematical Statistics - 961 Systems Science
Numerical data indexing:Percentage 2.222E+01%, Percentage 2.679E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.008

Accession number:20215211395507
Title:Disinfection efficacy of slightly acidic electrolyzed water sprayed on Salmonella on the chicken manure contaminated eggs
Title of translation:微酸性电解水对受鸡粪液污染鸡蛋表面沙门氏菌的喷雾消毒效果
Authors:Yuan, Xingyun (1); Zhang, Beibei (1); Mo, Qingnan (1); Zang, Yitian (1)
Author affiliation:(1) Nanchang Key Laboratory of Animal Health and Safety, College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang; 330045, China
Corresponding author:Zang, Yitian(zangyitian1@126.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:333-338
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Salmonella enteritidis (S. enteritidis) infection has been recognized as one of the most common bacterial causes of human gastroenteritis worldwide, and was closely associated with eggs. Slightly Acidic Electrolyzed Water (SAEW), as an environmentally-friendly disinfectant, was often be studied in disinfecting eggshell surfaces to remove dirt and pathogenic microorganisms. However, the efficiency of SAEW was often be affected by the presence of manure. In our study, disinfection efficiency of SAEW in spraying treatment method was evaluated on manure and S. enteritidis mixture contaminated eggs, to verify if this method could be used to alleviate the interference of chicken manure on disinfection effectiveness. Eggs were first sprayed with different solutions (H<inf>2</inf>O, ERW and SAEW) to clean the manure in different times (6, 12, 18 and 24 s), and then sprayed with different disinfectants (H<inf>2</inf>O, ERW and SAEW) with different available chlorine concentration (ACC, 5, 15, 25 and 35 mg/L) in different times (6, 12, 18 and 24 s). Eggs were divided into 5 groups: H<inf>2</inf>O+H<inf>2</inf>O group (Sterilized H<inf>2</inf>O sprayed for cleaning and disinfection treatment), ERW+ERW group (ERW single sprayed for cleaning and disinfection treatment), ERW+SAEW group (ERW sprayed for cleaning treatment, then SAEW used for disinfection treatment) and SAEW+SAEW group (SAEW single sprayed for cleaning and disinfection treatment). The inactivation models of SAEW+SAEW and ERW+SAEW group with different ACCs, cleaning times and disinfection times were developed using multiple linear regression analysis. After treatment, decontamination of eggs with SAEW single sprayed group showed an equivalent or higher bactericidal effect compared to other treatments. A complete inactivation of S. enteritidis (6.26 lg cfu/egg) on the surface of shelled egg samples resulted from SAEW+SAEW group and ERW+SAEW group at an ACC of 25 and 35 mg/L for 18 and 24 s, respectively. Moreover, the established model of SAEW+SAEW and ERW+SAEW group had a good fit-quantified by the determination coefficient R<sup>2</sup> (0.933 and 0.926) and adjusted R<sup>2</sup> (0.930 and 0.923). The model was validated with additional random 8 conditions within the experimental domain. The predicted value showed a good agreement with the actual values, for the points of response values were very close to the line of 100% correlation. The model was valid and the results demonstrated that the cleaning time, disinfection time and ACC significantly affected the S. enteritidis. enteritidis reduction (P < 0.01). In addition, the ACC was ranked as the most important factor in the three factors by analysing the parameter coefficients in the model equation. As previously stated, manure was a strong limiting factor for disinfection of SAEW due to it can react with HClO in SAEW in an oxidative manner, resulting in a reduction of the ACC. From another point of view, it also meaned that manure could be effectively removed by the SAEW. Therefore, SAEW also has a good organic removal function as well as an excellent disinfection function. In conclusion, our results demonstrated that the SAEW could be used in disinfecting manure contaminated eggshell surfaces to remove S. enteritidis in single sprayed treatment way.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:27
Main heading:Salmonella
Controlled terms:Chlorine - Disinfectants - Disinfection - Efficiency - Fertilizers - Fumigation - Linear regression - Manures - Ozone
Uncontrolled terms:% reductions - Chicken manure - Cleaning and disinfections - Cleaning treatment - Disinfection treatments - Egg - Electrolytics - Salmonella enteritidis - Slightly acidic electrolytic water - Slightly acidic electrolyzed waters
Classification code:461.9 Biology - 803 Chemical Agents and Basic Industrial Chemicals - 804 Chemical Products Generally - 821.2 Agricultural Chemicals - 821.5 Agricultural Wastes - 913.1 Production Engineering - 922.2 Mathematical Statistics
Numerical data indexing:Mass density 2.50E-02kg/m3, Mass density 3.50E-02kg/m3, Percentage 1.00E+02%, Time 1.80E+01s, Time 2.40E+01s
DOI:10.11975/j.issn.1002-6819.2021.20.037

Accession number:20215211395595
Title:Suitable particle size range of sand filter layers based on fractal dimension characteristics
Title of translation:基于分形维数特征的砂滤层适宜粒径范围
Authors:Li, Jinghai (1, 2); Zhai, Guoliang (1); Liu, Qingxia (2); Song, Lei (1); Cai, Jiumao (1)
Author affiliation:(1) Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences/Key Laboratory of Water-Saving Agriculture of Henan Province, Xinxiang; 453002, China; (2) School of Civil and Architectural Engineering, Anyang Institute of Technology, Anyang; 455000, China
Corresponding author:Liu, Qingxia(13837246449@163.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:162-168
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">This study aims to evaluate the filtration performance of sand filters using fractal dimensions. Three kinds of sand filters were also selected with particle size in the range of 1.0-1.18, >1.18-1.4, and >1.4-1.7 mm. The Yellow River sediment in the people's Victory Canal was collected as impurity particles in the raw water. The distribution of particle size in the Yellow River sediment was measured using a laser diffraction particle size analyzer (Mastersizer 3000, Dandong Baite Instrument Co., Ltd). It was found that the calculated mean values of skewness and kurtosis were 0.12 and -0.01, respectively, for the samples from the Yellow River sediment, indicating an outstanding normal distribution. Additionally, the samples were also collected from the Yellow River sediment in Lankao County, thereby verifying the distribution of particle size. It was found that the skewness and kurtosis values of the sediment sample in Lankao County were -0.11 and -0.23, respectively, where the frequency distribution of particle size also conformed to the normal distribution. An industrial CT scanner (C16M3201, Luoyang Tengda Testing Service Co., Ltd) was used to map the filter layer. The image processing and pixel coverage were utilized to calculate the porosity of cross section, the box-counting fractal dimension, and the ratio of the minimum to the maximum aperture (aperture ratio) in the three kinds of sand filter layers. The results showed that the porosities were 0.421, 0.431, and 0.439, respectively, while the box-counting fractal dimensions were 1.695, 1.709 and 1.726, respectively, and the aperture ratio was 1/17, 1/18, and 1/21, respectively, for the three types of layers. Then, the applicability of fractal theory was also evaluated for the quartz sand filters. Subsequently, a fractal model of filtration probability was established for the sand filters. The ranges of pore diameter in the three kinds of sand filters were 59.5-1 002, 66.9-1 220, and 72.9-1 503 μm, respectively. In the sediment of the Yellow River from the people's Victory Canal, the probabilities of impurity particles above 100 um passing through the sand filter were 0.67%, 0.81%, and 0.93%, respectively. In the Yellow River Sediment from Lankao County, the probabilities of impurity particles above 100 μm passing through the sand filter were 0.62%, 0.80%, and 0.91%, respectively. It inferred that the presence of surface filtration was proved theoretically. A systematic investigation was also made on the influence of surface filtration on Backwash frequency. Consequently, an optimal filter layer was achieved to reduce the surface filtration, particularly with the particle size in the range of >1.4-1.7 mm suitable for sand filters. The finding can provide strong support to explore the internal structure of sand filters and the selection of filter material.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:32
Main heading:Particle size
Controlled terms:Computerized tomography - Erosion - Fractal dimension - Higher order statistics - Normal distribution - Particle size analysis - Porosity - Quartz - Rivers - Sand - Sediments
Uncontrolled terms:Box-counting - Box-counting fractal dimension - Filtration performance - Images processing - Particles sizes - Quartz sand - Quartz sand filter - Sand filter - Surface filtration
Classification code:482.2 Minerals - 483 Soil Mechanics and Foundations - 483.1 Soils and Soil Mechanics - 723.5 Computer Applications - 921 Mathematics - 922.1 Probability Theory - 922.2 Mathematical Statistics - 931.2 Physical Properties of Gases, Liquids and Solids - 951 Materials Science
Numerical data indexing:Percentage 6.20E-01%, Percentage 6.70E-01%, Percentage 8.00E-01%, Percentage 8.10E-01%, Percentage 9.10E-01%, Percentage 9.30E-01%, Size 1.00E-04m, Size 1.40E-03m to 1.70E-03m, Size 5.03E-04m
DOI:10.11975/j.issn.1002-6819.2021.20.018

Accession number:20215211395642
Title:Spatial distribution and compensation strategy of land fallow based on quality-risk in arid areas
Title of translation:基于"质量-风险"的干旱区休耕空间布局及补偿策略
Authors:Zeng, Qingmin (1); Wang, Yurong (2); Wang, Jing (3); Chen, Ligen (1); Huang, Jinsheng (4); Liu, Xinping (5)
Author affiliation:(1) College of Public Administration, Nanjing Agricultural University, Nanjing; 210095, China; (2) Shanghai Academy of Agricultural Sciences, Institute of Agricultural Science and Technology Information, Shanghai; 201403, China; (3) College of Economics and Management, Northwest A&F University, Yangling; 712100, China; (4) School of Business, Anhui University of Technology, Maanshan; 243002, China; (5) College of Management, Xinjiang Agricultural University, Urumqi; 830052, China
Corresponding author:Chen, Ligen(lgchen@njau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:266-276
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A diversified fallow ecological compensation is an inevitable choice for the sustainable development of agriculture in China. It is very necessary to explore the spatial distribution of fallow land for the higher efficiency of ecological compensation for fallow in arid areas. Taking the Kaidu-Kongque River basin in Xinjiang as an example, this article aims to propose different compensation strategies for different zones, thereby determining the spatial layout of fallow, considering the quality of cultivated land and risk of land degradation. The specific procedures were: 1) An evaluation index system of cultivated land quality was established to select the indicators from two aspects of soil physical and chemical properties, and cultivation convenience. A comprehensive evaluation was then made for the quality of cultivated land. 2) MEDALUS-ESAs model was selected to estimate potential risks of land degradation in the basin, where four indicators included soil, climate, vegetation and land use. 3) The Z-score was also applied for the quality score of cultivated land and risk index of land degradation. The standardized value was divided into four quadrants, according to the coordinate axis to determine the spatial distribution of fallow. Specifically, the cultivated land with "low quality and low risk" was classified as a priority fallow area, "high quality-low risk" was classified as a sub-priority fallow area, "low quality-high risk" was classified as restricted fallow areas, and "high-quality-high-risk" was classified as fallow area. 4) Different compensation strategies were finally proposed for fallow, according to different zones. The results showed that: 1) There was a fair overall quality of cultivated land in the whole Kaidu-Kongque River Basin, but slightly good in local areas. The spatial pattern of land degradation risk was "low in the northern, high in the southern". 2) The area of cultivated land located in the priority fallow area was 67 814.60 hm<sup>2</sup>, mainly distributed in the western part of Kongque River Oasis and the northeastern part of Bosten Lake. The area of cultivated land located in the sub-priority fallow was 71 784.94 hm<sup>2</sup>, mainly distributed in the northern part of the Kaidu River Oasis. The area of cultivated land located in the restricted fallow area was 80 576.89 hm<sup>2</sup>, mainly distributed in the central area of the Kongque River Oasis, the northern and southern part of Bosten Lake, and the eastern part of the Kaidu River Oasis. The area of cultivated land located in the forbidden fallow area was 107 358.03 hm<sup>2</sup>, mainly distributed in the southern part of Kaidu River and Kongque River Oases and the eastern Bosten Lake. 3) The cultivated land located in the priority fallow area was restricted by cultivated land quality. As such, the long-term fallow was necessary to combine with the quality improvement of cultivated land. The fallow compensation in the zone was determined, according to the loss of agricultural income and the cost of land improvement. Furthermore, the cultivated land located in the sub-priority fallow area was in good condition, where the fallow can be combined with agricultural water saving to implement seasonally fallow. More importantly, the fallow compensation depended mainly on the loss of agricultural income. The cultivated land in the restricted fallow area was restricted by cultivated land quality and ecological safety. Therefore, the fallow can be combined with cultivated land quality improvement and ecological protection to implement annual fallow, where the agricultural income loss, land improvement costs, and ecological protection costs standard should be considered into the fallow compensation.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:37
Main heading:Land use
Controlled terms:Climate models - Cultivation - Ecology - Efficiency - Indicators (chemical) - Quality control - Risk perception - Rivers - Soils - Spatial distribution - Watersheds
Uncontrolled terms:Cultivated land qualities - Cultivated lands - Ecological compensation - Farmland qualities - Kaidu-kongque river basin - Land degradation - Land degradation risk - Land fallow - River basins - Spatial layout
Classification code:403 Urban and Regional Planning and Development - 405.3 Surveying - 443 Meteorology - 444.1 Surface Water - 454.3 Ecology and Ecosystems - 483.1 Soils and Soil Mechanics - 801 Chemistry - 804 Chemical Products Generally - 821.3 Agricultural Methods - 902.1 Engineering Graphics - 913.1 Production Engineering - 913.3 Quality Assurance and Control - 914.1 Accidents and Accident Prevention - 921 Mathematics
DOI:10.11975/j.issn.1002-6819.2021.20.030

Accession number:20215211395617
Title:Construction of the automatic quantification system for the phenotype of Amygdalus mira seeds based on HSV space and fitting ellipse
Title of translation:基于HSV空间和拟合椭圆的光核桃种核表型自动量化系统构建
Authors:Han, Qiaoling (1, 2, 3, 4); Cui, Shuqiang (1, 2, 3, 4); Xu, Shanshan (1); Zhao, Yue (1, 2, 3, 4); Zhao, Yandong (1, 2, 3, 4)
Author affiliation:(1) School of Technology, Beijing Forestry University, Beijing; 100083, China; (2) Beijing Lab of Urban and Rural Ecological Environment, Beijing Municipal Education Commission, Beijing; 100083, China; (3) Key Lab of State Forestry Administration for Forestry Equipment and Automation, Beijing; 100083, China; (4) Research Center for Intelligent Forestry, Beijing; 100083, China
Corresponding authors:Zhao, Yandong(yandongzh@bjfu.edu.cn); Zhao, Yandong(yandongzh@bjfu.edu.cn); Zhao, Yandong(yandongzh@bjfu.edu.cn); Zhao, Yandong(yandongzh@bjfu.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:202-210
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Extracting the phenotypic characteristics of Amygdalus mira seeds is to measure the size of a physical object that needs to operate a large number of peach seeds. However, some phenotypic data is still difficult to obtain at present. In this study, an automatic multi-feature extraction system was proposed for peach seeds using HSV color space and edge point detection. The system included three parts. The first part was the collection and image acquisition of Amygdalus mira seeds. Specifically, the Amygdalus mira seeds were collected from the scientific research institutions, and then seed images were captured using a small studio and digital camera. The second part was the image processing of peach seeds. First, the region of interest was obtained on the original image of peach seed, then converted from the RGB to the HSV color space. The threshold segmentation was then selected using the HSV space, in order to remove the seeds from the original image. The purpose of threshold extraction was to determine what threshold range of H space was used to segment the seed kernel and background and then determine the best segmentation of S space under the H threshold range. Finally, the V space threshold was selected in the threshold range of H and S space with the best segmentation, in order that all pictures were the same set of segmentation thresholds, further to realize the preliminary segmentation of peach seed. Binary morphological operations were then utilized to revise the under- and over-segmentation. The third part was the feature extraction and quantification of seeds. First, the morphological features were achieved, including area, shape index, and seed tip state. Specifically, the edge points of seed kernel images were detected to draw the fitting ellipse and separate the tip of seeds. Among them, the tip state was evaluated using the area and sharpness of the seed tip. Subsequently, the color and texture characteristics of the peach kernel were obtained using low-order moments and gray-level co-occurrence matrix. As such, the quantitative analysis was realized for the nucleus phenotype of Amygdalus mira seeds. Additionally, the extracted color features included the first-, the second-, and the third-order moments. The texture features included contrast, energy, homogeneity, and correlation. A comparative experiment was conducted to evaluate the RGB and gray threshold. It was found that the HSV threshold presented a better segmentation, indicating the highest accuracy rate (99.7%), average accuracy rate (98.9%), and Intersection over Union (IoU) (97.4%). In addition, the extraction experiments of morphological, color, and texture features were carried out to further verify the performance of the system. The results showed that there were quite different phenotypic characteristics of different seed individuals. At the same time, the H-mean and S-mean moment showed a downward trend, as the color depth of seed gradually deepened, compared the extracted color features with the visual. The same comparison experiment was also performed on texture features. The contrast increased, while the homogeneity decreased gradually, as the depth of grooves on the seed increased gradually. The energy and correlation decreased gradually when the surface texture of seeds was much clearer. In summary, the extracted characteristics of color and texture were more consistent with that of the visual, indicating the quantitative texture of Amygdalus mira seed kernel. Consequently, this system can be expected to realize the extraction and quantification of kernel tip state, color, and texture features. The finding can also provide the data foundation and technical support for the breeding research of Amygdalus mira.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Image segmentation
Controlled terms:Color - Color image processing - Extraction - Feature extraction - Fruits - Mathematical morphology - Textures
Uncontrolled terms:Amygdali mira - Ellipse fitting - Features extraction - HSV color spaces - HSV space - Image identification - Images segmentations - Peach seeds - Phenotypic parameter - Seed tip
Classification code:741.1 Light/Optics - 802.3 Chemical Operations - 821.4 Agricultural Products
Numerical data indexing:Percentage 9.74E+01%, Percentage 9.89E+01%, Percentage 9.97E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.023

Accession number:20215211395667
Title:Quantity statistics of spruce under UAV aerial videos using YOLOv3 and SORT
Title of translation:利用无人机航拍视频结合YOLOv3模型和SORT算法统计云杉数量
Authors:Chen, Fengjun (1, 2); Zhu, Xueyan (1, 2); Zhou, Wenjing (1, 2); Zheng, Yili (1); Gu, Mengmeng (3); Zhao, Yandong (1, 4)
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) Department of Horticultural Science, Texas A&M University, College Station; TX; 77843, United States; (4) Key Laboratory of State Forestry Administration for Forestry Equipment and Automation, Beijing; 100083, China
Corresponding authors:Zhao, Yandong(yandongzh@bjfu.edu.cn); Zhao, Yandong(yandongzh@bjfu.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:81-89
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A seedling quantity is a key indicator to predict the actual production, supply, and demand for the operation and management of a nursery. The manual visualization has still dominated the statistics for the number of seedlings in complete plots. However, the application needs cannot be fully met in recent years, such as high cost, low efficiency, and slow data update. Therefore, it is necessary to fast and accurately estimate the number of seedlings in the whole plots. Taking the spruce as the research object, this study aims to propose a quantity statistics approach under Unmanned Aerial Vehicle (UAV) aerial videos using YOLOv3 and SORT. The specific procedure included the data acquisition, YOLOv3 detection model, SORT tracking, and cross-line counting. Two areas were divided for the image and video acquisition, each with 6 complete test plots. In the stage of data acquisition, 558 images and 6 videos were captured by a DJI Phantom 4 (UAV). The quantity statistics dataset was then constructed with the acquired images and videos, where the training dataset contained 558 images, and the test dataset contained 6 videos. Subsequently, a YOLOv3 model was selected to detect the spruce, while a SORT model was to track the spruce, and the cross-line counting to count the number of spruce. The performance of the combined YOLOv3+SORT was also quantitatively evaluated using Mean Count Accuracy (MCA), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Frame Rate (FR). It was found that the MCA of 92.30%, MAE of 72, RMSE of 98.85, and FR of 11.5 frames/s for the test dataset in the quantity statistics. The experimental results showed that quick and accurate counting was achieved for the number of spruce in the complete plots. The YOLOv3+SORT was also compared with the SSD+SORT and Faster R-CNN+SORT, in order to further verify the performance of the model. The results showed that the YOLOv3+SORT performed over the SSD+SORT in all four evaluation indexes. Particularly, the YOLOv3+SORT was much faster with higher guaranteed accuracy, with 1.33 percentage points lower MCA, and 10.1 frames/s higher FR, compared with the Faster R-CNN+SORT. In summary, the quantity statistics using YOLOv3 and SORT can be widely expected to serve as an effective way to rapidly and accurately count the number of seedlings in the whole plots. This study can also offer promising potential support to the seedling quantity statistics from the perspective of UAV aerial videos.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:42
Main heading:Unmanned aerial vehicles (UAV)
Controlled terms:Antennas - Data acquisition - Error statistics - Mean square error - Statistical tests
Uncontrolled terms:Aerial video - Frame-rate - Key indicator - Mean absolute error - Performance - Quantity statistic - Root mean square errors - SORT - Spruce - YOLOv3
Classification code:652.1 Aircraft, General - 723.2 Data Processing and Image Processing - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 9.23E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.009

Accession number:20215211395649
Title:Quantitative analysis of the evolution process of high liquid limit laterite shrinkage fracture in Shaoyang areas of Hunan Province of China
Title of translation:湖南邵阳地区高液限红黏土干缩裂隙演化过程的量化分析
Authors:Chen, Aijun (1); Chen, Junhua (1); Cheng, Feng (1); Wu, Di (1)
Author affiliation:(1) School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin; 541004, China
Corresponding author:Chen, Aijun(44420141@qq.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:146-153
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Laterite is a special type of soil in tropical and subtropical humid areas. It is evolved from carbonate rocks to physical, chemical, and biological weathering, as well as laterization with the color of brown-red, maroon and yellowish-brown. Furthermore, laterite is very likely to crack in a dry environment, due to its sensitivity to ambient humidity. The resulting dry shrinkage cracks have posed a great threat to the strength and stability of the soil. Therefore, there is a commonly-hidden danger of collapse from the shrinkage cracking of laterite in slope projects. Most cracking of cohesive soil comes from the evaporation of water in the soil. Boundary constraints and uneven shrinkage can result in the formation and development of a stress-strain field in the soil. Once the tensile exceeds the maximum tensile strength of the soil, the cracks gradually occur and continue to develop during evolution. In this study, a quantitative analysis was performed on the dry shrinkage cracking of red clay in high liquid-limit laterite in Shaoyang area of Hunan Province in China. A drying test was also conducted to explore the evolution and formation mechanism of cracks in the laterite using slurry samples under natural hot-humid conditions. A three-dimensional strain measurement system was adopted to collect the moisture, displacement, strain, and crack of the soil. Then, a quantitative description was made on the evolution characteristics of crack morphology and strain field during dehumidification, thereby investigating the influence of water content on fracture morphology and strain field. The results show that: 1) Six stages were found in the evolution of dry shrinkage cracks on the surface of the soil sample. The cracks were formed in the later stages with the cracking surroundings from the previous stages. Specifically, the intersection angle of fractures was close to 90º in different stages. 2) Most soil was in the tensile state with a nearly 0.5% strain at the crack tip during the initial stage of crack development. The soil around the cracks gradually evolved into a compressive state, as the crack developed. Once all the cracks developed, the soil around the crack was totally in a compressive state. 3) The evolution of cracks was closely related to the limited water content. Specifically, the cracks on the soil surface began to rapidly develop, widen and extend, when the soil water content approached the liquid limit of 67.7%. The developing rate of crack began to slow down when the soil water content reached the plastic limit of 28.3%. Once the soil water content was less than the plastic limit of 18.8%, there was no obvious change of fracture, indicating that the fracture development was nearly completed. 4) The cracking time and width of early fracture exceeded those of later fracture in the process of fracture evolution. The displacement and strain varied at the different parts of the soil surface. The vertical shrinkage at the center of the soil block was greater than that at the edge, but the displacement and strain at the center of the soil block were much less than that at the edge. The finding can offer a great engineering reference to prevent geological diseases or environmental disasters in laterite areas.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:25
Main heading:Soils
Controlled terms:Biology - Crack propagation - Crack tips - Humidity control - Morphology - Shrinkage - Tensile strength - Tropics
Uncontrolled terms:Compressive state - DIC - Dry-shrinkage - Hunan province - Liquid limits - Shrinkage cracking - Shrinkage cracks - Soil surfaces - Soil water content - Strain fields
Classification code:443 Meteorology - 461.9 Biology - 483.1 Soils and Soil Mechanics - 931.2 Physical Properties of Gases, Liquids and Solids - 951 Materials Science
Numerical data indexing:Percentage 1.88E+01%, Percentage 2.83E+01%, Percentage 5.00E-01%, Percentage 6.77E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.016

Accession number:20215211395537
Title:Influence of circulation distribution on the optimization results of mixed-flow pump based on inverse design
Title of translation:环量分布对基于反问题设计的混流泵优化结果的影响
Authors:Li, Yanjun (1); Wang, Mengcheng (1); Yuan, Jianping (1); Yuan, Shouqi (1); Zheng, Yunhao (1)
Author affiliation:(1) National Research Center of Pumps, Jiangsu University, Zhenjiang; 212023, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:44-52
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">To quantitatively study the influence of the impeller outlet circulation distribution on the optimization results of the mixed flow pump, the mixed flow pump with a specific speed of 511 was selected as the baseline model. A comprehensive optimization system was used to optimize under two different conditions, and the performance of the optimization results were compared with the baseline model. In the first case, the influence of the distribution form of the impeller outlet circulation on the optimization result of the mixed flow pump impeller was not considered, that is, the free vortex design (constant distribution of impeller outlet spanwise circulation) was adopted, while in the second case, the effect of circulation distribution was considered, and the forced vortex design (linear distribution of impeller outlet spanwise circulation) was adopted. The optimization system consists of an inverse design method, an optimal latin hypercube sampling method, a radial basis function neural network model and a multi-island genetic algorithm. The optimization objective is the weighted efficiency at 0.8Q<inf>des</inf>, 1.0Q<inf>des</inf> and 1.2Q<inf>des</inf> with weighting factors of 0.2, 0.5, and 0.3 (Q<inf>des</inf> means design flow rate). The constraints are the head change of the optimized mixed flow pump at 1.0Q<inf>des</inf> less than 3% compared to the baseline model design point, and the pump section efficiency at 0.8Q<inf>des</inf>, 1.0Q<inf>des</inf> and 1.2Q<inf>des</inf> is greater than the baseline model. The research results showed that in the forced vortex design, when the circulation value at the hub was selected as the design parameter, it is feasible to combinedly use the continuity equation, the energy conservation equation and the radial balance equation to calculate the spanwise distribution of impeller outlet circulation. Which can ensure that the pump section head changes of the sampling points under the design condition are within a reasonable range (the range of head variation is less than 10% of the baseline model design head), and there is no need to add new sample points. In addition, the comparison of the predicted head and calculated head of the optimal solution also shows the same result. The results of local sensitivity analysis showed that the impeller outlet spanwise circulation distribution control parameters has a greater impact on the pump section weighted efficiency, and it can influence the other design parameters effect on the weighted efficiency. Therefore, it is necessary to consider the influence of the impeller outlet circulation in the optimal design of the mixed flow pump. The internal flow analysis showed that the forced vortex design can more effectively control the flow regime near the impeller outlet than the free vortex design. This is not only conductive to the improvement of the efficiency of the impeller, but also to the reduction of the hydraulic loss of the downstream components of the impeller, thereby further improving the overall optimization effect of the mixed flow pump. In the free vortex design, the weighted efficiency of the optimization result is 84.14%, while in the forced vortex design, the weighted efficiency of the optimization result is 85.08%, and the heads of both all meet the constraint conditions. This study can provide reference for the optimization design of turbomachinery, so as to maximize the optimization effect.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Vortex flow
Controlled terms:Computational fluid dynamics - Design - Genetic algorithms - Impellers - Inverse problems - Pumps - Radial basis function networks - Sensitivity analysis
Uncontrolled terms:Baseline models - Circulation distribution - Hydrodynamic parameters - Impeller outlet - Inverse designs - Local sensitivity analysis - Mixed flow pump - Mixed-flow pump impellers - Optimisations - Optimization design
Classification code:601.2 Machine Components - 618.2 Pumps - 631.1 Fluid Flow, General - 723.5 Computer Applications - 921 Mathematics - 931.1 Mechanics
Numerical data indexing:Percentage 1.00E+01%, Percentage 3.00E+00%, Percentage 8.414E+01%, Percentage 8.508E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.005

Accession number:20215211395499
Title:Quantifying the water sources of Camellia oleifera during fruit growth peak period using hydrogen and oxygen isotopes
Title of translation:基于氢氧同位素的油茶果实生长高峰期水分来源量化
Authors:Yue, Lingli (1); Xia, Xiong (1); Hu, Deyong (1); Xiao, Weihua (1); Zhang, Wenping (1); Xu, Wenbin (1); Wu, Youjie (1)
Author affiliation:(1) College of Water Resources & Civil Engineering, Hunan Agricultural University, Changsha; 410128, China
Corresponding author:Wu, Youjie(wuyoujie@hunau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:154-161
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Water is a key factor for plant growth and development. Quantifying water sources is one of the most important steps to effectively manage the irrigation of forests during the fruit peak growth period in hilly areas. However, the research on the water use of different fruit growth peaks is still lacking on Camellia oleifera. In this study, a systematic investigation was conducted to quantify the water source of Camellia oleifera forest during the fruit peak growth period using hydrogen and oxygen isotopes. The precipitation, soil, and Camellia oleifera samples were also collected from April-June (the first fruit growth peak) and July-August (the second fruit growth peak) in 2019 and 2020, where the soil sampling depth was 1 m. The soil layer was divided into three layers: 0-30, >30-60, and >60-100 cm, according to the distribution of root and soil water content. Taking Young Camellia oleifera aged 3 to 5 years as subjects, the isotopic composition of xylem and soil water was compared in the active layer of the root system at the peak of fruit growth. Linear mixed and the Bayesian hybrid (MixSIAR) models were used to quantify the water absorption source of the root system. The results indicate that the Local Meteoric Water Line (LMWL) was δD=8.29δ<sup>18</sup>O+12.99, R<sup>2</sup>=0.99 during the test period, where the soil and plant water isotope were concentrated near the LMWL. Most isotopes of xylem water were distributed in the range of soil water isotope values, where the soil water was the direct water source. The isotope value of xylem water basically intersected with that of soil water of 0-100 cm. The intersection depth mainly intersected 0-30 cm during the growth peak of the first fruit, and then increased gradually during the growth peak of the second fruit. It inferred that the water source in the first peak period came from the 0-30 cm soil layer, whereas, the water in the deeper soil layer was used in the second peak period. The model results showed that Camellia oleifera presented similar water utilization strategies in the two fruit growth peaks in 2019 and 2020. Specifically, the soil water in the 0-30 cm soil layer was mainly used at the peak of fruit growth. The contribution rates of 0-30, >30-60 and >60-100 cm soil layers were 51.3%, 28.2% and 20.5%, respectively. The water absorption depth increased in the second fruit growth peak, compared with the first growth peak. For example, the results of MixSIAR model showed that the utilization rate of 0-30 cm soil layer decreased by 19%, while the utilization rate of >30-60 and >60-100 cm two soil layers increased by 12% and 8%, respectively. The contributions of three soil layers (unit volume) to water absorption of root were 149.6, 81.1, and 58.7 mm, respectively. There was only a slight difference to simulate the contribution proportion of soil water in each soil layer using linear mixing and the MixSIAR model. This finding can provide a sound reference to formulate a suitable irrigation system for young Camellia oleifera in the southern hilly region. Correspondingly, the forest water and fertilizer construction can also be integrated for the healthy development of Camellia oleifera.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:35
Main heading:Soil moisture
Controlled terms:Forestry - Fruits - Isotopes - Plants (botany) - Soil testing - Water absorption
Uncontrolled terms:%moisture - Camellia oleifera - Fruit growth - Fruit growth peak of camellia oleifera - MixSIAR model - Peak period - Soil layer - Soil water - Water source - Water use
Classification code:483.1 Soils and Soil Mechanics - 802.3 Chemical Operations - 821.0 Woodlands and Forestry - 821.4 Agricultural Products
Numerical data indexing:Age 3.00E+00yr to 5.00E+00yr, Percentage 1.20E+01%, Percentage 1.90E+01%, Percentage 2.05E+01%, Percentage 2.82E+01%, Percentage 5.13E+01%, Percentage 8.00E+00%, Size 0.00E00m to 1.00E00m, Size 0.00E00m to 3.00E-01m, Size 1.00E00m, Size 5.87E-02m, Size 6.00E-01m to 1.00E00m
DOI:10.11975/j.issn.1002-6819.2021.20.017

Accession number:20215211395618
Title:Effect of magnetization of irrigation water on the clogging of drip irrigation emitters with integrated water and fertilizer
Title of translation:灌溉水磁化处理对水肥一体化滴灌滴头堵塞的影响
Authors:Wang, Zhaoxi (1, 2); Zhao, Xue (1, 2); Zhang, Wenqian (1, 2); Niu, Wenquan (1, 3)
Author affiliation:(1) The Key Laboratory of Agricultural Soil and Water Engineering in Arid Areas, Northwest A&F University, Yangling; 712100, China; (2) College of Water Conservancy and Civil Engineering, Northwest A&F University, Yangling; 712100, China; (3) Institute of Soil and Water Conservation, MWR & CAS, Yangling; 712100, China
Corresponding authors:Niu, Wenquan(nwq@nwafu.edu.cn); Niu, Wenquan(nwq@nwafu.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:127-135
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">This study aims to explore the effect of magnetization treatment on the clogging of drippers for the integrated drip irrigation of water and fertilizer in the area of the Yellow River. Taking the inner-embedded drip emitter as the research object, the intensity of magnetization was set to 0.2, 0.4, and 0.6 T, where the control group was unmagnetized. A short-term intermittent irrigation test was also carried out for 2% of the mass of potassium sulfate fertilizer, urea, and compound fertilizer muddy water (sediment content of 3.0 g/L). The results showed that the magnetization significantly slowed down the downward trend of dripper flow and irrigation uniformity (P<0.01). The optimal magnetization intensity greatly varied in the different fertilizers. Specifically, there was the greatest mitigation effect of dripper flow for the mixture of potassium sulfate fertilizer and compound fertilizer, when the magnetization intensity was 0.4T. The greatest mitigation effect was found during the decrease in the flow rate of the dripper in the urea mixture at the magnetization intensity of 0.2 T. The effective irrigation times for the mixture of potassium sulfate fertilizer, urea, and compound fertilizer without magnetization treatment (irrigation times with a relative flow rate greater than 75%) were 10, 10, and 3 times, respectively. Furthermore, the effective irrigation times of different fertilizer mixtures increased after the magnetization treatment. When the magnetization intensity was 0.4, 0.2, and 0.4 T, the effective irrigation times of potassium sulfate fertilizer, urea, and compound fertilizer mixture increased the most, which were 16, 15, and 7 times, respectively. The number of clogged emitters increased significantly in the front section of the capillary tube for the potassium sulfate fertilizer and compound fertilizer treatment, whereas, the urea decreased after magnetizing the irrigation water. In the 0.4 T treatment, the most increased number of blocked drippers was found in the front section of the capillary for the potassium sulfate fertilizer and compound fertilizer mixture, which were 68.77% and 27.50%, respectively. In the 0.2 T treatment, there was the largest decrease (55.36%) in the number of blocked drippers in the front section of the urea mixed liquid capillary tube. The ratio for the amount of sediment in the capillary tube to the amount of sediment output from the dripper was represented by η under different magnetization treatments. When applying potassium sulfate fertilizer and compound fertilizer, the magnetization treatment increased the value of η, indicating the largest increase at 0.4 T. By contrast, the magnetization treatment reduced the value of η, when the urea was applied, indicating the most obvious decrease at 0.2 T. As such, the magnetization significantly dominated the sedimentation and movement for the sensitive particle size of emitter blockages. Specifically, the magnetization significantly increased the proportion of sensitive particle size (smaller than 0.03 mm) in the siltation sediment for the capillary of the potassium sulfate and the compound fertilizer mixture, reducing the proportion of sensitive particle size in the sediment output from the emitter, where that of urea was the opposite. When the magnetization intensity was 0.4 T, after applying potassium sulfate fertilizer and compound fertilizer, the sediment-sensitive particle size in the front and middle of the capillary increased the most: 25.75%, 11.17%, and 17.87%, 10.36%, respectively. After applying urea, the magnetization presented the largest decrease, when the magnetization was 0.2 T. When the magnetization intensity was 0.4 T, the proportion of sensitive particle size in the output sediment of the potassium sulfate and the compound fertilizer mixture dripper presented the largest decrease, which was 5.33% and 4.61%, respectively. When the magnetization intensity was 0.2 T, the urea mixed liquid dripper presented the largest increase in the proportion of sensitive particle size in the sediment output, which was 5.26%. The finding can provide a strong reference for the anti-clogging prevention measures in the drip irrigation drippers with integrated water and fertilizer in the Yellow River irrigation areas.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:35
Main heading:Irrigation
Controlled terms:Fertilizers - Magnetization - Metabolism - Mixtures - Sediments - Sulfur compounds - Urea
Uncontrolled terms:Compound fertilizer - Drip irrigation - Dripper clogging - Integration of water and fertilizers - Irrigation waters - Magnetization intensities - Magnetization treatment - Mitigation effects - Particles sizes - Yellow river
Classification code:483 Soil Mechanics and Foundations - 701.2 Magnetism: Basic Concepts and Phenomena - 804 Chemical Products Generally - 804.1 Organic Compounds - 821.2 Agricultural Chemicals - 821.3 Agricultural Methods
Numerical data indexing:Magnetic flux density 2.00E-01T, Magnetic flux density 4.00E-01T, Magnetic flux density 6.00E-01T, Mass density 3.00E+00kg/m3, Percentage 1.036E+01%, Percentage 1.117E+01%, Percentage 1.787E+01%, Percentage 2.00E+00%, Percentage 2.575E+01%, Percentage 2.75E+01%, Percentage 4.61E+00%, Percentage 5.26E+00%, Percentage 5.33E+00%, Percentage 5.536E+01%, Percentage 6.877E+01%, Percentage 7.50E+01%, Size 3.00E-05m
DOI:10.11975/j.issn.1002-6819.2021.20.014

Accession number:20215211395552
Title:Cultivated land quality evaluation and management zoning considering the attribute of "resource-asset-capital" in mountainous areas of Yunnan Province of China
Title of translation:考虑"资源-资产-资本"属性的云南山区耕地质量评价与管理分区
Authors:Shi, Yunyang (1, 2); Ai, Dong (1, 2); Sun, Yihang (1, 2); Hao, Jinmin (1, 2)
Author affiliation:(1) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China; (2) Key Laboratory of Agricultural Land Quality, Ministry of Natural Resources of the People's Republic of China, Beijing; 100193, China
Corresponding authors:Hao, Jinmin(jmhao@cau.edu.cn); Hao, Jinmin(jmhao@cau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:277-286
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">"Resource-asset-capital" attributes can be used to promote the efficient utilization and allocation of cultivated land against the market-oriented economy. Taking a typical Xundian County in mountainous areas of Yunnan Province as a study area, the quality evaluation and zoning management were made using the attributes connotation of "resource-asset-capital" and multi-source data of cultivated land. The targeted measures of local cultivated land management were also proposed for each zone using the local autocorrelation, according to the spatial agglomeration of quality evaluation. The results show that: 1) The resource attribute of cultivated land referred to the specific agricultural activities for the products from the cultivated land under certain natural conditions, such as light, temperature, water, soil, and heat. The asset attribute of cultivated land was that the cultivated land resources in social relations were able to bring benefits, thereby determining the ownership through the legal system. The capital attribute of cultivated land was that the cultivated land was traded and circulated in the market to obtain high profits. The resource, asset and capital attributes presented the influence on each other, indicating the only way for the value of cultivated land resources. 2) There were great differences among the geographical distribution and spatial pattern of resource, asset and capital quality of cultivated land. The resource quality of cultivated land showed less variation and more stable geographical distribution, compared with asset and capital quality. Furthermore, the resource quality of cultivated land in the study area presented a "high in the east and west and low in the middle" trend in spatial patterns. However, the asset and capital quality of cultivated land in the study area showed a "gradient decreasing towards the urban center" and a "high in the southeast and low in the northwest" pattern, respectively. 3) Taking the administrative village as the basic research unit, four areas were divided using the comprehensive spatial agglomeration, including the market-oriented pilot zone, market-oriented cultivation area, efficient upgrading area, and remediation concentration area. Differentiated management measures were also proposed for each zone. It is necessary to formulate and implement policies and regulations for the easy entry of high-quality cultivated land resources into the market for the market-oriented pilot zone. Further, the property rights system and the income distribution can be improved to ensure the rational circulation of cultivated land resources for the market-oriented cultivation area. The finding can provide a scientific reference for the protection and development of cultivated land management in the mountainous areas of Yunnan province.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:41
Main heading:Land use
Controlled terms:Agglomeration - Commerce - Geographical distribution - Information management - Laws and legislation - Natural resources management - Quality control - Resource allocation - Zoning
Uncontrolled terms:Cultivated lands - Land resources - Management IS - Management zoning - Mountainous area - Quality evaluation - Resource-asset-capital attribute - Study areas - Yunnan mountainoi area - Yunnan province
Classification code:403 Urban and Regional Planning and Development - 405.3 Surveying - 802.3 Chemical Operations - 902.1 Engineering Graphics - 912.2 Management - 913.3 Quality Assurance and Control - 971 Social Sciences
DOI:10.11975/j.issn.1002-6819.2021.20.031

Accession number:20215211395555
Title:Quality inspection of Spathiphyllum plug seedlings based on the side view images of the seedling stem under the leaves
Title of translation:基于叶片下苗茎侧视图像的白掌穴盘苗品质检测
Authors:Yang, Yi (1); Fan, Kaijun (2); Han, Jiangfeng (3); Yang, Yanli (4); Chu, Qi (4); Zhou, Zhuomin (3); Gu, Song (3, 5)
Author affiliation:(1) College of Electronic Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) College of Electromechanical Engineering, China University of Petroleum(East China), Qingdao; 266580, China; (3) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (4) Guangzhou Sky Mechanical & Electrical Technology Co., Ltd., Guangzhou; 510642, China; (5) Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou; 510642, China
Corresponding authors:Gu, Song(sgu666@sina.com); Gu, Song(sgu666@sina.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:194-201
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Plug seedlings have been widely used in the production of vegetable and flower planting. The consistent quality of plug seedlings depends mainly on economic benefits. It is usually necessary to identify and remove unqualified seedlings from the plugs, and then replace them with qualified seedlings. The manual operation of substandard seedlings is mainly used from the plugs to the supplement seedling at present, indicating low efficiency, high labor costs, and unstable classification. The seedling sorting machine using machine vision can automatically identify the lack of seedling holes and unqualified seedlings, and then remove the unqualified seedlings from the plug trays. The accurate classification can be achieved with higher operation efficiency. The top view images are selected to judge the quality of plug seedlings with no crossed leaves and no mutual obscuration. However, the leaves of adjacent seedlings cross each other or are blocked and covered, when most plug seedlings of flower and vegetable are sold. It cannot be evaluated on the growth status and quality of individual seedlings using the top view image. Taking the Spathiphyllum seedlings as the research object, this study aims to observe the local area of seedling stem under the leaves using perspective images under the leaves. An automatic quality inspection of plug seedlings was realized to combine with the judging standard of seedling level, particularly on the stem image covering each other with leaves. Firstly, the critical value of the projection area of the stem of Spathiphyllum seedlings was proposed, according to the production standards. Secondly, an image acquisition unit of the seedling stem was constructed, consisting of a leaf guide piece, a miniature camera, and two light guide fibers. Subsequently, the stem images were captured under the leaf of Spathiphyllum seedlings in the darkroom. Then, the PC vision was utilized to analyze the images and projection area of the seedling stem. The seedlings were determined to be qualified or not, according to the quality evaluation on the projection area and the critical value of the Spathiphyllum seedling stem. The hole positions of unqualified seedlings were returned to PLC at last. A three-factor three-level test was carried out to select the conveyor speed, where the deviation of the center distance between seedling stem and hole in the shooting direction, the deviation rate-How closed the projection area of the stem to the Critical Value of the Projection Area of Stem(CVA) as the test factors. The quality test results show that the accuracy of quality detection of plug seedlings depended mainly on the deviation distance and conveyor speed. Specifically, the accuracy of quality detection dropped bellow 85%, when the seedling deviated from the hole center greater than 10 mm and the conveyor speed increased to 0.06m/s. But there was no significant impact when the projection area of the stem was close to CVA. In addition, the quality inspection test was carried out on 72 holes of Spathiphyllum plug seedlings. It was found that the recognition accuracy of the system reached 97.92%, and the productivity was 150 tray/h, and 10 800 plant/h, when the conveyor speed was 0.045 m/s and the deviation distance of seedling stem was within 10mm. This finding can provide a strong theoretical reference for the automatic evaluation of plug seedlings grading and quality inspection, particularly when adjacent leaves were covered.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:33
Main heading:Computer vision
Controlled terms:Agricultural machinery - Cameras - Efficiency - Fruits - Inspection - Seed - Vegetables - Wages
Uncontrolled terms:Critical value - Leaf covering - Machine-vision - Plug seedling - Projection area - Protected horticulture - Quality detection - Quality inspection - STEM images - Top views
Classification code:723.5 Computer Applications - 741.2 Vision - 742.2 Photographic Equipment - 821.1 Agricultural Machinery and Equipment - 821.4 Agricultural Products - 912.4 Personnel - 913.1 Production Engineering
Numerical data indexing:Percentage 8.50E+01%, Percentage 9.792E+01%, Size 1.00E-02m, Velocity 4.50E-02m/s, Velocity 6.00E-02m/s
DOI:10.11975/j.issn.1002-6819.2021.20.022

Accession number:20215211395590
Title:Optimizing irrigation and nitrogen management for potato production under multi-objective production conditions
Title of translation:不同生产目标条件的马铃薯水氮管理优化
Authors:Tang, Jianzhao (1); Xiao, Dengpan (1); Wang, Jing (2); Wang, Rende (1); Bai, Huizi (1); Guo, Fenghua (1); Liu, Jianfeng (1)
Author affiliation:(1) Engineering Technology Research Center, Geographic Information Development and Application of Hebei, Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang; 050011, China; (2) College of Resources and Environmental Sciences, China Agricultural University, Beijing; 100193, China
Corresponding author:Xiao, Dengpan(xiaodengpan168@163.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:108-116
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Water is a determining factor in crop production, particularly with the increase of irrigation areas and crops in recent years. Water shortage has posed a great challenge to crop production in North China. Fortunately, the nitrogen (N) fertilizer can serve as another key factor for crop growth and yield formation. However, there is a severe unbalance between the supply of N fertilizer and crop demand. It is also a trade-off between the irrigation and N fertilizer in most parts of Agro-Pastoral Ecotone (APE), which is one of the staple production regions for potatoes in China. Therefore, it is necessary to optimize the irrigation and N management for potato sustainable production using various production goals under different precipitation years. In this study, 27 study sites in the APE were selected to explore the coupling impacts of irrigation and N on the potato yield, Water Use Efficiency (WUE), and economic benefits using the Agricultural Production Systems Simulator (APSIM) Potato model. A two-year field experiment was also carried out under different treatments of irrigation and N fertilizer at a typical site in the APE. Specifically, ten irrigation levels were set in the test, where the deficit values ranged from 10 to 100 mm with the interval of 10 mm, while the application amount of N fertilizer ranged from 30 to 210 kg/hm<sup>2</sup> with the interval of 30 kg/hm<sup>2</sup>. Three types of precipitation years (dry, normal, and wet) were divided in the APE, according to the guarantee rate of precipitation. Subsequently, the WUE was calculated using the ratio of fresh potato yield to evapotranspiration. The economic benefit was the difference between the gross income and the total inputs, where the gross income was the product of the total fresh yield and unit price. Among them, the inputs included the cost of seeding, irrigation, fertilization, use of fungicides and pesticides, tillage, planting and harvesting, and labor. The results showed that the APSIM-Potato model performed well to simulate the phenology, the soil water content of 1m depth, potato N uptake, and yield. The yield of rainfed potato without the application of N fertilizer was ranged from 4 760 to 18 500 kg/hm<sup>2</sup>, from 9 200 to 20 900 kg/hm<sup>2</sup>, and from 11 900 to 21 500 kg/hm<sup>2</sup> under dry, normal and wet precipitation years, respectively. More importantly, the yields were the lowest in the middle APE under all types of precipitation years. The maximum yield of potato was achieved under the dry year using different combinations of irrigation and N fertilizer. In addition, an optimal combination was achieved to maximize the yield, where the irrigation inputs were 589, 544, and 512 mm in dry, normal, and wet years, respectively, while the N application amounts were all 210 kg/hm<sup>2</sup>. The irrigation inputs were much higher in the eastern and western APE under all precipitation year types. The maximum WUEs were 85.9, 90.2, and 92.2 kg/ (mm•hm<sup>2</sup>) in the dry, normal, and wet years, respectively. An optimal combination was also achieved to maximize the WUE, where the irrigation inputs were 172, 107, and 87 mm in the dry, normal, and wet years, respectively, while the amounts of N were 60-120 kg/hm<sup>2</sup>. Among them, the proportion of sites with 60 kg/hm<sup>2</sup> was the highest in the dry years. As such, the maximum economic benefits were 19 340, 18 610, and 18 470 Yuan/hm<sup>2</sup> in dry, normal, and wet years, respectively. An optimal combination was also achieved to maximize the income, where the irrigation inputs were 226, 152, and 116 mm in dry, normal, and wet years, respectively, while the application amounts of N were 30-90 kg/hm<sup>2</sup> in different year types. The proportion of sites with 90 kg/hm<sup>2</sup> was the highest in the wet years. The finding can greatly contribute to formulating optimal management of irrigation and N fertilizer, according to various goals of potato production under different precipitation years.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:34
Main heading:Irrigation
Controlled terms:Crops - Cultivation - Economic and social effects - Economics - Efficiency - Nitrogen fertilizers - Seed - Soil moisture - Water supply
Uncontrolled terms:'Dry' [ - Agro-pastoral ecotones - Crop production - Economic benefits - Fertilisation - Income - N fertilizers - Optimal combination - Water use efficiency - Yield
Classification code:446.1 Water Supply Systems - 483.1 Soils and Soil Mechanics - 804 Chemical Products Generally - 821.2 Agricultural Chemicals - 821.3 Agricultural Methods - 821.4 Agricultural Products - 913.1 Production Engineering - 971 Social Sciences
Numerical data indexing:Mass 9.00E+01kg, Mass 9.00E+02kg, Mass 9.22E+01kg, Size 1.00E-02m to 1.00E-01m, Size 1.00E-02m, Size 1.00E00m, Size 1.16E-01m, Size 5.08E-02m, Size 5.12E-01m, Size 8.70E-02m, Mass 2.10E+02kg, Mass 3.00E+01kg to 2.10E+02kg, Mass 3.00E+01kg, Mass 3.00E+01kg to 9.00E+01kg, Mass 5.00E+02kg, Mass 6.00E+01kg to 1.20E+02kg, Mass 6.00E+01kg
DOI:10.11975/j.issn.1002-6819.2021.20.012

Accession number:20215211395565
Title:Development of potato seed-metering state monitoring system based on space capacitance sensors
Title of translation:基于空间电容传感器的马铃薯排种状态监测系统研制
Authors:Zhu, Liang (1); Wang, Guanping (1); Sun, Wei (1); Zhang, Hua (1); Liu, Xiaolong (1); Feng, Bin (1); Wang, Chengjiang (1); Sun, Liping (2)
Author affiliation:(1) College of Mechatronic Engineering, Gansu Agricultural University, Lanzhou; 730070, China; (2) Gasu Polytechnic College of Animal Husbandry & Engineering, Wuwei; 733006, China
Corresponding author:Wang, Guanping(wgp678@163.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:34-43
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A spoon-type potato seed-metering has been widely used for easy preparation and seeding feasibility, due to its simple structure and low price, especially for small and medium-sized planters. But the relatively low reliability of seed-metering has led to the huge loss and significant reduction of yield, where the common miss-seeding rate can be about 5%-7%.Thetraditionalphotoelectric monitoring system cannot fully meet the high performance of anti-dust and anti-vibration. In this study, a new approach was proposed to construct a space capacitance sensor for the evaluation of seed-metering states and mass acquisition of seed potatoes. Specifically, the capacitance variation was obtained in the process of working seed spoon, when passing through the space surrounding the capacitor plates. A theoretical derivation was carried out first to evaluate the feasibility of the potato seed-metering state, according to the maximum net capacitance fluctuation (MNCF) signal. Furthermore, a Maxwell model was performed on the spatial capacitance sensor to determine the range of capacitance using the parameters and morphology of key components in a typical potato seeder. There was a direct influence of all parameters on the size of space capacitor plates to be constructed, including the shape of seed spoon, spoon chain, and the diameter of cutting seed tuber. Since the larger capacitance plates allowed for the higher base capacitance, there was no obvious fluctuation in the maximum net capacitance, when the seed tuber passed through the surrounding space. As such, the sensor sensitivity was reduced significantly. However, the misjudgment inevitably occurred, due to the insufficient sampling data, where the sampling frequency of the system was not enough, if the capacitor plate was too small, while the potato seed on the spoon moved quickly, particularly when the system working at a higher speed. Taking MAX038 as the core, the capacitance of the space capacitance sensor was indirectly obtained by c/f conversion-frequency measurement, and then the MNCF related parameters were calculated, according to Nyquist sampling. A special bench test of seed potato movement was also conducted under the constant temperature and humidity environment, thereby acquiring the regression models of temperature and humidity on the measured parameters. More importantly, the measurement data under different conditions was freely converted to a standard state. The specific parameters of the standard state were the temperature of 15℃ and humidity of 50% RH. In terms of different-sized seed potatoes with the same breed, there was a significant linear relationship between the MNCF and the weight. It was found that the system atic measurement error of spatial capacitance was less than 1%, and the error of seed potato mass acquisition was not more than 3%. The miss-seeding was determined accurately within the test range. Nevertheless, 2.33% of 1-seed normal-seeding was misjudged as the multi-seeding, and 2.78% of the 2-seeds multi-seeding was misidentified as normal-seeding, for the irregularity of test seeds. Misjudgment mainly occurred in an extreme case, particularly whether the single seed potato was too large, or the double seed potato was too small. Overall, the accuracy of the system was still higher than before. Correspondingly, the system performance under actual conditions can be widely expected to perform well on a complete judgment of normal-, miss- and multi-seeding at one time in the scheme. The finding can also provide a new reference for highly reliable monitoring of the potato seed-metering under severe dust and violent vibration environments.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:31
Main heading:Capacitance
Controlled terms:Monitoring - Plates (structural components) - Regression analysis - Seed - Testing
Uncontrolled terms:Capacitance sensors - Capacitor plates - Monitoring system - Potato - Seed metering - Seed metering status - Simple structures - Space capacitance - State monitoring - Temperature and humidities
Classification code:408.2 Structural Members and Shapes - 701.1 Electricity: Basic Concepts and Phenomena - 821.4 Agricultural Products - 922.2 Mathematical Statistics
Numerical data indexing:Percentage 1.00E00%, Percentage 2.33E+00%, Percentage 2.78E+00%, Percentage 3.00E+00%, Percentage 5.00E+00% to 7.00E+00%, Percentage 5.00E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.004

Accession number:20215211395562
Title:Navigation path recognition between crop ridges based on semantic segmentation
Title of translation:基于语义分割的作物垄间导航路径识别
Authors:Rao, Xiuqin (1, 2); Zhu, Yihang (1, 2); Zhang, Yanning (1, 2); Yang, Haitao (3); Zhang, Xiaomin (1, 2); Lin, Yangyang (1, 2); Geng, Jinfeng (1, 4, 5); Ying, Yibin (1, 2)
Author affiliation:(1) College of Biosystem Engineering and Food Science, Zhejiang University, Hangzhou; 310058, China; (2) Key Laboratory of Agricultural Products Processing Equipment, Ministry of Agriculture and Rural Affairs, Hangzhou; 310058, China; (3) School of Mathematical Sciences, Zhejiang University, Hangzhou; 310058, China; (4) School of Mechanical and Electrical Engineering, Zaozhuang University, Zaozhuang; 277101, China; (5) Xinduo Group Co., Ltd., Yongkang; 321300, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:179-186
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A navigation path has been widely considered as one of the most important sub-tasks of intelligent agricultural equipment in field operations. However, there are still some challenges remaining on the recognition of current navigation paths between crop ridges, including the accuracy, real-time performance, generalization, and difficulty in the interpretation of deep learning models. In this research, a new Fast-Unet model was proposed to accurately and rapidly recognize the navigation path between crop ridges using semantic segmentation. The jump connection of the Unet model was also retained to generate the navigation line and yaw angle using the least square regression. Specifically, a cotton dataset of inter-ridge navigation path consisted of 800 images, 640 of which was set as the training set, 160 of that as the validation set. Subsequently, two datasets of 100 images each were constructed for the navigation paths of sugarcane and cotton ridges, which were divided into 50 images in the training set, and 50 images in the verification set. The training strategy was selected as the data augmentation and learning rate adjustment. The training order was ranked as the corn first, and then the sugarcane dataset. The Mean Intersection over Union (MIoU) was utilized as the accuracy indicator of the Fast-Unet model, which was 0.791 for cotton, 0.881 for maize, and 0.940 for sugarcane. Furthermore, the least-squares regression was selected to calculate the navigation path of maize and sugarcane with good linearity between the ridges. Additionally, the navigation line was selected to further calculate the yaw angle. The mean difference between the predicted yaw angle of maize and sugarcane navigation path and the labeled were 0.999° and 0.376° under the Fast-Unet model, respectively. In terms of real-time performance, the inference speed of the Fast-Unet model was 6.48 times higher than that of Unet. The inference speed was 64.67 frames per second to process the RGB image data on a single-core CPU, while the number of parameters of the Fast-Unet model was 6.24% of that of Unet model. Correspondingly, the computing devices were deployed with weak computing power, thereby performing real-time calculations. A gradient weighted class activation mapping(Grad-CAM) was also used to visually represent the final feature extraction of model recognition and transfer learning. More importantly, the special features were highlighted on the navigation path between crop ridges in the optimized Fast-Unet structure, concurrently to remove a large number of redundant feature maps, while retaining only the most crucial feature extractors. The transfer learning also presented a larger activation area than the direct training, where the activated area matched the main road to be identified. In summary, the improved model can be fully realized the real-time recognition of maize navigation path. The finding can also provide technical and theoretical support to the development of navigation equipment for intelligent agricultural machinery in the field.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Crops
Controlled terms:Cotton - Deep learning - E-learning - Navigation - Semantic Segmentation - Semantics
Uncontrolled terms:Deep learning - Images processing - Least squares regression - Navigation lines - Navigation paths - Path recognition - Real time performance - Semantic segmentation - Transfer learning - Yaw angles
Classification code:461.4 Ergonomics and Human Factors Engineering - 723.4 Artificial Intelligence - 821.4 Agricultural Products
Numerical data indexing:Percentage 6.24E+00%
DOI:10.11975/j.issn.1002-6819.2021.20.020

Accession number:20215211395631
Title:Dynamic reconfiguration method of rural active distribution network based on regional division
Title of translation:基于区域划分的农村有源配电网动态重构方法
Authors:Liu, Zhihong (1); Sheng, Wanxing (1); Du, Songhuai (1); Su, Juan (1); Xia, Yue (1)
Author affiliation:(1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China
Corresponding author:Su, Juan(sujuan@cau.edu.cn)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:248-255
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">In recent years, under the guidance of China's green energy development strategy, a large number of photovoltaic, wind power and other DGs have been connected to the rural distribution network. The current rural distribution network structure, DG grid-connected location and capacity, line transmission capacity and other system conditions are in conflict with the ever-increasing rural power demand. DG output and load demand are continuously changing with time. The large-scale access of DGs and EVs has made the "source-load" side of the rural distribution network present significant uncertainty. The traditional topology of rural distribution network cannot cope with the impact of this "source-load" double uncertainty. Therefore, it is urgent to study a new method of dynamic reconfiguration for rural active distribution network. This paper establishes a dynamic reconfiguration model of active distribution network with DG consumption and line loss as objective functions. Taking into account the time-varying characteristics of "source-load", this paper proposes a new method of dynamic reconfiguration of rural active distribution network based on regional division, and designs the process of this dynamic reconfiguration method. In order to improve the efficiency of solving the problem of dynamic reconfiguration of active distribution network, a regional division method is proposed for the first time. The regional division method includes two parts: The initial division of regions and the optimized division of regions. The dynamic reconfiguration method of active distribution network based on area division mainly includes the following four steps. Firstly, the distribution network structure is divided into several initial regions which include main line regions and branch line regions based on the regional initial division method. Secondly, with the goal of promoting the flexible and efficient combined application of DGs between regions, the result of regional initial division is optimized dynamically based on the breadth-first traversal algorithm in the graph theory algorithm. Thirdly, based on the obtained results of dynamic regional optimization, the depth-first traversal algorithm is used to test and modify the DNR scheme to meet the topology constraints of the distribution network. At this time, all feasible DNR schemes can be obtained. Finally, the fast non-dominated sorting strategy is adopted to select the best network reconfiguration scheme that meets the constraints such as node voltage. To validate the performance of the proposed method, it is tested on the well-known IEEE 33-node and PG&E 69-node distribution system. The simulation result of 33-node distribution system shows that the loss reduction effect of the proposed method is very good. Especially at 14:00, the loss reduction effect of the distribution network was the most obvious, which was reduced by 71.41%. At this time, the effect of increasing the utilization rate of DG consumption is also obvious. On this basis, the proposed method on the consumption of each DG was deeply analyzed in this article. Result shows that the proposed method can achieve complete consumption of DG. The voltage of each node under the network structure obtained by the regional optimization division method meets the voltage quality requirements. In addition, the average daily DG consumption rate of the PG&E 69-node distribution system was increased by 16.09 percent point, and the daily line loss was reduced by 55.32%. The effectiveness of the proposed method is verified by the simulation of these two case studies. The simulation results show that the proposed method can fully switch and adjust the ability to improve the absorption capacity of the distributed power, reduce the line loss, suppress the fluctuation of the distributed power, and keep the node voltage smooth.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Dynamic models
Controlled terms:Genetic algorithms - Graph theory - Planning - Rural areas - Wind power
Uncontrolled terms:Active distributions - Dynamic re-configuration - Energy - Network dynamic reconfiguration - Network dynamics - Network structures - Network-based - Regional divisions - Rural active distribution network - Rural distribution networks
Classification code:615.8 Wind Power (Before 1993, use code 611 ) - 912.2 Management - 921 Mathematics - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory
Numerical data indexing:Percentage 1.609E+01%, Percentage 5.532E+01%, Percentage 7.141E+01%
DOI:10.11975/j.issn.1002-6819.2021.20.028

Accession number:20215211395531
Title:Impulsive force simulation of the rubber ball sieve-cleaning device for batch seed cleaners
Title of translation:批次式种子清选机橡胶球清筛装置激振力模拟分析
Authors:Li, Yonglei (1); Xu, Zexin (1); Wan, Lipengcheng (1); Zhao, Hu (1); Chen, Haijun (2, 3); Song, Jiannong (1)
Author affiliation:(1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (3) Key Laboratory of Agro-Products Postharvest Handling, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:23-33
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A batch seed cleaner is a piece of special equipment to meet the specific processing of plot breeding materials. A rubber ball sieve-cleaning device can usually be used as an accessory for a seed cleaner to keep sieve cleaning and avoid sieve-mesh blocking. The sieve-cleaning performance of rubber ball sieve-cleaning devices has an important influence on the operation efficiency and quality of batch seed cleaners. The impulsive force of the rubber ball on the sieve is the key factor to determining the cleaning performance. In this study, the structural and working principles of rubber ball sieve-cleaning devices were introduced to theoretically analyze the random elastic collision screening of rubber balls for the accurate acquisition of impulsive force. An EDEM-MBD coupling model was built for a batch seed cleaner using Hertz-Mindlin in contact mode. A piece of sieve-developed test equipment was utilized to measure the contact parameters, such as the restitution coefficient and friction coefficient for the contact model. A rubber ball impulsive force measurement device was built to obtain the real force of a single ball, according to strain-force measurement. The average and the maximum impulsive force of a single rubber ball were effectively obtained, with the acceptable relative errors between the simulation and measured value, less than 5 % and 10%, respectively. The Box-Behnken experiments with four-factor and three-level were conducted to simulate the impulsive force of sieve-cleaning devices under different working conditions. The mathematical relationships were established between the average or the maximum impulsive force and parameters, such as the amplitude, vibration frequency, screening inclination angle, and ball number. The impulsive force of the rubber ball sieve-cleaning device under different parameters was easily obtained using regression equations. The maize seeds cleaning test under different vibration frequencies was carried out with the index of blockage number, where the relationship was between the blockage number of sieve and impulsive force of the sieve-cleaning device. The test results show that the sieve-cleaning device presented an excellent performance with no blockage on the sieve, with an average impulsive force of 8.87 N and the maximum impulsive force of 18.78 N, when the vibration frequency was 7.2 Hz. An optimal combination was achieved for the screening performance if the average impulsive force not less than 9 N or the maximum impulsive force not less than 19 N. The finding can provide a strong design reference for the screening mechanism and parameter optimization of rubber ball sieve-cleaning devices.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:29
Main heading:Cleaning
Controlled terms:Equipment testing - Friction - Rubber - Sieves
Uncontrolled terms:Breeding materials - Cleaning devices - Forces measurements - Impulsive forces - Performance - Rubber balls - Seed cleaning - Sieve-cleaning device - Simulation - Vibration frequency
Classification code:802.3 Chemical Operations - 818.1 Natural Rubber
Numerical data indexing:Force 1.878E+01N, Force 1.90E+01N, Force 8.87E+00N, Force 9.00E+00N, Frequency 7.20E+00Hz, Percentage 1.00E+01%, Percentage 5.00E+00%
DOI:10.11975/j.issn.1002-6819.2021.20.003

Accession number:20215211395652
Title:Construction of the quality regulation system for provincial scale slope farmland based on quality evaluation
Title of translation:基于质量评价的省域尺度坡耕地质量调控体系构建
Authors:Chen, Zhengfa (1); Gong, Aimin (1); Zhang, Liudong (1); Wang, Jianxiong (1); Xiang, Biao (1); Ning, Dongwei (1)
Author affiliation:(1) College of Water Conservancy, Yunnan Agricultural University, Laboratory of Land Resources Utilization and Protection Engineering in Yunnan Province, Kunming; 650201, China
Corresponding author:Zhang, Liudong(zld8066@163.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:136-145
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">A slope farmland has been one of the most serious land-use types of soil and water loss, as well as the non-point source pollution. Natural conditions and unreasonable farming have also posed great damage to the ecological environment, particularly on the quality degradation of slope farmland. Therefore, it is very necessary to construct the quality control system of slope farmland in recent years. Taking sloping farmland in Yunnan province of China as a research object, a factor analysis model was first established to diagnose the quality obstacle factors of slope farmland. The types of quality obstacles were then ranked to define in each region, thereby identifying the controllable factors, the regulation priority, and objectives of slope farmland quality. The quality regulation potential of slope farmland was calculated to determine the zoning regulation mode in different regions. The results showed that: 1) The main types of quality obstacles were erosion degradation, drought, and water shortage, as well as the nutrient poverty type in the sloping farmland. There was some difference in the combination and performance of obstacle factors in different regions. 2) The adjustable factors of slope farmland quality included the thickness of arable layer, soil bulk density, pH value, organic matter, the total nitrogen, available phosphorus, available potassium, irrigation assurance rate, and field slope, among which the field slope, soil organic matter, irrigation assurance rate, available phosphorus, available potassium and pH value were the priority adjustment and control factors. The goal of quality control in the sloping farmland was to make the controllable factors in the appropriate range under various control measures. An optimal range of factors were achieved, where the thickness of plough layer ≥17.35 cm, soil organic matter ≥28.89 g/kg, soil available phosphorus ≥32.44 mg/kg, soil available potassium ≥137.81 mg/kg, irrigation assurance rate ≥73.33%, soil bulk density ≤1.31 g/cm<sup>3</sup>, field slope ≤12.87°, and pH value 6.06-8.06. 3) The objectives of quality control in the sloping farmland included the ideal and actual state. In an ideal state, the potential of quality control in the sloping farmland was 0.347, indicating an upgrade from the "medium" to the "higher" level. In the actual state, the potential of quality control in the sloping farmland was 0.198, indicating that the quality level was improved from the current "medium" to "high". The potential of actual state control was used as the standard quality control of slope farmland. 4) According to the general idea of "erosion control, water regulation, and fertility enhancement", the integrated mode of quality control in the sloping farmland was constructed as follows. The tillage modes were utilized to promote soil and water conservation, such as ridge, contour, and reverse slope tillage, as well as the conservation tillage (rotary, subsoiling, and no tillage + deep tillage) in farming measures. The water engineering slope to ladder project and high-efficiency water-saving measures can be implemented to actively promote the straw returning, green and organic fertilizer application. The soil testing and formula fertilization among soil fertility measures can be used to increase the content of soil organic matter and nutrients in the slope cultivated land. This finding can provide a scientific guide for the quality cultivation and management of regional slope farmland at a provincial scale.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:30
Main heading:Farms
Controlled terms:Biogeochemistry - Irrigation - Land use - Nitrogen - Organic compounds - pH - Phosphorus - Potassium - Quality control - Soil pollution - Soils - Water pollution - Water quality
Uncontrolled terms:Available phosphorus - Evaluation - Farmland qualities - Obstacle factor diagnose - pH value - Regulation system - Regulatory potential - Slope farmland - Sloping farmlands - Yunnan
Classification code:403 Urban and Regional Planning and Development - 445.2 Water Analysis - 453 Water Pollution - 481.2 Geochemistry - 483.1 Soils and Soil Mechanics - 549.1 Alkali Metals - 801.1 Chemistry, General - 801.2 Biochemistry - 804 Chemical Products Generally - 804.1 Organic Compounds - 821 Agricultural Equipment and Methods; Vegetation and Pest Control - 821.3 Agricultural Methods - 913.3 Quality Assurance and Control
Numerical data indexing:Linear density 1.31E-01kg/m, Mass 1.3781E-04kg, Mass 2.889E-02kg, Mass 3.244E-05kg, Percentage 7.333E+01%, Size 1.735E-01m
DOI:10.11975/j.issn.1002-6819.2021.20.015

Accession number:20215211395665
Title:Effects of different soil surface mulching patterns on soil moisture and nutrient in dryland apple orchard in east Gansu Province
Title of translation:陇东旱地苹果园不同地面覆盖模式的水分与养分效应
Authors:Yin, Xiaoning (1); Dong, Tie (1); Sun, Wentai (1); Niu, Junqiang (1); Liu, Xinglu (1); Ma, Ming (1)
Author affiliation:(1) Institute of Fruit and Floriculture Research, Gansu Academy of Agricultural Science, Lanzhou; 730070, China
Corresponding author:Ma, Ming(maming65118@163.com)
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:117-126
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">Drought with less rainfall is one of the main factors affecting the high quality, high yield, and stability of apples on the Loess Plateau in western China. Ridging and film mulching in the tree tray with rows clearing (F) have currently been the most commonly-used mulching modes to preserve soil moisture in apple orchards. However, moisture preservation still needs to be improved. In this study, a fixed point test was carried out over three years to investigate the effects of different mulching patterns on soil moisture contents before flowering, in the fruit expansion stage and after harvest, as well as nutrient effects and tree growth response. A 17-year-old apple orchard was also selected in the main apple-producing area of the Loess Plateau in east Gansu Province, China. Specifically, the ridge mulching of tree trays (F) was combined with the straw mulching between rows to form a whole garden mulching model (F+W), whereas, the water seepage holes were added on the sides of the film in a row to form a three-dimensional moisture preservation model (F+W+H), with no ridging and no coverage as the control (CK). The results showed that the average moisture content of 0-100 cm soil layer in the three phases of three mulching patterns was higher than that of CK in 2015 (drought year), of which 0-100 cm soil layer in 2016 (Autumn drought year), and 0-100 cm and 100-200 cm soil layer in 2017 (normal rainfall) of both F+W+H and F+W were extremely significant (P<0.01), while F significant (P<0.05) higher than CK. There was also no significant decrease in the inter-annual average moisture contents of 400-500 cm soil layer of F+W+H and 300-500 cm soil layer of F+W after harvest, but those of F and CK decreased significantly. The total evapotranspiration of 0-500 cm soil layer was ranked in order of F+W+H <F+W<F<CK from before flowering in 2015 to after harvest in 2017, where the mulching patterns were extremely significant (P<0.01) lower than that of CK. There was a stable and high cumulative amount of K<inf>2</inf>O absorption, where the average K<inf>2</inf>O accumulations over three years in three mulching patterns were significantly higher (P<0.01) than that of CK. The cumulative amounts of nitrate nitrogen in three mulching patterns in 0-500 cm soil layer were lower than that of CK in 2015, whereas, those of F+W+H and F+W in 300-500 cm soil layer, F in 300-400 cm soil layer were slightly higher than that of CK in 2016. Nitrate nitrogen accumulations in the 0-300 cm soil layer in 2015 and 2016 were 92%-96.2% of the entire profile. Furthermore, the average cumulative amounts of nitrate nitrogen in the F+W+H, F+W, and F in 0-300 cm soil layer were seriously lower (P<0.01) than those of CK by 36.8%, 34.4%, and 39.6%, respectively. The average yield in three years of F+W+H, F+W, and F increased by 13.1%, 13.0%, and 8.3%, compared with the CK, respectively. Consequently, the moisture conservation and rain collection were improved after tree ridge mulching in the orchard was perfected, where the F+W+H and F+W were better modes of mulching. But it was still necessary to reduce chemical fertilizer application, while increasing organic fertilizer for better nitrogen utilization.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:26
Main heading:Fruits
Controlled terms:Drought - Evapotranspiration - Forestry - Harvesting - Landforms - Moisture determination - Nutrients - Orchards - Rain - Sediments - Seepage - Soil moisture
Uncontrolled terms:Apple orchards - Cumulative amount - Fruit nutrient uptake - Gansu province - NO3--N - Nutrient uptake - Soil layer - Soil surface mulching - Soil surfaces - Yield
Classification code:443.3 Precipitation - 444 Water Resources - 481.1 Geology - 483 Soil Mechanics and Foundations - 483.1 Soils and Soil Mechanics - 821.0 Woodlands and Forestry - 821.3 Agricultural Methods - 821.4 Agricultural Products - 944.2 Moisture Measurements
Numerical data indexing:Percentage 9.20E+01% to 9.62E+01%, Size 0.00E00m to 1.00E00m, Size 0.00E00m to 3.00E+00m, Size 0.00E00m to 5.00E+00m, Size 1.00E00m to 2.00E+00m, Size 3.00E+00m to 4.00E+00m, Size 3.00E+00m to 5.00E+00m, Size 4.00E+00m to 5.00E+00m, Age 1.70E+01yr, Percentage 1.30E+01%, Percentage 1.31E+01%, Percentage 3.44E+01%, Percentage 3.68E+01%, Percentage 3.96E+01%, Percentage 8.30E+00%
DOI:10.11975/j.issn.1002-6819.2021.20.013

Accession number:20215211395533
Title:Research progress of the restitution coefficients of collision of particles in agricultural and food fields
Title of translation:农业和食品领域中颗粒碰撞恢复系数的研究进展
Authors:Wang, Lijun (1); Liu, Tianhua (2); Feng, Xin (1); Gao, Yunpeng (1); Wang, Bo (1); Zhang, Sen (1)
Author affiliation:(1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) Tractor Research Institute, Weichai Lovol Heavy Industry, Weifang; 261000, China
Source title:Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Abbreviated source title:Nongye Gongcheng Xuebao
Volume:37
Issue:20
Issue date:October 15, 2021
Publication year:2021
Pages:313-322
Language:Chinese
ISSN:10026819
CODEN:NGOXEO
Document type:Journal article (JA)
Publisher:Chinese Society of Agricultural Engineering
Abstract:<div data-language="eng" data-ev-field="abstract">The collision of particles has been widely found in the processing of agricultural and food fields. The restitution coefficient of collision (RCC) of particles is one of the most important parameters to represent the behavior of particles after the collision. The responsive behavior of particles after the collision can also be predicted to obtain an accurate RCC of the particle after measurement. However, the RCC selection of particles still remained unclear, particularly on the limited function of devices and simplification in the application. Three RCC types are divided, including the restitution coefficient of kinematics, the restitution coefficient of kinetics, and the restitution coefficient of energy. The restitution coefficient of kinematics can be generally defined as the ratio of the velocities of particles before and after the collision. Since the variation in the velocity of particle collision can be caused by the forces on the particle, the restitution coefficient of kinetics is defined as the ratio of the momentums of restituted and extruded particles. Furthermore, two stages are divided in the process of particle collision using energy. In one stage, the particle is compressed and the energy of the particle would be absorbed. In another stage, the particle is restituted that the energy of the particle would be released. Subsequently, the RCC of particles needs to be calibrated to combine physical and simulation tests. As such, a physical experiment was performed on three types of RCC particles to verify the equivalence and applicability under different collision conditions. The features of the devices for testing RCC of the particle were illustrated. The Discrete Element Method (DEM) and Finite Element (FE) were also selected to simulate the interaction between agricultural particles and machinery. The influencing factors were summarized to improve the theoretical models, including the velocity and angle of particle collision, surface roughness of particle, temperature, and the material of particle. Thus, enhanced accuracy of predicted motion would be achieved for the particle after the collision. An attempt was also made on the applications of particle RCC in the theoretical model and numerical simulation related to mechanical parameters design. Consequently, it was found the resultant effect of different factors on RCC of particle, in order to enrich RCC of the particle under the real collision for the higher accuracy of the calculated. A promising prospect was also proposed from the multi-point collision of particles. A creative design of the device was also proposed to evaluate the RCC of particles. The finding can provide a strong reference for further investigation on the RCC of agricultural and food particles.<br/></div> © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Number of references:80
Main heading:Kinematics
Controlled terms:Agricultural machinery - Agricultural products - Finite difference method - Kinetics - Surface roughness - Velocity
Uncontrolled terms:Collision types - Determination - Energy - Particle - Particles collisions - Responsive behaviour - Restitution coefficient - Restitution coefficient of collision - Theoretical modeling - Velocity of particles
Classification code:631.1 Fluid Flow, General - 821.1 Agricultural Machinery and Equipment - 821.4 Agricultural Products - 921.6 Numerical Methods - 931 Classical Physics; Quantum Theory; Relativity - 931.1 Mechanics - 931.2 Physical Properties of Gases, Liquids and Solids
DOI:10.11975/j.issn.1002-6819.2021.20.035

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