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2023年第4期共收录46篇
1. Design and Performance Test of Loss Sowing Detection System for Cavity-type Rice Seed-metering Device
Accession number: 20232214170705
Title of translation:
Authors: Zhang, Shun (1, 2); Wang, Haoyu (1); Yuan, Yanwei (3, 4); Kuang, Fuming (1); Xiong, Wei (1); Zhu, Dequan (1)
Author affiliation: (1) School of Engineering, Anhui Agricultural University, Hefei; 230036, China; (2) Anhui Province Engineering Laboratory of Intelligent Agricultural Machinery and Equipment, Hefei; 230036, China; (3) Chinese Academy oj Agricultural Mechanization Sciences Group Co., Ltd., Beijing; 100083, China; (4) National Key Laboratory oj Agricultural Equipment Technology, Beijing; 100083, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 51-62
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The precision seeding method of rice with cavity-type has the advantages of simplifying the seeding mechanism and reducing seed damage. Aiming at the problem of miss-seeding holes during the hill-drop direct seeding process of the cavity-type precision and small-amount seed-metering device of hybrid rice, combining with the method of combined pulse, a novel loss sowing detection method and its supporting system with cavity scanning of light curtain was designed based on cavity-type seeding principle. The construction method of combined pulse was expounded and the dynamic model of rice seed movement in the cavity detection zone was established to clarify the key structural parameters of the cavity. Subsequently, the performance tests of the loss sowing detection system at different rotational speeds, variable rotational speeds, and different vibration conditions of the seed-metering device were carried out successively. The results of the rotational speed adaptability test showed that all the detection errors at different rotational speeds and variable rotational speeds of the seed-metering device were not higher than 0. 80%. The results of the vibration adaptability test showed that the performance of the detection system was not affected by the medium and high-frequency vibration conditions, while affected by the low-frequency vibration conditions characterized by relatively large amplitude with slightly larger detection error, but the error was not higher than 1. 20%. The field test results showed that the detection system had good adaptability to different forward speeds of seeder, and the detection error was not higher than 2. 13%. The research result can provide a theoretical reference for loss sowing detection method of rice precision and small-amount seeding, and lay the foundation for the development of reseeding systems. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Error detection
Uncontrolled terms: Cavity-type seed-metering device? - ?Detection system? - ?Hybrid rice? - ?Light curtains? - ?Loss sowing detection? - ?Photoelectric sensors? - ?Rotational speed? - ?Seed-metering device? - ?Super hybrid rice? - ?Vibration condition
Numerical data indexing: Percentage 1.30E+01%, Percentage 2.00E+01%, Percentage 8.00E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.005
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
2. Carbon Fixation and Carbon Emission Reduction Effects of Different Water and Nitrogen Management Modes in Black Soil Paddy Fields
Accession number: 20232314185793
Title of translation:
Authors: Zhang, Zhongxue (1, 2); Yu, Peizhe (1, 2); Du, Sicheng (1, 2); Li, Tiecheng (1, 2); Qi, Zhijuan (1, 2); Wang, Bai (3)
Author affiliation: (1) School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) Key Leboratory of Efficient Utilization of Agricultural Water Resources, Ministry of Agriculture and Rural Affairs, Northeast Agricultural University, Harbin; 150030, China; (3) Heilongjiang Water Conservancy Research Institute, Harbin; 150080, China
Corresponding author: Qi, Zhijuan(zhijuan.qi@neau.edu.cn)
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 366-375
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to explore the effects of different water and nitrogen management modes on carbon fixation and carbon emission reduction in black soil paddy fields, a field experiment was conducted. Two irrigation modes of conventional flooding irrigation (F) and controlled irrigation (C) were set up, and three nitrogen application rates of 110kg/hm2(N), 99kg/hm2(N1,10% nitrogen reduction) and 88kg/hm2 (N2,20% nitrogen reduction) were selected. The CO2 emission intensity and CH4 emission intensity of rice soil respiration under six water and nitrogen management modes were measured, and the dry matter quality, carbon content and carbon sequestration of each organ after rice harvest were calculated. The results showed that under different water and nitrogen management modes, the soil respiration CO2 emission intensity of each treatment showed a single peak change, and reached the peak at the tillering stage. The methane emission of each treatment showed a double peak change and reached the peak at the tillering stage and the two time periods after the application of panicle fertilizer. Under the same irrigation method, with the decrease of nitrogen application rate, soil respiration CO2 emission intensity and methane emission intensity were also decreased significantly (P0.05). With the decrease of nitrogen application rate, the soil carbon budget of each treatment was increased first and then decreased under the same irrigation system. Considering comprehensively, CN1 treatment can improve soil carbon sequestration capacity and reduce soil carbon loss and greenhouse gas emissions from paddy fields under high production capacity. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 33
Main heading: Photosynthesis
Controlled terms: Budget control? - ?Carbon? - ?Carbon dioxide? - ?Emission control? - ?Floods? - ?Harvesting? - ?Irrigation? - ?Methane? - ?Nitrogen? - ?Nitrogen fertilizers ? - ?Nitrogen fixation? - ?Phytoplankton? - ?Soils
Uncontrolled terms: Black soil? - ?Black soil paddy field? - ?Carbon budgets? - ?Gross primary productivity? - ?Management modes? - ?Net primary production? - ?Net soil carbon budget? - ?Nitrogen management? - ?Paddy fields? - ?Soil carbon ? - ?Soil carbon pool? - ?Water and nitrogen management mode? - ?Waters managements
Classification code: 451.2 Air Pollution Control? - ?461.9 Biology? - ?471 Marine Science and Oceanography? - ?483.1 Soils and Soil Mechanics? - ?741.1 Light/Optics? - ?802.2 Chemical Reactions? - ?804 Chemical Products Generally? - ?804.1 Organic Compounds? - ?804.2 Inorganic Compounds? - ?821.2 Agricultural Chemicals? - ?821.3 Agricultural Methods
Numerical data indexing: Mass 1.10E+02kg, Mass 8.80E+01kg, Mass 9.90E+01kg, Percentage 1.00E+01%, Percentage 1.078E+01%, Percentage 2.00E+01%, Percentage 2.862E+01%, Percentage 3.666E+01%, Percentage 4.953E+01%, Percentage 5.16E+00%, Percentage 5.71E+00%, Percentage 5.87E+01%, Percentage 6.72E+00%, Surface density 3.1937E-01kg/m2 to 4.89E-01kg/m2
DOI: 10.6041/j.issn.1000-1298.2023.04.038
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
3. Research on Energy Management Model for Extended-range Electric Rotary-tilling Tractor
Accession number: 20232314185739
Title of translation:
Authors: Wang, Zhenzhen (1); Zhou, Jun (2); Wang, Xu (2)
Author affiliation: (1) College of Optical Mechanical and Electrical Engineering, Zhejiang a and F University, Hangzhou; 311300, China; (2) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 428-438
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The demand for green power agricultural machinery and equipment in modern agricultural production environment is more and more urgent. Among them, the extended-range electric tractor has attracted much attention in the demand for medium and high horsepower, which not only makes up for the lack of battery life of pure electric tractors, but also reduces pollution emissions compared with traditional tractors. Due to the complex operating conditions of tractors (such as ploughing, rotary tillage, transportation, and harvesting, etc.), among them, rotary tillage is one of the most common agricultural operations. In order to promote the diversified development of electric tractor products, taking an extended-range electric rotary-tilling tractor with a dual-motor independent electric drive structure as the object, a novel backward modeling method of a dual-input variable, including the forward speed and the power take-off (PTO) was proposed to set up the energy management model of the powertrain system. The energy management model designed mainly contained a Genset model, motor model, power battery pack model, transmission system (reducer and differential) model, wheel-soil system model, engine accessories, and auxiliary load system models. According to the characteristics of rotary tillage operation, a design method based on the combination of measured data and empirical formulas was put forward to establish a cycle model of rotary tillage conditions, which provided an environment for simulation tests and bench tests. Based on the dynamic programming, the energy management strategy of the extended-range electric rotary tilling tractor was designed, the rotary tillage operation simulation test and the bench test were carried out respectively. The results showed that the simulation results were in good agreement with the bench test results in the aspect of the forward speed, and the maximin average error was 2.18%, which was within the acceptable range, especially when operating at low speed below 0.6m/s, these two results were basically consistent. There was also a high degree of coincidence between the results of simulation and bench test in terms of the rotary tillage torque. The power values of the Genset in the bench test were larger than Genset results of the simulation, which indicated that the Genset module in the simulation underestimated the actual efficiency of the Genset of the bench. Nevertheless, the variation trend of SOC in the simulation was the same as that of the bench test results. In general, the energy management model of the extended range electric tractor can well describe the changes in the power of each motor, the power of the Genset and the SOC of the power battery pack during a given rotary tillage condition, and the fuel consumption of the simulation test and the bench test were 4065.5g and 3994.7g, respectively, the relative error was 1.77%, which verified the rationality and accuracy of the established energy management model of the extended-range electric rotary-tilling tractor. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 40
Main heading: Dynamic programming
Controlled terms: Agriculture? - ?Battery Pack? - ?Digital storage? - ?Electric drives? - ?Energy management? - ?Power takeoffs? - ?Tractors (agricultural)
Uncontrolled terms: Bench tests? - ?Dual-motor independent drive? - ?Dual-motors? - ?Electric tractors? - ?Energy management model? - ?Extended range? - ?Extended-range electric tractor? - ?Gen-sets? - ?Management Model? - ?Rotary tillages
Classification code: 525 Energy Management and Conversion? - ?663.1 Heavy Duty Motor Vehicles? - ?702.1.2 Secondary Batteries? - ?722.1 Data Storage, Equipment and Techniques? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.1 Agricultural Machinery and Equipment? - ?921.5 Optimization Techniques
Numerical data indexing: Mass 3.9947E+00kg, Mass 4.0655E+00kg, Percentage 1.77E+00%, Percentage 2.18E+00%, Velocity 6.00E-01m/s
DOI: 10.6041/j.issn.1000-1298.2023.04.045
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
4. Pigeon Behavior Detection Model Based on Improved YOLO v4
Accession number: 20232314185744
Title of translation: YOLO v4
Authors: Guo, Jianjun (1, 2); He, Guohuang (1, 2); Xu, Longqin (1, 3); Liu, Tonglai (1, 4); Feng, Dachun (1, 2); Liu, Shuangyin (1, 2)
Author affiliation: (1) College of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou; 510225, China; (2) Institute of Intelligent Agriculture InnovationZhongkai University of Agriculture and Engineering, Guangzhou; 510225, China; (3) Guangdong Big Data Engineering Research Center for Agricultural Product Safety, Zhongkai University of Agriculture and Engineering, Guangzhou; 510225, China; (4) Provincial Modern Agriculture ( Agricultural Product Quality and Safety Trace Ability), Industrial Technology R and D Center, Zhongkai University of Agriculture and Engineering, Guangzhou; 510225, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 347-355
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Pigeon whole behavior is closely related to the loft environmental comfort and pigeon whole health. For human observation and recording the pigeon whole behavior is time-consuming, sampling limited, subjective and other issues, to timely meet the pigeon whole precision detection and pigeon whole behavior and health, based on the YOLO v4 pigeon whole behavior detection method was proposed. In this method, CSPDarkNet53 was used as the Backbone network to extract feature maps covering shallow semantic information of pigeons, and then PANet was used to transfer the bottom features and stack features to the top. Aiming at the high similarity degree of pigeon social behavior features, in order to achieve accurate identification of pigeon behavior in complex environment. The adaptively spatial feature fusion (ASFF) module was adopted to improve the YOLO v4 model, and the ASFF module was added to the feature pyramid network, which can adaptively fuse multi-layer features according to the feature weights and make full use of the features information of different scales. Moreover, ASFF can effectively filter spatial conflict information and suppress reverse gradient inconsistency, improve feature proportion invariance and reduce inference overhead. Based on the cleaning and social behaviors of meat pigeons in multiple periods, a database of five kinds of meat pigeon behavior images was made. OpenCV tool was used to process blur, brightness, haze and noise to expand the image data set (totally 10320 images), increase data diversity and simulate different recognition scenes, and improve the generalization ability of the model. A 82 ratio was used to divide the training and validation sets. The training iterated 300 epochs in total, and the detection was carried out through meat pigeon data sets of different time periods, angles and sizes. The detection results showed that the detection accuracy of improved YOLO v4-ASFF model was 14.73 percentage points and 14.97 percentage points higher than that of mAP50 and mAP75 of original YOLO v4 model at the threshold of 0.50 and 0.75. Compared with Faster R-CNN,SSD, YOLO v3, YOLO v5 and CenterNet model, mAP50 of the YOLO v4-ASFF was improved by 13.98 percentage points, 14.00 percentage points, 18.63 percentage points, 14.16 percentage points and 10.87 percentage points in test set, respectively. The video detection speed was 8.1f/s, and the improved model had higher recognition accuracy under the condition of the same inference speed, strong generalization ability in complex environment, and less misdetection and omission of behaviors with high similarity. The research on meat pigeon behavior detection can provide technical reference for intelligent meat pigeon breeding and scientific management. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Image enhancement
Controlled terms: Consumer behavior? - ?Feature extraction? - ?Semantics? - ?Social behavior
Uncontrolled terms: Adaptively spatial feature fusion? - ?Behavior detection? - ?Features fusions? - ?Improved YOLO v4? - ?Multi-scale characteristic? - ?Multi-scales? - ?Percentage points? - ?Pigeon behavior detection? - ?Social behaviour? - ?Spatial features
Classification code: 931.3 Atomic and Molecular Physics? - ?971 Social Sciences
DOI: 10.6041/j.issn.1000-1298.2023.04.036
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
5. Object Detection Algorithm for Pigs Based on Dual Dilated Layer and Rotary Box Location
Accession number: 20232214170747
Title of translation:
Authors: Geng, Yanli (1, 2); Lin, Yanbo (1); Fu, Yanfang (3); Yang, Shucai (4)
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) Hebei Provincial General Animal Husbandry Station, Shijiazhuang; 050035, China; (4) Tianjin Mojieke Technology Co., Ltd., Tianjin; 300130, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 323-330
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: At present, the target detection algorithm based on horizontal box is applied to pig objection detection. The adhesion and mutual occlusion in the image of pigs bring great difficulty to individual pig detection. The image of pig has a large ratio of length to width and may rotate at any angle. Object detection algorithm for group pig images based on dual dilated layer and rotary box location network (DR-Net) was proposed. Images of pigs was collected in three pig farms. A dynamic clustering method based on histogram feature and singular value decomposition was used to extract the key frames of pig videos, Laplace operator was used to eliminate images with unclear targets. There were 9 600 images as the data set after data enhancement. The outline of the pig with rotary box was marked. Data set was divided into training set, verification set and test set according to 8: 1: 1. Dual dilated layer used the residual structure and combined two convolution with different dilation factors. The receptive field was increased exponentially with the increase of layers. Stacking dual dilated layers can obtain very large receptive field, it can help the model understand the global information of the image with fewer parameters. Every pig target was located in a rotary box and represented by five parameters. In training, regression loss calculation method based on Gaussian Wasserstein distance was used. The model can get prediction results more accurate. In DR-Net, the features of the input image was extracted by dual dilated layer. The CSP layer containing multi-layer Res2Net module, which was used to feature fusion and feature extraction of different scales. The prediction results were output through head network. The results showed that the precision, recall, mean average precision, MAE and RMSE of DR-Net were 98. 57%, 97. 27%, 96. 94%, 0. 21 and 0. 54, respectively. DR-Net was superior to YOLO v5 and YOLO v5 with rotary box location and pig target recognition accuracy was improved. By analyzing the visualization feature map, DR-Net can accurately locate the target using the head, neck, back or tail feature of pigs under occlusion and adhesion condition. The research can contribute to the construction of intelligent pig farm and provide reference for the subsequent research on pig behavior recognition. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 24
Main heading: Location
Controlled terms: Adhesion? - ?Behavioral research? - ?Convolution? - ?Image enhancement? - ?Mammals? - ?Object detection? - ?Object recognition? - ?Signal detection? - ?Singular value decomposition? - ?Statistical tests
Uncontrolled terms: Data set? - ?Dilated convolution? - ?Gaussian wasserstein distance? - ?Gaussians? - ?Object detection algorithms? - ?Objects detection? - ?Pig? - ?Pig farms? - ?Rotary box location? - ?Wasserstein distance
Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?716.1 Information Theory and Signal Processing? - ?723.2 Data Processing and Image Processing? - ?921 Mathematics? - ?922.2 Mathematical Statistics? - ?951 Materials Science? - ?971 Social Sciences
Numerical data indexing: Percentage 2.70E+01%, Percentage 5.70E+01%, Percentage 9.40E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.033
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
6. Inversion of Leaf Essential Oil Yield of Cinnamomum camphora Based on UAV Multi-spectral Remote Sensing
Accession number: 20232214170727
Title of translation:
Authors: Lu, Xianghui (1); Yang, Baocheng (1); Zhang, Haina (1); Zhang, Jie (1); Wang, Qian (1); Jin, Zhinong (1)
Author affiliation: (1) Jiangxi Provincial Engineering Research Center of Seed-Breeding and Utilization of Camphor Trees, Nanchang Institute of Technology, Nanchang; 330099, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 191-197 and 213
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Cinnamomum camphora (Linn.) Presl essential oil has great market potential in the development of forestry economy. Multi-spectral remote sensing yield prediction is a new way to efficiently invert C. camphora essential oil. The yield of essential oil in the harvest period of C. camphora was taken as the research object. Using UAV multispectral remote sensing technology, the sensitive vegetation index was selected as the input variable, and the essential oil yield of ground synchronous observation was taken as the output variable. Three machine learning methods, support vector machine (SVM), random forest (RF) and back propagation neural network (BPNN), were used to construct the estimation model of essential oil yield of C. camphora. The results showed that modified soil adjusted vegetation index (MSAVI), optimized soil adjusted vegetation index (OSAVI), renormalized difference vegetation index (RDVI), soil adjusted vegetation index (SAVI) and nonlinear vegetation index (NLI) were highly sensitive to the essential oil yield of C. camphora, and the correlation coefficients R were 0. 765 1, 0. 813 1, 0. 771 1, 0. 779 4 and 0. 818 3, respectively. The yield prediction models for essential oil of C. camphora were constructed by using three machine learning methods, SVM, RF, and BPNN. In the training set, the coefficients of determination R were 0. 723, 0. 853 and 0. 770, respectively; the root mean square errors (RMSE) were 11. 649 kg/hm, 9. 179 kg/hm and 10. 484 kg/hm, respectively; the mean relative errors (MRE) were 7. 204%, 10. 808% and 7. 181%, respectively. In the validation set, the R2 of validation set were 0. 688, 0. 869 and 0. 732, respectively; RMSE were 7. 951 kg/hm2, 5. 809 kg/ hm2, 8. 483 kg/hm2; MRE were 6. 914%, 5. 545%, 7. 999%, respectively. Through the comprehensive comparison, with MSAVI, OSAVI, RDVI, SAVI, NLI as input data, the prediction model of C. camphora essential oil yield based on RF method achieved the highest accuracy. The research can provide a theoretical basis for improving the prediction accuracy of essential oil yield of C. camphora leaves based on UAV multi-spectral remote sensing and provide technical support for rapid monitoring of large-area economic plant growth. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 41
Main heading: Remote sensing
Controlled terms: Backpropagation? - ?Essential oils? - ?Forecasting? - ?Forestry? - ?Mean square error? - ?Neural networks? - ?Soils? - ?Support vector machines? - ?Vegetation
Uncontrolled terms: Back-propagation neural networks? - ?Cinnamomum camphora? - ?Essential oil yields? - ?Inversion? - ?Multi-spectral? - ?Random forests? - ?Remote-sensing? - ?Support vectors machine? - ?Three machine learning methods? - ?Vegetation index
Classification code: 483.1 Soils and Soil Mechanics? - ?723 Computer Software, Data Handling and Applications? - ?723.4 Artificial Intelligence? - ?804.1 Organic Compounds? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?922.2 Mathematical Statistics
Numerical data indexing: Mass 1.79E+02kg, Mass 4.83E+02kg, Mass 4.84E+02kg, Mass 6.49E+02kg, Mass 8.09E+02kg, Mass 9.51E+02kg, Percentage 1.81E+02%, Percentage 2.04E+02%, Percentage 5.45E+02%, Percentage 8.08E+02%, Percentage 9.14E+02%, Percentage 9.99E+02%
DOI: 10.6041/j.issn.1000-1298.2023.04.018
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
7. Blockchain Multi-chain Model of Fruit and Vegetable Supply Chain for Traceability Subjects
Accession number: 20232314185724
Title of translation:
Authors: Sun, Chuanheng (1); Wan, Yuping (1); Luo, Na (2, 3); Xu, Daming (2, 3); Xing, Bin (2, 3); Yang, Xinting (2, 3)
Author affiliation: (1) College of Information Technology, Shanghai Ocean University, Shanghai; 201306, China; (2) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (3) National Engineering Laboratory for Agri - Prodnet Quality Traceability, Beijing; 100097, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 416-427
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In recent years, agricultural food safety problems have occurred frequently, which seriously infringe on people’s health. Due to the traceability feature of blockchain technology, the agricultural food traceability system based on blockchain was introduced, aiming to better supervise all traceability data generated in the supply chain and ensure food safety. The multi-chain traceability system of agricultural food was established for the whole supply chain. It stored traceability data for multiple participating subjects in blockchain. Due to the difference of traceability demand data of each subject, it was difficult to realize data sharing and access control across supply chain links, it was also difficult to protect sensitive data in a differentiated way, and risk traceability data cannot be subjected to targeted supervision. Therefore, the traceability data for different subjects was not suitable to be stored in the same ledger. Based on this idea, a subject-oriented chain building method was proposed, in which the traceability data for different traceability participating subjects were stored in different blockchains. By analyzing the traceability subjects in the fruit and vegetable supply chain, a multi-chain traceability architecture was established based on the traceability participating subjects. The traceability demand of consumers were realized through the traceability chain, the data flow among enterprises was realized through the sharing chain, the security protection and authorization sharing of the enterprise’s private data were realized based on the privacy chain, and the regulatory chain was used to realize the management and control of risk data in all links by the regulatory authorities. A subject-oriented multi-chain traceability system was designed and implemented based on Hyperledger Fabric. A suitable storage scheme was designed according to the characteristics of each blockchain. At the same time, in order to ensure the authenticity of the data obtained by each subject after data sharing, a collaborative verification method was proposed to achieve this purpose. The test results showed that the average query time of the traceability chain was 38.86ms, the average time to obtain real shared data was about 806.80ms, the average time to obtain real private data was about 910.35ms, and the average time to obtain real regulatory data was about 675.90ms. The subject-oriented chain building traceability system solved the problems existing in the previous blockchain multi chain system on the basis of realizing the traceability requirements of each subject, and provided reference significance for fruit and vegetable blockchain traceability system. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 30
Main heading: Supply chains
Controlled terms: Authorization? - ?Blockchain? - ?Digital storage? - ?Distributed ledger? - ?Food safety? - ?Fruits? - ?Information management? - ?Safety engineering? - ?Sensitive data? - ?Vegetables
Uncontrolled terms: Agricultural foods? - ?Block-chain? - ?Data regulatory? - ?Data Sharing? - ?Fruit and vegetable traceability? - ?Fruit and vegetables? - ?Hyperledg fabric? - ?Multi-chain data sharing? - ?Traceability subject? - ?Traceability systems
Classification code: 461.6 Medicine and Pharmacology? - ?722.1 Data Storage, Equipment and Techniques? - ?723 Computer Software, Data Handling and Applications? - ?723.2 Data Processing and Image Processing? - ?723.3 Database Systems? - ?821.4 Agricultural Products? - ?822.3 Food Products? - ?911.3 Inventory Control? - ?912 Industrial Engineering and Management? - ?913 Production Planning and Control; Manufacturing? - ?914 Safety Engineering
Numerical data indexing: Time 3.886E-02s, Time 6.759E-01s, Time 8.068E-01s, Time 9.1035E-01s
DOI: 10.6041/j.issn.1000-1298.2023.04.044
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
8. Design and Hydroponic Monitoring of Flexible Electroconductivity Chip
Accession number: 20232314185779
Title of translation:
Authors: Zhang, Miao (1, 2); Wang, Liru (1); Li, Haozhen (1); Lu, Xiao (1); Wang, Jin (1); Liu, Gang (1, 2)
Author affiliation: (1) Key Laboratory of Smart Agriculture Systems, China Agricultural University, Ministry of Education, Beijing; 100083, China; (2) China AgricuItural University, Key leboratory of Agricultural Information Acquisition Technology, Ministry of Agricult ure and Rural Affairs, Beijing; 100083, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 386-393
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In view of the existing problems in the detection of agricultural conductivity, such as complex detection methods, large instrument volume and high requirements for internal components, and in order to improve the detection efficiency and reduce the size of the sensor, a single-walled carbon nanotube flexible conductivity sensor chip based on ink-jet printing was designed and fabricated. The sensor chip was modeled and calibrated by AC impedance spectroscopy. The response time, stability, repeatability, bending and packaging effect of the sensor chip were systematically tested, and the error between the flexible sensor chip and the commercial EC electrode was determined. The feasibility of applying the flexible chip to the on-line monitoring of EC of soilless lettuce nutrient solution was verified. The experimental results showed that the total chip area was about 30mm×40mm, realizing miniaturization of detection. The conductivity range of modeling and calibration was 25.8~3098μS/cm, and the measurement impedance range was 160~15000Ω. There was an obvious power function relationship between the standard conductivity value and the measured impedance value, and the correlation coefficient was 0.99. The absolute error range of the verification test was -99.76~115.62μS/cm, and the relative error range was -5.89%~8.02% (FS). The measurement results of the flexible chip were in good agreement with the EC standard value. The maximum response time of the flexible EC sensor chip was 10s. The stability fluctuation within 12h was 3.91μS/(cmDK·h), and the absolute error range of five repeated measurements was -74~62μS/cm. The stability and repeatability were in good agreement with commercial EC electrodes. Bending in the range of 0°~90° and PDMS packaging had no effect on its performance. In the monitoring of EC value of hydroponic lettuce for 10 consecutive days, the maximum deviation between the flexible EC sensor chip and the commercial EC sensor was 46μS/cm. The flexible chip showed good consistency with the commercial electrode, and its micro flexibility was more suitable for hydroponic rhizosphere monitoring. The flexible EC sensor chip can monitor the EC value of soilless culture nutrient solution in real time and accurately, which had a good prospect of agricultural application. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Hydroponics
Controlled terms: Electrodes? - ?Errors? - ?Ink jet printing? - ?Lettuce? - ?Nutrients? - ?Single-walled carbon nanotubes (SWCN)? - ?Soils? - ?Substrates? - ?Titanium dioxide
Uncontrolled terms: Absolute error? - ?Conductivity detection? - ?Electroconductivity? - ?Error range? - ?Flexible chip? - ?Nutrient solution? - ?Sensor chips? - ?Single Wall? - ?Single wall carbon nanotube? - ?Soil-less culture
Classification code: 483.1 Soils and Soil Mechanics? - ?745.1 Printing? - ?761 Nanotechnology? - ?804.2 Inorganic Compounds? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?933.1 Crystalline Solids
Numerical data indexing: Electrical conductance 3.91E-06S, Electrical conductivity 2.58E-03S/m to 3.098E-01S/m, Electrical conductivity 4.60E-03S/m, Electrical conductivity 7.40E-03S/m to 6.20E-03S/m, Electrical conductivity 9.976E-03S/m to 1.1562E-02S/m, Electrical resistance 1.60E+02Ohm to 1.50E+04Ohm, Percentage -5.89E+00%, Percentage 8.02E+00%, Size 3.00E-02m, Size 4.00E-02m, Time 1.00E+01s, Time 4.32E+04s
DOI: 10.6041/j.issn.1000-1298.2023.04.040
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
9. Automatic Retraction Control System of Rotors Hovering Spray Boom Sprayer
Accession number: 20232214170737
Title of translation:
Authors: Zhou, Zhiyan (1, 2); Xiang, Ying (1, 3); Chen, Yuli (1, 4); Yu, Xin (1, 5); Liu, Zibo (1, 3); Zheng, Dateng (6)
Author affiliation: (1) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou; 510642, China; (3) Guangdong Engineering Research Center for Agricultural Aviation Application (ERCAAA), Guangzhou; 510642, China; (4) Guangdong Provincial Key Laboratory of Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou; 510642, China; (5) Key Laboratory of Key Technology on Agricultural Machine and Equipment, South China Agricultural University, Ministry of Education, Guangzhou; 510642, China; (6) Institute of Mechanical and Electrical Technology, Jinggangshan University, Ji’an; 343009, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 120-131
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The rotor suspended spray bar combines the advantages of ground machinery and aerial UAV respectively, which can simplify the complex truss structure and reduce the secondary pollution caused by droplet drift through the rotor downwind field. It has a good application prospect. It is difficult to retract the rotor suspended spray bar in the traditional retraction and retraction mode. Therefore, an automatic boom retraction and retraction device with a regular quadrilateral cylinder as the main body was proposed, the D-H coordinate system and the forward kinematics model of the boom retraction and retraction process were established, the dynamics model was constructed by Newton Euler method, and the optimal trajectory of the boom retraction and retraction was obtained by using cubic uniform B-spline curve trajectory planning. Taking the movement time, joint impact and energy consumption of the boom retraction and retraction as the multi-objective function, the Pareto solution set was solved by NSGA-II algorithm. The boom retraction and retraction test was conducted by selecting the trajectory of the boom deployment time in the solution set as 56 s, 61 s, 66 s, 71 s, 76 s and 81 s, and the boom retraction time as 54 s, 59 s, 64 s, 69 s, 74 s and 79 s. The test results showed that there was a significant relationship between the movement time of the spray bar and the standard deviation of the spray bar angle. The shorter the movement time was, the worse the stability of the spray bar was, the greater the joint impact was, and the more energy consumption was. When the trajectory corresponding to the boom retraction time of 59 s, 61 s was taken as the optimal trajectory for boom retraction and retraction, the average tracking error between the drum speed and the planned speed was no more than 0. 201 (°)/s, and the average tracking error between the actual motion angle and the planned angle of joints 3, 4, and 5 was no more than 6. 201°. The boom can better track the optimal trajectory to complete retraction and retraction. The research verified the effectiveness of the automatic boom retraction and retraction device and the accuracy of the optimal trajectory of boom retraction and retraction. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Three term control systems
Controlled terms: Antennas? - ?Curve fitting? - ?Energy utilization? - ?Proportional control systems? - ?Trajectories? - ?Unmanned aerial vehicles (UAV)
Uncontrolled terms: Automatic adjustment? - ?Automatic retraction and playback? - ?Boom sprayer? - ?Energy-consumption? - ?Movement time? - ?Optimal trajectories? - ?Retraction devices? - ?Rotor hovering spray boom? - ?Spray booms? - ?Trajectory Planning
Classification code: 525.3 Energy Utilization? - ?652.1 Aircraft, General? - ?731.1 Control Systems? - ?921.6 Numerical Methods
Numerical data indexing: Time 5.40E+01s, Time 5.60E+01s, Time 5.90E+01s, Time 6.10E+01s, Time 6.40E+01s, Time 6.60E+01s, Time 6.90E+01s, Time 7.10E+01s, Time 7.40E+01s, Time 7.60E+01s, Time 7.90E+01s, Time 8.10E+01s
DOI: 10.6041/j.issn.1000-1298.2023.04.011
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
10. Design and Experiment of Mechanism of Wave Screen for Maize Grain Cleaning
Accession number: 20232214170729
Title of translation:
Authors: Feng, Xin (1, 2); Wang, Lijun (1, 2); Yu, Kunmeng (1, 2); Gao, Yunpeng (1, 2); Bi, Shengying (1, 2); Wang, Bo (1, 2)
Author affiliation: (1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) Key Laboratory oj High Efficient Seeding and Harvesting Equipments, Ministry of Agriculture and Rural Affairs, Harbin; 150030, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 142-154
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: To improve the performanee of cleaning device under the condition of large feeding mass of maize mixture, a wave screen for maize grain cleaning was designed based on crank and double rockers mechanism. The concave and approximate flattening of the wave screen were realized by the combined movement of multi-stage screens. Structure of wave sieve was determined based on theoretical analysis. CFD-DEM method was used for numerical simulating the motion of gas-solid two-phase in wave screen cleaning device. A high speed airflow belt could be formed in the upper space in the cleaning device, which was beneficial to the blowing of impurities. The airflow velocity near the wave sieve was decreased first and then increased along the longitudinal direction of wave sieve. The airflow distribution near sieve layer was beneficial to the migration and temporary retention of materials on sieve when sieve group moved in wave mode. Maize grains successively completed the impact on the screen, retention, which were thrown and passed over the screen under the motion of the wave screen, which could improve the efficiency of grain penetrating the sieve hole. The air velocity at the inlet of the cleaning device, the angle of installed screen and rotational speed of drive shaft were selected as the test factors. The loss rate, cleaning rate and screening efficiency of maize grains were selected as test indexes. The quadratic orthogonal rotation combination test was carried out. The mathematical models between factors and indicators were established. The best combination of parameters was obtained as follows; the airflow velocity of cleaning device inlet was 14. 6 m/s, the angle of installed screen was 8. 5°, and the rotational speed of drive shaft was 240 r/min. The high-speed camera bench test was carried out. The motion of the grains on the wave screen in the bench test was as same as that in the simulation, which verified the accuracy of the simulation result. When the feeding mass of maize mixture was as large as 7 kg/s, the cleaning rate of grains after screening by wave sieve was 99. 12%, and the loss rate of grains was reduced by 0. 45%. The time of screening 21 kg maize mixture was 6. 86 s, and the mechanism of wave screen could meet the requirement of cleaning large feeding mass of maize mixture. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Cleaning
Controlled terms: Air? - ?Efficiency? - ?Feeding? - ?Grain (agricultural product)? - ?High speed cameras? - ?Numerical methods? - ?Sieves
Uncontrolled terms: Air flow velocity? - ?Cleaning devices? - ?Cleaning rate? - ?Driving mechanism? - ?Large feeding mass? - ?Loss rates? - ?Maize grain cleaning? - ?Motion of grain? - ?Rotational speed? - ?Wave screens
Classification code: 691.2 Materials Handling Methods? - ?742.2 Photographic Equipment? - ?802.3 Chemical Operations? - ?804 Chemical Products Generally? - ?821.4 Agricultural Products? - ?913.1 Production Engineering? - ?921.6 Numerical Methods
Numerical data indexing: Angular velocity 4.008E+00rad/s, Mass 2.10E+01kg, Mass flow rate 7.00E+00kg/s, Percentage 1.20E+01%, Percentage 4.50E+01%, Time 8.60E+01s, Velocity 6.00E+00m/s
DOI: 10.6041/j.issn.1000-1298.2023.04.013
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
11. Insect Pest Detection of Field Crops Based on Improved YOLOF Model
Accession number: 20232214170736
Title of translation: YOLOF
Authors: Peng, Hongxing (1, 2); Xu, Huiming (1); Gao, Zongmei (3); Tian, Xingguo (4); Deng, Qianting (5); Xian, Chunlong (6)
Author affiliation: (1) College of Mathematics and Informatics, South China Agricultural University, Guangzhou; 510642, China; (2) Key Laboratory of Smart Agricultural Technology in Tropical South China, Ministry of Agriculture and Rural Affairs, Guangzhou; 510642, China; (3) Department of Biological Systems Engineering, Washington State University, Pullman; WA; 99350, United States; (4) College of Food Science, South China Agricultural University, Guangzhou; 510642, China; (5) Assets and Laboratory Management Office, South China Agricultural University, Guangzhou; 510642, China; (6) College of Economics and Management, South China Agricultural University, Guangzhou; 510642, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 285-294 and 303
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The wide distribution of pests in the field leads to diffieulties in image data acquisition, and most of the traditional detection models use complex feature pyramid network (FPN) to enhance detection accuracy, which affects the real-time detection to some extent. To this end, the trap lamp device was designed to construct the pest dataset FieldPest5 and the detector YOLOF, which does not use the FPN structure, was improved to propose a pest detection model YOLOF_PD that balanced detection accuracy and efficiency. Firstly, the Cutout data augmentation method was added to alleviate the occlusion problem in the pest images, and the complete intersection over union (CIolI) loss function was used to obtain better box regression positions. Secondly, the adaptive coordinate attention (AC A) mechanism was proposed to enhance the information representation capability of the model. Specifically, the global maximum pooling (GMP) path was added to the global average pooling (GAP) path of the original coordinate attention (CA) mechanism, and the weights of different paths were updated adaptively by using learnable parameters. Finally, the Dilated _ Dwise _ AC A encoder was proposed to improve the performance of YOLOF for small-scale pest detection. Improvements were made to the projector and residual modules in the dilated encoder. The ACA attention mechanism was introduced after the 3x3 convolution in the projector module, and in the Residual module 3x3 depth-separable convolution and lxl pointwise convolution were fused. The experimental results showed that the improved YOLOF_PD model mAP achieved 93. 7% on the FieldPest5 test set, which was 2. 1 percentage points higher than that of the model before improvement, and the detection speed was 42. 4 f/s, which can meet the requirements of fast pest detection. Compared with Cascade R-CNN, RetinaNet and ATSS, YOLOF_PD achieved good performance in terms of detection effect and detection speed. The research result can lay a solid foundation for field pest data collection as well as real-time pest detection. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 34
Main heading: Convolution
Controlled terms: Data acquisition? - ?Feature extraction? - ?Image enhancement? - ?Signal encoding
Uncontrolled terms: Adaptive coordinate attention? - ?Attention mechanisms? - ?Detection accuracy? - ?Detection models? - ?Feature pyramid? - ?Insect trap lamp? - ?Multi-scale features? - ?Pest detection of field? - ?Pyramid network? - ?YOLOF
Classification code: 716.1 Information Theory and Signal Processing? - ?723.2 Data Processing and Image Processing
Numerical data indexing: Percentage 7.00E+00%
DOI: 10.6041/j.issn.1000-1298.2023.04.029
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
12. Optimization and Experiment on Process Parameters of Hot Pressing Bonding of Seaweed Sheet
Accession number: 20232314185760
Title of translation:
Authors: Chen, Kunjie (1); He, Xinye (1); Qi, Hengyang (2); Yang, Haoyong (3); Yu, Haiming (1)
Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Lianyungang Haigong Machinery Co.Ltd., Lianyungang; 222100, China; (3) Jiangsu Agricultural Machinery Test and Appraisal Station, Nanjing; 210017, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 407-415
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the existing sandwich seaweed production equipment uses a single piece of seaweed to process and produce one by onethere are many problemssuch as too many dropped sandwich materialsand it is difficult to accurately align two pieces of seaweedresulting in serious material wastepoor product qualityand low production efficiencythus a processing method of bonding a single sheet of seaweed into a ribbon-shaped seaweed sheet by hot pressing bonding was pioneeredand the experimental research and parameter optimization of the hot pressing bonding process of this seaweed sheet was carried out. Firstlythe effects of hot pressing temperaturehot pressing time and alcohol concentration on the toughness and adhesion of the bonded seaweed sheet were studied by single factor experiment. Thenthrough quadratic regression orthogonal test and response surface analysisthe influence law of each factor on the evaluation index was studiedand the mathematical model between each influencing factor and the evaluation index was established. Finallythrough the solution of the mathematical modelthe hot pressing bonding process parameters of seaweed tablets were optimizedand the optimization results were verified by experiments. The test results showed that hot pressing temperaturehot pressing time and alcohol concentration had significant effects on the toughness and adhesion of seaweed sheets (P ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 33
Main heading: Adhesion
Controlled terms: Hot pressing? - ?Production efficiency? - ?Seaweed? - ?Surface analysis
Uncontrolled terms: Alcohol concentrations? - ?Hot press bonding? - ?Hot pressing temperature? - ?Hot pressing time? - ?Optimisations? - ?Pressing bonding? - ?Process parameters? - ?Processing method? - ?Response-surface methodology? - ?Seaweed sheet
Classification code: 471.1 Oceanography, General? - ?913 Production Planning and Control; Manufacturing? - ?913.4 Manufacturing? - ?951 Materials Science
Numerical data indexing: Force 1.36E+00N, Force 8.86E+00N, Percentage 6.152E+01%, Time 2.91E+00s
DOI: 10.6041/j.issn.1000-1298.2023.04.043
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
13. Method for Millimeter Wave Radar Farm Obstacle Detection Based on Invalid Target Filtering
Accession number: 20232214170742
Title of translation:
Authors: Xue, Jinlin (1); Cheng, Feng (1); Wang, Bingqing (2); Li, Yuqing (1); Ma, Zhengbao (3); Chu, Yangyang (1)
Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Jiangsu Agricultural Machinery Information Center, Nanjing; 210017, China; (3) Jiangsu Agricultural Machinery Development and Application Center, Nanjing; 210017, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 233-240
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Farmland obstacle detection is a prerequisite for automatic driving of farm machinery. For farmland obstacle detection based on millimeter wave radar, an algorithm for invalid target filtering was proposed. Firstly, the target information output from the millimeter wave radar was analyzed and the farmland target obstacle information was extracted, and then the empty target, pseudo target and non-threat data were filtered out by using the invalid target filtering algorithm. The empty targets with zero target distance in the radar data were directly filtered out; the pseudo targets generated by the radar working performance or unstable echo signal were filtered by the radar effective target life cycle method; the non-threat targets exceeding the horizontal distance threshold and vertical distance threshold were directly filtered out. The experimental results showed that the average filtering rate of the proposed algorithm reached more than 85% in the static state. When the speed was 3 km/h, the average filtration rate was 85. 24% in the non-working state and 84. 23% in rotary tillage. When the speed was 5 km/h, 84. 22% were not operated and 84. 18% were rotary tillage. When the speed was 7 km/h, the non-operation was 84. 19%, and the rotary tillage was 84. 16%. The experimental results showed that although the filtering rate was decreased to a certain extent with the increase of speed or hanging rototiller tool in the driving state, the filtering rate of the proposed algorithm could reach more than 84% either in the stationary state or in the driving state. This method can be used to detect obstacles in farmland under complex environment. Under driving conditions, the experimental results showed that the vibration of the tractor had a large influence on the filtering effect. In order to reduce the impact of vibration, a device for millimeter wave radar vibration damping was designed, through the experimental verification, it was showed that the device vibration damping effect was obvious, the average filtering rate in the unoperated state reached more than 84%, which can help to reduce the impact of tractor vibration. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 25
Main heading: Information filtering
Controlled terms: Automobile drivers? - ?Farms? - ?Life cycle? - ?Millimeter waves? - ?Obstacle detectors? - ?Signal processing? - ?Tractors (agricultural)
Uncontrolled terms: Automatic driving? - ?Average filtering? - ?Driving state? - ?Farm obstacle detection? - ?Invalid target? - ?Millimeter-wave radar? - ?Millimetre-wave radar? - ?Obstacles detection? - ?Rotary tillages? - ?Vibration-damping
Classification code: 432 Highway Transportation? - ?663.1 Heavy Duty Motor Vehicles? - ?711 Electromagnetic Waves? - ?716.1 Information Theory and Signal Processing? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.1 Agricultural Machinery and Equipment? - ?903.1 Information Sources and Analysis? - ?912.4 Personnel
Numerical data indexing: Percentage 1.60E+01%, Percentage 1.80E+01%, Percentage 1.90E+01%, Percentage 2.20E+01%, Percentage 2.30E+01%, Percentage 2.40E+01%, Percentage 8.40E+01%, Percentage 8.50E+01%, Size 3.00E+03m, Size 5.00E+03m, Size 7.00E+03m
DOI: 10.6041/j.issn.1000-1298.2023.04.023
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
14. Spatiotemporal Variation and Driving Factors for FVC in Huaihe River Basin from 1987 to 2021
Accession number: 20232214170726
Title of translation: 1987—2021FVC
Authors: Zhao, Shengnan (1); Wang, Yu (1); Qiao, Xuning (1); Zhao, Tongqian (2)
Author affiliation: (1) School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo; 454000, China; (2) School of Resource and Environment, Henan Polytechnic University, Jiaozuo; 454000, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 180-190
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Vegetation coverage and its response is an important topic in current global change research. Studying the temporal and spatial change trend of vegetation coverage in the Huaihe River basin is of great significance for revealing the evolution and driving mechanism of fragile ecosystems in the climate transition zone. The Landsat images on the Google Earth Engine (GEE) platform were used to calculate the fraction of vegetation coverage (FVC) of the Huaihe River basin, and the temporal and spatial change characteristics of FVC were analyzed. The driving factors of FVC were analyzed from interannual and spatial scales with the data of night light, temperature, precipitation, evapotranspiration, soil and topography. The results showed that from 1987 to 2021, the overall FVC in the Huaihe River basin showed an increasing trend. The change trend of FVC was mainly stable and improved in space, accounting for 45. 2% and 39. 7%, respectively. The improvement area was concentrated in Xinyang, Zhumadian, Nanyang, Luoyang, etc., while the degradation area was mainly found in Nantong, Taizhou, Yancheng, Linyi, Weifang, Zhengzhou, Fuyang, etc. On the interannual scale, the correlation between FVC change and night light data was higher than that of temperature and precipitation, and the increasing trend of FVC in Huaibei was not as significant as that in Huainan. On the spatial scale, nighttime light, potential evapotranspiration, precipitation and terrain were the main factors affecting the spatial differences of FVC in the Huaihe River basin, and human activities represented by nighttime light had the greatest impact on FVC. The influence of nighttime lighting data on FVC change had spatial heterogeneity; the area of positive correlation area accounted for 25. 4%, mainly cultivated land and forest land. The area of negatively correlated areas accounted for 14. 7%, mainly distributed in the central urban areas of prefecture-level cities and even counties. The joint effect of human activities and natural factors was the main cause of vegetation change in Huaihe River basin in the past 35 years. The average contribution of human activities and natural factors to FVC change was 56. 0% and 44. 0%, respectively. The research results can provide support for the formulation of green urbanization road and ecological protection policy in China. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 34
Main heading: Climate change
Controlled terms: Evapotranspiration? - ?Forestry? - ?Land use? - ?Rivers? - ?Topography? - ?Vegetation? - ?Watersheds
Uncontrolled terms: Change trends? - ?Driving factors? - ?Fraction of vegetation coverage? - ?Google earth engine? - ?Google earths? - ?Huaihe river basins? - ?Human activities? - ?Night lights? - ?Temporal and spatial changes? - ?Vegetation coverage
Classification code: 403 Urban and Regional Planning and Development? - ?443.1 Atmospheric Properties? - ?444.1 Surface Water? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?951 Materials Science
Numerical data indexing: Age 3.50E+01yr, Percentage 0.00E00%, Percentage 2.00E+00%, Percentage 4.00E+00%, Percentage 7.00E+00%
DOI: 10.6041/j.issn.1000-1298.2023.04.017
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
15. Design and Experiment of Rice Straw Biaxial Deep-buried Returning Machine
Accession number: 20232214170751
Title of translation:
Authors: Wang, Jinfeng (1); Yang, Dongze (1); Wang, Zhentao (1); Fu, Zuodong (1); Wang, Jinwu (1); Weng, Wuxiong (1)
Author affiliation: (1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 21-30
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In view of the problems that traditional single-axis machines are difficult to adapt to the wet and clay soil conditions covered with a large amount of straw when straw is returned to the rice field in the northern cold region, the problem that the quality of work is difficult to meet the needs of actual work. A type of rice straw double-shaft deep-buried returning machine with forward rotation of the front shaft and reverse rotation of the rear shaft was designed. Combined with the actual agronomic requirements and the soil movement process, the horizontal distance between the center of the front and rear knife shafts was 650 mm and the vertical distance was 100 mm, and the whole machine was configured. The EDEM simulation software was used to simulate the working process of the field returning machine. Taking the forward speed, front axle speed and rear axle speed as the test factors, and taking the straw returning rate and the power consumption of the machine as the evaluation indicators, an orthogonal test was carried out to establish the straw returning rate and the machine tool power consumption regression equation. Design-Expert analysis software was used to obtain the optimal parameter combination, and the optimal working parameters were determined according to the simulation optimization results and actual processing requirements; forward speed was 1. 5 km/h, front axle speed was 274. 2 r/min, rear axle speed was 219. 4 r/min, providing theoretical support for subsequent field experiments. The field test results showed that when the stubble height was 15 ~ 20 cm, the surface straw coverage was 468-578 g/m, and the forward working speed of the tractor was the first gear of low speed (1. 5 km/h), the rice straw biaxial deep burial returning machine can still be used. The field rate was 88. 7%-91. 2%, the ground flatness was 1. 8-2. 4 cm, the broken soil rate was 97. 7%-98. 8%, and the tillage depth was 16. 6-19. 5 cm. All indicators met the agronomic requirements, which improved the straw returning rate and the broken soil rate, at the same time, there was no phenomenon of stagnant soil in front of the machine. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 32
Main heading: Electric power utilization
Controlled terms: Agricultural machinery? - ?Clay? - ?Computer software
Uncontrolled terms: Axis machines? - ?Discrete-element simulations? - ?Double shaft? - ?Field test? - ?Forward speed? - ?Rice staw? - ?Rice straws? - ?Single-axis? - ?Straw returning? - ?Wet soil
Classification code: 483.1 Soils and Soil Mechanics? - ?706.1 Electric Power Systems? - ?723 Computer Software, Data Handling and Applications? - ?821.1 Agricultural Machinery and Equipment
Numerical data indexing: Angular velocity 3.34E-02rad/s, Angular velocity 6.68E-02rad/s, Linear density 4.68E-01kg/m to 5.78E-01kg/m, Percentage 2.00E+00%, Percentage 7.00E+00%, Percentage 8.00E+00%, Size 1.00E-01m, Size 1.50E-01m to 2.00E-01m, Size 4.00E-02m, Size 5.00E+03m, Size 5.00E-02m, Size 6.50E-01m
DOI: 10.6041/j.issn.1000-1298.2023.04.002
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
16. Identification of Early Wheel Spot and Rust on Sugarcane Leaves Based on Spectral Analysis
Accession number: 20232214170711
Title of translation:
Authors: Huang, Yiqi (1); Liu, Xianghuan (1, 2); Huang, Zhenyu (1, 2); Qian, Wanqiang (2); Liu, Shuangyin (3); Qiao, Xi (1, 2)
Author affiliation: (1) College of Mechanical Engineering, Guangxi University, Nanning; 530004, China; (2) Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen; 518120, China; (3) College of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou; 510225, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 259-267
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problem that the symptoms of early wheelspot disease and rust disease on sugarcane leaves are similar and difficult to distinguish, which leads to the inconvenience of prescribing the right medicine to the disease in actual production. The feasibility of using hyperspectral imaging technology to identify early wheel spot disease and rust disease on sugarcane leaves was explored. Firstly, hyperspectral images of healthy sugarcane leaves, early wheel spot leaves and rust leaves were collected by hyperspectral imaging system in the spectral range of 406 ~ 1 014 nm. The average spectral reflectance of region of interest (ROI) was extracted and its average spectrum was calculated as the raw spectral data. The first derivative (FD), Savitzky-Golay convolution smoothing (SG) and standard normal variate (SNV) were used to preprocess the original spectral data. Then on the basis of preprocessing, principal component analysis (PCA) and ant colony optimization (ACO) were used to reduce the feature dimension, and the feature after dimensionality reduction were used as the input variables in the later modeling. Finally, the support vector machine (SVM) and random forest (RF) were used for recognition by combining dimensionality reduction and non-dimensionality reduction. In order to determine the optimal recognition model, totally 18 combined models with different preprocessing methods, dimensionality reduction methods and classifiers were tested. By comparison, it was found that the SG-SVM recognition model had the best effect, and the accuracy of the test set was 99. 65%. It was feasible and effective to use hyperspectral imaging technology to identify early wheel spot and rust on sugarcane leaves, which can provide reference for ultra-low altitude remote sensing disease monitoring of plant protection UAV. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 33
Main heading: Support vector machines
Controlled terms: Ant colony optimization? - ?Forestry? - ?Hyperspectral imaging? - ?Image segmentation? - ?Plants (botany)? - ?Principal component analysis? - ?Remote sensing? - ?Wheels
Uncontrolled terms: Data preprocessing? - ?Dimension reduction? - ?Dimensionality reduction? - ?Disease recognition? - ?Hyperspectral imaging technologies? - ?Rust disease? - ?Spectral data? - ?Spectral dimension reduction? - ?Spectral dimensions? - ?Sugarcane leaf
Classification code: 601.2 Machine Components? - ?723 Computer Software, Data Handling and Applications? - ?746 Imaging Techniques? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?921.5 Optimization Techniques? - ?922.2 Mathematical Statistics
Numerical data indexing: Percentage 6.50E+01%, Size 1.40E-08m
DOI: 10.6041/j.issn.1000-1298.2023.04.026
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
17. Machine Learning Based 3D in Situ Visual Discriminant Analysis of Mammalian and Non-mammalian Bone Meals by Micro-CT
Accession number: 20232314185768
Title of translation: Micro-CT
Authors: Zhu, Ying (1); Gao, Bing (1); Shi, Zhuolin (1); Xie, Ruyue (1); Liu, Xian (1); Han, Lujia (1)
Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China
Corresponding author: Han, Lujia(hanlj@can.edu.cn)
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 394-398+438
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Rapid discriminant analysis of meat and bone meal from different animal origin species is an important guarantee to strengthen feed supervision and prevent the spread of BSE disease. In order to explore the feasibility of using advanced micro-computed tomography (Micro-CT) to rapidly identify and analyze meat and bone meal from different species of animals, a calibration sample set and two validation sample sets consisted of different amount of avian origin and bovine bone particles were prepared. The Bruker Skyscan 1275 Micro-CT system was used to build method for 3D in situ visual characterization. The Micro-CT conditions for sample scaning and images reconstructing were: tube voltage of 80kV, tube current of 125μA, image resolution of 10μm, reconstructed gray-scale image of from 0 to 255, and the corresponding X-ray absorption coefficient was from 0 to 0.035. The regions of interest of different bone particle samples were extracted for image segmentation. Combined with PLS-DA and SVM-DA machine learning algorithms, avian origin and bovine origin bone particle image segmentation models were constructed, respectively. Finally, the Micro-CT in situ 3D visual discriminant analysis of avian origin and bovine bone particles were carried out. The main results were as follows: the gray range of the regions of interest for image segmentation of chicken and bovine bone particles was 165~255. The total accuracy of cross validation of chicken and bovine bone particles based on PLS-DA and SVM-DA models was 94%. The Micro-CT 3D in situ visualization results of the verification set samples were verified to be consistent with the actual results of the samples. The verification results showed that the established Micro-CT 3D in situ visual discriminant analysis method achieved very consistent results with that of the actual samples. The research result can provide an imaging methodology for 3D in situ visual discriminant analysis for rapid and non-invasive identification of different species of animal origin material in feed. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 30
Main heading: Visualization
Controlled terms: Computerized tomography? - ?Discriminant analysis? - ?Image reconstruction? - ?Image resolution? - ?Image segmentation? - ?Learning algorithms? - ?Machine learning? - ?Mammals? - ?Three dimensional computer graphics? - ?X ray absorption
Uncontrolled terms: 3d in situ visualization? - ?Animal-derived bone? - ?Bone-particles? - ?Bovine bone? - ?Discriminant? - ?Machine-learning? - ?Meat and bone meal? - ?Micro-computed tomography? - ?Sample sets? - ?Situ visualization
Classification code: 711 Electromagnetic Waves? - ?723.2 Data Processing and Image Processing? - ?723.4 Artificial Intelligence? - ?723.4.2 Machine Learning? - ?723.5 Computer Applications? - ?903.1 Information Sources and Analysis? - ?922 Statistical Methods
Numerical data indexing: Electric current 1.25E-04A, Percentage 9.40E+01%, Size 1.00E-05m, Voltage 8.00E+04V
DOI: 10.6041/j.issn.1000-1298.2023.04.041
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
18. Field Broccoli Head Recognition Technology Based on Laws and Gabor Filter
Accession number: 20232214170753
Title of translation: LawsGabor
Authors: Zhao, Xiong (1, 2); Xu, Gangji (1); Chen, Jianneng (1); Yu, Gaohong (1); Dai, Li (1, 2)
Author affiliation: (1) Faculty of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province, Hangzhou; 310018, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 313-322
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Correctly identifying the field location of broccoli is the basis for realizing automatic harvesting of broccoli. Because the flower ball color is similar to the plant stem, broccoli cannot be identified only by color features. The algorithm firstly strengthened the boundary texture of the image through pretreatment and Laws filter, in which the filter kernel function of Laws adopted E5 xEs. Then Gabor filter was applied to the texture enhanced image, and Gabor transform which was a short-time window Fourier transform proposed to meet the locality of two dimensional images in spatial and frequency domain, with window function of Gaussian function. Through Gabor filter, each pixel had a 1 X 8 dimensions texture feature vector, which was generated by eight different Gabor filtering kernel functions that were determined by the wavelengths of one sinusoidal modulation wave and the directions of eight different kernel functions. The texture feature vector was zero-mean normalization to speed up the convergence of clustering process, and K-means clustering segmentation and open operation were performed to obtain the potential region of broccoli heads. Meanwhile, the image was segmented based on color features. Through converting RGB (red, green, blue) image into HSV (Hue, Saturation, Value) image, the Hue component of the image was threshold to filter out ground pixels. Finally, the results of texture feature recognition and color feature recognition were fused to realize the recognition of field broccoli heads. A total of 792 images were used for the experiment. The experimental results showed that this method could accurately identify the broccoli field images. The precision rate was 96. 96%, the recall rate was 94. 41%, and the Fl score was 95. 67%. Through the algorithm recognition of three sets of different shooting environment data sets, the Fl score of the three sets of data sets was always maintained at more than 94%, which had good shooting environment adaptability and laid a foundation for automatic harvesting of broccoli by agricultural robots. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 32
Main heading: Gabor filters
Controlled terms: Agricultural robots? - ?Color? - ?Frequency domain analysis? - ?Image enhancement? - ?Image recognition? - ?Image texture? - ?K-means clustering? - ?Laminating? - ?Pixels? - ?Plants (botany) ? - ?Textures
Uncontrolled terms: Broccoli? - ?Color features? - ?Data set? - ?Features recognition? - ?Gabor filtering? - ?Kernel function? - ?Law filtering? - ?Technology-based? - ?Texture enhancement? - ?Texture feature vector
Classification code: 703.2 Electric Filters? - ?723.2 Data Processing and Image Processing? - ?731.5 Robotics? - ?741.1 Light/Optics? - ?816.1 Processing of Plastics and Other Polymers? - ?821.1 Agricultural Machinery and Equipment? - ?903.1 Information Sources and Analysis? - ?921.3 Mathematical Transformations
Numerical data indexing: Percentage 4.10E+01%, Percentage 6.70E+01%, Percentage 9.40E+01%, Percentage 9.60E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.032
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
19. Estimation of Citrus Canopy Chlorophyll Based on UAV Multispectral Images
Accession number: 20232214170738
Title of translation:
Authors: Luo, Xiaobo (1, 2); Xie, Tianshou (1, 2); Dong, Shengxian (3)
Author affiliation: (1) School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing; 400065, China; (2) Chongqing Engineering Research Center for Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing; 400065, China; (3) Chongqing Xinjintu Information Technology Co., Ltd., Chongqing; 408000, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 198-205
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Chlorophyll is an important physiological and biochemical indicator that reflects the growth level and health status of plants, how to obtain the chlorophyll content of citrus canopy quickly and non-destructively on a large scale which can accurately guide orchard management has become an urgent problem. A multi-rotor UAV DJI M600Pro with a multispectral sensor Sequoia manufactued by Parrot was used, which had four bands, including green, red, red edge and near infrared to acquire multi-band reflectance data, after removing the canopy shading and soil background by using normalized difference canopy shadow index, the vegetation index and texture characteristics were calculated. With the ground-truthed chlorophyll content values collected by handheld chlorophyll meter CCM-300 manufactured by OPTI-SCIENCES as validation, the inversion accuracy of full subset regression, partial least squares regression and deep neural network was compared to select the optimal model. The results showed that the correlation between vegetation index and chlorophyll content was high. Comparing the modeling results using only vegetation index with those using only texture features, the inversion accuracy of full subset regression and partial least squares regression of the model using only texture features was significantly improved and the inversion accuracy of full subset regression and partial least squares regression could be improved by introducing both vegetation index and texture features. The deep neural network which had 46 input units, 4 hidden layers and 1 output unit obtained the highest inversion accuracy with R, MAE, and RMSE of 0. 665, 7. 69 mg/m, and 9. 49 mg/m, respectively, due to its good nonlinear fitting ability, it was selected as the optimal model. The research used UAV multispectral images to obtain citrus canopy chlorophyll content by inversion, which was of practical significance for monitoring citrus growth status. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 35
Main heading: Chlorophyll
Controlled terms: Antennas? - ?Deep neural networks? - ?Infrared devices? - ?Least squares approximations? - ?Multilayer neural networks? - ?Regression analysis? - ?Remote sensing? - ?Textures? - ?Unmanned aerial vehicles (UAV)? - ?Vegetation
Uncontrolled terms: Aerial vehicle? - ?Canopy shadow? - ?Chlorophyll contents? - ?Citrus? - ?Deep neutral network? - ?Inversion accuracy? - ?Multispectral remote sensing? - ?Neutral network? - ?Unmanned aerial vehicle? - ?Vegetation index
Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?652.1 Aircraft, General? - ?804.1 Organic Compounds? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics
Numerical data indexing: Mass 4.90E-05kg, Mass 6.90E-05kg
DOI: 10.6041/j.issn.1000-1298.2023.04.019
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
20. Estimation of Winter Wheat Yield Based on Bivariate Assimilation and Cross-wavelet Transform
Accession number: 20232214170712
Title of translation:
Authors: Zhang, Yue (1, 2); Wang, Pengxin (1, 2); Chen, Chi (1, 2); Liu, Junming (3); Li, Hongmei (4)
Author affiliation: (1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China; (3) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China; (4) Shaanxi Provincial Meteorological Bureau, Xi’an; 710014, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 170-179
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: To further improve the accuracy of winter wheat yield estimation in Guanzhong Plain of Shaanxi Province, the ensemble Kalman filter (EnKF) algorithm was used to assimilate the CERES-Wheat model simulated soil moisture at the depth of 0 ~ 20 cm and leaf area index (LAI) with remote sensing observations of the vegetation temperature condition index (VTCI) and LAI, respectively. At the same time, the resonance periods between assimilated VTCI and LAI at each growth stage and yield were analysed by using the cross-wavelet transform, respectively, and the weights of assimilated VTCI and LAI at each stage were obtained by calculating the wavelet cross-correlation degrees, and then a regional yield estimation model for winter wheat based on weighted VTCI and LAI was constructed. The results showed that at the sample point scale, the assimilated VTCI and LAI can combine the effects of model simulations and remote sensing observations, and the trends were more consistent with the actual crop growth changes. At the regional scale, there were specific resonance periods between VTCI, LAI and yield for each growth stage after cross-wavelet transform, regardless of assimilation or not, respectively. It was also found that the assimilation promoted the feature extraction for key growth stages. Compared with the estimated yield model constructed without assimilation, the estimated yield model constructed with assimilation had normalized root mean square error of 13. 23%, coefficient of determination of 0. 50, and mean relative error of 10. 58%, with a slight improvement in accuracy, and the distribution of yield estimation results from the assimilated model was closer to the official statistical yields. In summary, the regional yield estimation model combining assimilation and cross-wavelet transform can effectively improve the estimation accuracy and provide a relevant research basis for further precision agricultural management. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 25
Main heading: Remote sensing
Controlled terms: Crops? - ?Mean square error? - ?Soil moisture? - ?Vegetation? - ?Wavelet transforms
Uncontrolled terms: Cross-wavelet transform? - ?Data assimilation? - ?Growth stages? - ?Leaf Area Index? - ?Remote-sensing? - ?Resonance period? - ?Vegetation temperature condition index? - ?Winter wheat? - ?Winter wheat yields? - ?Yield estimation
Classification code: 483.1 Soils and Soil Mechanics? - ?821.4 Agricultural Products? - ?921.3 Mathematical Transformations? - ?922.2 Mathematical Statistics
Numerical data indexing: Percentage 2.30E+01%, Percentage 5.80E+01%, Size 0.00E00m to 2.00E-01m
DOI: 10.6041/j.issn.1000-1298.2023.04.016
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
21. Design and Experiment of Farmland Surface Micro-landform Measuring Device after Rapeseed Planter Seeding
Accession number: 20232214170752
Title of translation:
Authors: Zhang, Qingsong (1, 2); Qi, Tao (1); Liao, Qingxi (1, 2); Wang, Zetian (1); Chen, Jie (1); Zhu, Longtu (1)
Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key Laboratory of Agricultural Equipment in Mid-lower Yangtze River, Ministry of Agriculture and Rural Affairs, Wuhan; 430070, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 73-82 and 119
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problems that the characteristic parameters’ measurement of the micro-landform shape of the working surface is difficult, the measuring efficiency and error by the traditional measurement method are difficult to balance, and the operation convenience of the existing measurement device is not enough after the operation of the rapeseed combined direct seeder, and a self-propelled remote control farmland surface micro-geomorphology measuring device was designed. The device was mainly composed of a moving unit and a micro-geomorphology measurement system. The device can reach the designated measurement area by remote control operation, control the laser radar to scan height and speed by the mobile phone APP, and display the measurement status information in real time to realize the efficient measurement of the shape characteristics of the farmland surface micro-geomorphology. The driving force of the suspension vibration avoidance mechanism and the driving mechanism of the moving unit of the device was designed and analyzed, and the parameters of the cylindrical spiral compression spring and the driving motor of the moving unit were determined. The hardware and software of the control unit of the micro-landform measurement system were designed, and the hardware circuit and software workflow of the control unit were determined. The tilt error and system error of the device were analyzed, and the correction method of eliminating tilt error and system error was determined. The field measurement test of the device was carried out to measure the micro-geomorphologio characteristics of the surface and the furrow type. The results showed that the developed farmland surface micro-geomorphologic measuring device measured the surface micro-geomorphologic shape characteristics after the operation of the rapeseed combined direct seeder and the rape micro-ridge direct seeding machine. The root mean square height, surface correlation length, average furrow width, furrow width stability coefficient, average furrow depth and furrow depth stability coefficient were 4. 01%, 4. 81%, 3. 70%, 1. 34%, 2. 09% and 2. 89%, respectively. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 24
Main heading: Landforms
Controlled terms: Display devices? - ?Errors? - ?Farms? - ?Optical radar? - ?Remote control? - ?Topography? - ?Vibration analysis
Uncontrolled terms: LiDAR? - ?Measurement system? - ?Measurements of? - ?Measuring device? - ?Micro geomorphologies? - ?Micro topography? - ?Rapesed planter? - ?Self-propelled remote control? - ?Shape characteristics? - ?Surface micro-topography
Classification code: 481.1 Geology? - ?716.2 Radar Systems and Equipment? - ?722.2 Computer Peripheral Equipment? - ?731.1 Control Systems? - ?741.3 Optical Devices and Systems? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?951 Materials Science
Numerical data indexing: Percentage 1.00E00%, Percentage 3.40E+01%, Percentage 7.00E+01%, Percentage 8.10E+01%, Percentage 8.90E+01%, Percentage 9.00E+00%
DOI: 10.6041/j.issn.1000-1298.2023.04.007
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
22. Synchronous Heating Fermentation and Micro-ecological Network of Dry Anaerobic Fermentation Equipment
Accession number: 20232314185719
Title of translation:
Authors: Yi, Rui (1); Zhao, Lixin (1, 2); Yao, Zonglu (1, 2); Feng, Jing (3); Liu, Xinxin (4); Yu, Jiadong (1, 2)
Author affiliation: (1) Institute of Agricultural Environment and Sustainable Development, Chinese Academy of Agricultural Sciences, Beijing; 100081, China; (2) Key Laboratory of Hnv-carbon Green Agriculture in North China, Ministry of Agriculture and Rural Affairs, Beijing; 100081, China; (3) Institute of Rural Energy and Environmental Protection, Ministry of Agriculture and Rural Affairs, Beijing; 100125, China; (4) College of Engineering, Heilongjiang Bayi Agricultural University, Daqing; 163319, China
Corresponding author: Yu, Jiadong(yujiadong010@163.com)
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 376-385
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Dry anaerobic fermentation is one of the important technologies to improve the efficiency of agricultural and rural waste treatment and resource recycling. Previously, due to the problems of low methane production efficiency and uneven mass and heat transfer of this technology, the micro-aerobic synchronous pre-heating dry fermentation technology was proposed, supporting equipment was designed, and pilot and pilot tests were carried out, and the methane production efficiency was improved. In order to further improve the practical application quality of amplification equipment, based on the optimization of key components such as sealing, feed inlet and outlet, and spray circulation system of fermentation equipment, the optimal aeration rate and the material transformation characteristics of micro-aerobic pre-heating stage in practical application were further explored, the relationship between microbial ecological network was revealed, and the actual operation effect was evaluated. The results showed that the optimization of key components significantly improved the operational stability of the equipment. The optimal aeration rate was 10L/min and the volume gas production rate reached 1.20m3/(m3·d) in the micro-aerobic synchronous pre heating stage. At the 40th hour, the material temperature of each layer in the aerated group was increased by 45.54%, 32.46% and 52.06% compared with that in the non aerated group. The simultaneous pre-heating promoted the degradation of cellulose and hemicellulose in each layer of the material, improved the acidification efficiency, and increased the concentration of organic acids by 59.83%, 50.69% and 20.85%, respectively. The gas production potential of the material was increased by 34.9%. The relationship between microbial network and changes in fermentation environmental factors was investigated. It was found that the abundance of SBR 1031, Synergistales and Gaiellales, which had synergistic effects in micro aerobic pre heating stage, were increased by 57.67%, 15.88% and 68.59%, respectively. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 36
Main heading: Fermentation
Controlled terms: Agriculture? - ?Cellulose? - ?Methane? - ?Production efficiency? - ?Rural areas? - ?Waste treatment
Uncontrolled terms: ’Dry’ [? - ?Agricultural and rural waste? - ?Anaerobic fermentation? - ?Dry anerobic fermentation? - ?Ecological networks? - ?Fermentation equipment? - ?Heating stage? - ?Micro aerobics? - ?Microbiome? - ?Pre-heating
Classification code: 452.4 Industrial Wastes Treatment and Disposal? - ?804.1 Organic Compounds? - ?811.3 Cellulose, Lignin and Derivatives? - ?815.1.1 Organic Polymers? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?913 Production Planning and Control; Manufacturing? - ?913.4 Manufacturing
Numerical data indexing: Percentage 1.588E+01%, Percentage 2.085E+01%, Percentage 3.246E+01%, Percentage 3.49E+01%, Percentage 4.554E+01%, Percentage 5.069E+01%, Percentage 5.206E+01%, Percentage 5.767E+01%, Percentage 5.983E+01%, Percentage 6.859E+01%, Volume 1.00E-02m3
DOI: 10.6041/j.issn.1000-1298.2023.04.039
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
23. Design and Experiment of Cow Calving Prediction Equipment Based on Tail Raising Characteristics
Accession number: 20232214170756
Title of translation:
Authors: Zhao, Jizheng (1, 2); Lu (1, 2); Shi, Fulei (1, 2); Dong, Zhengqi (1, 2); Song, Huaibo (1, 2)
Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Shaanxi, Yangling; 712100, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 338-346 and 385
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to solve the problem of lack of automatic monitoring and predicting equipment in the process of cow production, a cow calving predicting equipment based on the tail raising characteristics was designed. The equipment included a data acquisition node for recording the tail acceleration of cows to be delivered, a wireless networking for data upload and cloud data storage platform, and a calving prediction algorithm based on machine learning model was developed to realize the automatic prediction of cow calving. The tail data acquisition node used STM32L151CBT6A MCU to control ICM42605 sensor to achieve acceleration data acquisition. After finishing data sorting and local storage, the data was uploaded to the gateway through LoRa network. The gateway transmitted data to Tencent Cloud IoT development platform through WiFi network according to MQTT protocol, and synchronously stored the data in Tencent Cloud database. In the algorithm development experiment, based on the data of 25 cows before calving, a production prediction model was developed based on MK trend test and multi SVM of ensemble learning. After the algorithm performance verification, the model was deployed to the Tencent cloud server. The verification test results showed that the acceleration signal measured by the oxtail node had a good correlation with the output signal set by the vibration sensor calibrator (r = 0. 938, P ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 26
Main heading: Forecasting
Controlled terms: Data acquisition? - ?Digital storage? - ?Gateways (computer networks)? - ?Internet of things? - ?Learning algorithms? - ?Machine learning? - ?Wi-Fi
Uncontrolled terms: Animal husbandry? - ?Automatic monitoring? - ?Calfing prediction? - ?Cloud data? - ?Data acquisition nodes? - ?Data storage? - ?Machine-learning? - ?Smart animal husbandry? - ?Tail raising characteristic? - ?Wireless networking
Classification code: 722.1 Data Storage, Equipment and Techniques? - ?722.3 Data Communication, Equipment and Techniques? - ?723 Computer Software, Data Handling and Applications? - ?723.2 Data Processing and Image Processing? - ?723.4 Artificial Intelligence? - ?723.4.2 Machine Learning? - ?902.2 Codes and Standards
Numerical data indexing: Percentage 3.00E+00%, Percentage 8.20E+01%, Time 4.32E+04s
DOI: 10.6041/j.issn.1000-1298.2023.04.035
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
24. Self-correcting Method for Application Rate Control Parameters of Wheat Seed Drill Machine
Accession number: 20232214170715
Title of translation:
Authors: Ding, Yongqian (1, 2); Chen, Chong (3); Yu, Hongfeng (3); Zhang, Hongda (3); Dou, Xianglin (3); Liu, Zhuo (3)
Author affiliation: (1) College of Artijitial Intelligence, Nanjing Agricultural University, Nanjing; 210031, China; (2) Collaborative Innovation Center for Modern Crop Production Co-sponsored by Province and Ministry, Nanjing; 210095, China; (3) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 31-37
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: An application rate detection method was proposed based on a special dynamic weighing system where the nitrogen springs through pressure sensors provided the total supporting force and gave rise to the pulling force change of the S-type weighing sensors with the weight change of the material (wheat seed) inside the box. The unique measurement characteristics of the detection system was that the linear combination of the weighted sum of the two types of sensors and the actual application rate equation can filter the original signal of the sensors. The application rate detection method was found based on the measurement characteristics and applied to the application rate control of a seed drill machine with fluted rollers, with the control parameters self-corrected, which made the seed drill machine with fluted rollers realized the substantial closed-loop control of the application rate and ensured continuously high control accuracy. Using the seed drill machine with 6 of 24 fluted rollers were blocked, two types of tests for controlling the application rate, with and without the application of self-correcting control parameters, were carried out. During all the tests, the maximum, average and standard deviation of the absolute relative error between the measured value and the actual value were 4. 52%, 2. 68% and 1. 14%, respectively. While the corresponding statistic data between the actual value and the target value were 18. 38%, 17. 06% and 1. 21%, respectively without control parameters being self-corrected. And the corresponding data were improved to 3. 70%, 2. 61% and 0. 67% after introducing the control parameter self-correcting. The test results showed that the application rate measurement method can effectively measure the application rate of the seed drill machine and can be applied to self-correcting control parameters and holding high control accuracy. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 10
Main heading: Parameter estimation
Controlled terms: Drills? - ?Infill drilling? - ?Rollers (machine components)? - ?Signal processing
Uncontrolled terms: Application rate detecting? - ?Application rates? - ?Control parameters? - ?Rate controls? - ?Rate detection? - ?Seed drills? - ?Self-correcting? - ?Weighted signal? - ?Wheat seed drill machine? - ?Wheat seeds
Classification code: 511.1 Oil Field Production Operations? - ?601.2 Machine Components? - ?603.2 Machine Tool Accessories? - ?716.1 Information Theory and Signal Processing
Numerical data indexing: Percentage 1.40E+01%, Percentage 2.10E+01%, Percentage 3.80E+01%, Percentage 5.20E+01%, Percentage 6.00E+00%, Percentage 6.10E+01%, Percentage 6.70E+01%, Percentage 6.80E+01%, Percentage 7.00E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.003
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
25. Fruit Tree Location Method Based on 3D LiDAR and Optimized DBSCAN Algorithm
Accession number: 20232214170733
Title of translation: DBSCAN
Authors: Liu, Chao (1); Chen, Jinming (1); Liu, Hui (1); Xiao, Xinhua (1); Shen, Yue (1)
Author affiliation: (1) School of Electrical and Information Engineering, Jiangsu University, Zhenjiang; 212013, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 214-221 and 240
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to improve the autonomy and safety of orchard spray robot walking among orchard rows, a fruit tree location method based on 3D LiDAR and optimized DBSCAN algorithm was proposed. Firstly, the three-dimensional LiDAR was used to obtain the environmental information of the orchard in real time, and the original data was preprocessed by region of interest extraction, ground point cloud segmentation and voxel filtering. Then, the DBSCAN algorithm was optimized, the KD tree index was constructed to order the real-time point cloud data, and the KD tree nearest neighbor search was used to replace the traversal search method of the traditional DBSCAN algorithm. Finally, the clustering results of fruit trees were marked with reference position. Taking the midpoint of the *-axis of the plane between the rows where the clustering results faced as reference point, the point to the xoy plane of the chassis height of the orchard spray robot was projected, and the coordinates of the positioning reference point of the fruit trees were obtained, so as to calculate the relative position between the orchard spray robot and the fruit trees. The experimental results showed that compared with the traditional DBSCAN algorithm, the accuracy and real-time performance of the optimized DBSCAN algorithm were significantly improved. Based on the optimized DBSCAN algorithm, the average horizontal positioning error of fruit trees was 2. 6%, and the average vertical positioning error of fruit trees was 1. 6%. When the orchard spray robot traveled between rows, this method can meet the accuracy and real-time requirements of fruit tree positioning, and it can provide effective reference for precision agriculture equipment in autonomous navigation and operation in forest orchard environment. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 30
Main heading: Orchards
Controlled terms: Agricultural robots? - ?Clustering algorithms? - ?Forestry? - ?Fruits? - ?Image segmentation? - ?Information filtering? - ?Navigation systems? - ?Nearest neighbor search? - ?Optical radar
Uncontrolled terms: Clustering results? - ?DBSCAN algorithm? - ?Fruit tree positioning? - ?Fruit trees? - ?LiDAR? - ?Location method? - ?Orchard spray robot? - ?Real- time? - ?Reference points? - ?Tree location
Classification code: 716.2 Radar Systems and Equipment? - ?731.5 Robotics? - ?741.3 Optical Devices and Systems? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.1 Agricultural Machinery and Equipment? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?903.1 Information Sources and Analysis? - ?921.5 Optimization Techniques
Numerical data indexing: Percentage 6.00E+00%
DOI: 10.6041/j.issn.1000-1298.2023.04.021
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
26. Design and Test of Garlic Clove Orientation Device Based on Capacitive Detection Technology
Accession number: 20232214170714
Title of translation:
Authors: Hou, Jialin (1, 2); Fang, Lizhi (1, 2); Li, Yuhua (1, 2); Wu, Yanqiang (1, 2); Zhou, Kai (1, 2)
Author affiliation: (1) College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian; 271018, China; (2) Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence, Taian; 271018, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 63-72
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to solve the problem of low upright rate of traditional machinery, a method for determining the garlic clove orientation based on capacitive detection technology was proposed. There were differences in morphological structure between the bud and the root; under the same width, the volume of the bud was smaller than that of the root. The feature was exploited and converted to an average dielectric constant difference to determine the orientation of the garlic clove by detecting the capacitance. The feasibility of the method was verified based on the electric field analysis of ANSYS in the research process. In addition, the corresponding bud adjustment device was designed. Orthogonal tests took the short axis radius, long axis radius, and bottom angle of the device as the test factors and the upright rate as the test indicators, and the test data were analyzed by Design-Expert 11. 1. 2. 0 software to obtain the order of influence of each factor on the index value. The results showed that when the bottom angle, short axis radius, and long axis radius were 80°, 22. 99 mm, and 27. 79 mm, respectively, the device performance was optimal and the theoretical upright rate was 96. 6%. The test verification of the optimized factors was basically consistent with the optimized results. With the pole plate parameter as the test factor and the signal-to-noise ratio as the test indicators, the test data showed that the device performance was optimal when the pole plate parameter was 45 mm X 8 mm x 0. 10 mm. The prototype test was carried out with Jinxiang and Cangshan garlic cloves, and the qualified rate was 95. 0%, which met the requirements of garlic sown. The research result can provide support for the application of capacitance detection technology in precision sowing equipment. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 23
Main heading: Capacitance
Controlled terms: Electric fields? - ?Plates (structural components)? - ?Poles? - ?Signal to noise ratio? - ?Software testing
Uncontrolled terms: ANSYS? - ?Capacitance detections? - ?Capacitive detection? - ?Clove orientation device? - ?Detection technology? - ?Device performance? - ?EDEM? - ?Garlic seede? - ?Long axis? - ?Test data
Classification code: 408.2 Structural Members and Shapes? - ?701.1 Electricity: Basic Concepts and Phenomena? - ?716.1 Information Theory and Signal Processing? - ?723.5 Computer Applications
Numerical data indexing: Percentage 0.00E00%, Percentage 6.00E+00%, Size 1.00E-02m, Size 4.50E-02m, Size 7.90E-02m, Size 8.00E-03m, Size 9.90E-02m
DOI: 10.6041/j.issn.1000-1298.2023.04.006
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
27. Identification of Apple Leaf Diseases Based on Improved ResNetl8
Accession number: 20232214170708
Title of translation: ResNet18
Authors: Jiang, Honghua (1); Yang, Xianghai (1); Ding, Ruirou (1); Wang, Dongwei (2); Mao, Wenhua (3); Qiao, Yongliang (4)
Author affiliation: (1) College of Information Science and Engineering, Shandong Agricultural University, Taian; 271018, China; (2) College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao; 266109, China; (3) Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing; 100083, China; (4) Faculty of Engineering, The University of Sydney, Sydney; 2006, Australia
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 295-303
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Aiming at the problem that the traditional apple leaf disease classification method has poor accuracy and low efficiency, which affects prevention and cure effect, an improved ResNetl8 algorithm was proposed. By adding the branch of channel and spatial attention mechanism to the original ResNetl8, the feature extraction ability of the network for leaf disease regions was strengthened to improve the disease recognition accuracy and real-time performance. In addition, to better guide the network to learn the features of sporadically distributed disease spots, the feature map random cropping branch was introduced, which not only achieved the expansion of the limited sample space, but also further optimized the network structure and improved the training speed. The experiment was conducted with five common types of apple foliar diseases (black star, black rot, cedar rust, gray spot, and powdery mildew) as the main research objects and compared with the mainstream classification algorithm models for analysis. The experimental results showed that the disease classification accuracy of the proposed ResNetl8-CBAM-RC1 model can reach 98. 25%, which was higher than that of ResNetl8 (93. 19%) and VGG16 (96. 13%), and can effectively extract leaf disease features, enhance the recognition of multiple types of diseases, and improve the real-time recognition capability and accuracy. In addition, the model size was only 37. 44 MB and the inference time of a single image was 9. 11 ms, which can meet the real-time requirements of orchard disease recognition on embedded devices and provide information support for disease prevention and control in digital orchards. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 23
Main heading: Orchards
Controlled terms: Deep neural networks? - ?Digital devices? - ?Disease control? - ?Fruits
Uncontrolled terms: Apple leaf disease? - ?Attention mechanisms? - ?Classification methods? - ?Deep learning? - ?Disease classification? - ?Leaf disease? - ?Prevention and cure? - ?Random clipping? - ?Resnetl8? - ?Spatial attention
Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products
Numerical data indexing: Percentage 1.30E+01%, Percentage 1.90E+01%, Percentage 2.50E+01%, Time 1.10E-02s
DOI: 10.6041/j.issn.1000-1298.2023.04.030
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
28. Design and Experiment of Spiral Blades Auxiliary Roller of Organic Fertilizer Side Throwing Device
Accession number: 20232214170735
Title of translation:
Authors: Liu, Hongxin (1, 2); Zhao, Yijian (1); Xie, Yongtao (1); Zhang, Yiming (1); Shang, Jiajie (1)
Author affiliation: (1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) College of Mechanical and Electrical Engineering, Suqian College, Suqian; 223800, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 107-119
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to solve the problems of near fertilizer accumulation and local ridging in the existing side throw device for organic fertilizer with inclined opposite discs, combined with the function and working principle of each component of side throw device, an auxiliary roller with symmetrical spiral blade was innovated on the basis of theoretical analysis, the key structural parameters and operating parameters were optimized, and the spatial position relationship between the side throw device and the discs of the main throwing component was clarified. Single factor and response surface experiments were carried out by EDEM software, the effects of roller speed, helix angle and blade number on uniformity coefficient of variation and fertilizer proportion within 1 m were studied, the optimal parameter combination was obtained after optimization. The simulation results showed that the optimal parameter combination of auxiliary roller was roller speed of 2 238 r/min, helix angle of 42. 70°, number of blades of 4, coefficient of variation of uniformity of 24. 45%, fertilizer proportion within 1 m of 24. 96%, and the simulation results with this parameter combination were better than those with the optimal parameters of the original roller. Test results of new auxiliary roller after innovative design were 25. 46% and 25. 65%, which were greatly improved compared with 46. 77% and 65. 94% of the original auxiliary roller, when combined with the main discs throwing uniformity was good, no accumulation and ridging phenomenon occurred. The results showed that symmetric spiral blades can effectively correct the movement direction of fertilizer particles, so that the non-controlled fertilizers concentrated in the main discs were dispersed on both sides. Combined with the main disc and other auxiliary components, the throwing performance was greatly improved. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 21
Main heading: Fertilizers
Controlled terms: Rollers (machine components)
Uncontrolled terms: Auxiliary roller? - ?Coefficients of variations? - ?Helix angles? - ?Optimal parameter combinations? - ?Organic fertilizer side throwing? - ?Organic fertilizers? - ?Roller speed? - ?Spiral blades? - ?Structural parameter? - ?Symmetrical spiral blade
Classification code: 601.2 Machine Components? - ?804 Chemical Products Generally? - ?821.2 Agricultural Chemicals
Numerical data indexing: Angular velocity 3.9746E+00rad/s, Percentage 4.50E+01%, Percentage 4.60E+01%, Percentage 6.50E+01%, Percentage 7.70E+01%, Percentage 9.40E+01%, Percentage 9.60E+01%, Size 1.00E00m
DOI: 10.6041/j.issn.1000-1298.2023.04.010
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
29. Kinematics Performance Analysis of Bifurcation Parallel Mechanism
Accession number: 20232314185770
Title of translation:
Authors: Li, Yongquan (1); Cai, Jun (1); Li, Yukun (1); Zheng, Tianyu (2); Wang, Jingxu (1); Qiao, Xiaofei (1)
Author affiliation: (1) College of Mechanical Engineering, Yanshan University, Qinhuangdao; 066044, China; (2) College of Mechanical Engineering, Hebei University of Technology, Tianjin; 300130, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 447-458
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: At present, many parallel mechanisms with motion bifurcation characteristics use single-loop mechanisms. The mechanism is complex and the configuration is monotonous. There are few known parallel mechanisms with 3T1R and 2R2T multi-modes.A branch chain with motion bifurcation characteristics was introduced into the parallel mechanism, and a motion bifurcation parallel mechanism with 3T1R + 2R2T two modes was obtainedand its degree of freedom and motion bifurcation characteristics were analyzed by using the screw theory.The results showed that when the mechanism was at the motion bifurcation point, the moving platform had five degrees of freedom. By driving different driving pairs, the mechanism can evolve into a configuration with different motion bifurcation characteristics, including three movements and one rotation, two movements and two rotations. In order to realize the reasonable switching between the two configurations, a rigid drive method was used to select a reasonable drive pair. The forward and inverse kinematics solutions of the parallel mechanism in different configurations were analyzed. It was concluded that both the forward and inverse kinematics equations can be solved analytically. The mechanism had good motion decoupling. The correctness of the forward and inverse kinematics solution was verified by ADAMS. The singularity of the mechanism was analyzed by Jacobi matrix. The results showed that there was no singularity in the two motion modes in a reasonable working range. The workspace of the organization was drawn. Based on the motion/force transfer performance method, the performance index of the mechanism was analyzed, and the performance distribution map in the workspace was drawn. The results showed that the two configurations had good motion/force transfer characteristics, and the high quality workspace was large. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 18
Main heading: Inverse problems
Controlled terms: Bifurcation (mathematics)? - ?Degrees of freedom (mechanics)? - ?Inverse kinematics? - ?Jacobian matrices? - ?Screws? - ?Transmissions
Uncontrolled terms: Characteristic of movement decoupling? - ?Decouplings? - ?Force transfer? - ?Forward and inverse kinematics? - ?Forward kinematics solutions? - ?Inverse kinematic solutions? - ?Movement bifurcation? - ?Parallel mechanisms? - ?Screw theory? - ?Transmission performance
Classification code: 602.2 Mechanical Transmissions? - ?605 Small Tools and Hardware? - ?921.1 Algebra? - ?931.1 Mechanics
DOI: 10.6041/j.issn.1000-1298.2023.04.047
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
30. Weed Detection Algorithm Based on Dynamic Pruning Neural Network
Accession number: 20232214170709
Title of translation:
Authors: Kang, Jie (1); Liu, Gang (1); Wang, Qing (1); Xia, Yu (1); Guo, Guofa (1); Liu, Wenbo (1)
Author affiliation: (1) School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi’an; 710021, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 268-275
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: To address the problem that the convolutional neural network models are difficult to be applied in practice due to their vast number of parameters and computation, a model compression method based on attention mechanism and dynamic sparse constraint was proposed. Firstly, the importance of each channel in the network was evaluated with the help of the squeeze and excitation networks (SENet) module, and sparse regularization was applied; then an adaptive penalty weight design method for network sparsity was proposed. According to the learning effect of the model, the weight was dynamically adjusted and added to the final training target to realize the dynamic compression of the model. Finally, the proposed model compression method was verified by experiments on the classic multi-classification dataset CIFAR-10. It was proved that the proposed model compression method based on attention mechanism and dynamic sparse constraint can reduce the network redundancy, resulting in a 43. 97% reduction in the amount of network model parameters and an 82. 94% reduction in the amount of computation, while the classification accuracy was only 0. 04 percentage points lower than that of the original VGG16 model. Then the proposed model compression method was applied to the weed detection task, and the experiment was carried out on the sugar beet and weed datasets. The experimental results showed that compared with the unpruned model, the pruned model reduced the model parameters by 41. 26%, the calculation amount by 45. 77%, and the average detection accuracy by only 0. 91 percentage points, which proved that this method could also have a good effect on the weed detection task. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Dynamics
Controlled terms: Classification (of information)? - ?Neural network models? - ?Parameter estimation? - ?Sugar beets? - ?Weed control
Uncontrolled terms: % reductions? - ?Attention mechanisms? - ?Compression methods? - ?Detection algorithm? - ?Detection tasks? - ?Dynamic sparse constraint? - ?Model compression? - ?ON dynamics? - ?Percentage points? - ?Weed detection
Classification code: 716.1 Information Theory and Signal Processing? - ?723.4 Artificial Intelligence? - ?821.4 Agricultural Products? - ?903.1 Information Sources and Analysis
Numerical data indexing: Percentage 2.60E+01%, Percentage 7.70E+01%, Percentage 9.40E+01%, Percentage 9.70E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.027
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
31. Calibration Method of Leaf Wetness Sensor in Irrigated Citrus Orchard
Accession number: 20232314185722
Title of translation:
Authors: Hu, Jie (1); Wang, Mengcheng (1); Lan, Yubin (1); Zhang, Yali (2); Lu, Xiaoyang (2)
Author affiliation: (1) College of Electronic Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) College of Engineering South China Agricultural University, Guangzhou; 510642, China
Corresponding author: Zhang, Yali(ylzhang@scau.edu.cn)
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 356-365
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Leaf wetness duration is one of the important input variables of plant disease model, which is related to the infection of many leaf pathogens and affects the infection and development rate of pathogens. The leaf wetness sensor can realize real-time and automated monitoring, and since the leaf wetness duration is affected by the interaction between the environment and plants, it needs to be calibrated in citrus orchards under irrigation. Citrus in growing season was used as experimental material to study the calibration method.The angle of the leaf wetness sensor was 30°, and two methods were used to determine the dry-wet threshold of the sensor: drip water to the sensor by pipetting gun and sprinkle irrigation facility to the sensor.The monitoring effects of sensors in different positions of the citrus canopy were compared, and the effects of rain and no rain conditions on the monitoring effects of the sensors were studied. Finally, the neural network model was used to verify the rationality of the threshold. The results showed that the leaf wetness sensor obtained a dry-wet threshold of 270mV in the irrigation environment. At this time, the monitoring effect of the sensor was the best, and the error was within 2h. By comparing with the prediction results of the neural network model, it was confirmed that the monitoring effect of the sensor was good under this threshold.The sensor located at the bottom of the citrus canopy had the highest monitoring accuracy, which can reach 0.95.The monitoring effect of the sensor was better in no rain condition than that in rainy condition.Overall, the calibration method of the leaf wetness sensor can be used to monitor the leaf wetness duration of irrigated citrus orchards, which met the requirements of the citrus disease early warning system. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 39
Main heading: Calibration
Controlled terms: Irrigation? - ?Orchards? - ?Rain
Uncontrolled terms: ’Dry’ [? - ?Calibration method? - ?Citrus? - ?Citrus canopies? - ?Citrus orchards? - ?Condition? - ?Leaf wetness? - ?Leaf wetness durations? - ?Leaf wetness sensor? - ?Monitoring effect
Classification code: 443.3 Precipitation? - ?821.3 Agricultural Methods
Numerical data indexing: Time 7.20E+03s, Voltage 2.70E-01V
DOI: 10.6041/j.issn.1000-1298.2023.04.037
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
32. Simulation and Experiment of Seed Taking Performance of Swing-clamp Type Maize Precision Seed-metering Device
Accession number: 20232214170750
Title of translation:
Authors: Zhang, Xuejun (1, 2); Cheng, Jinpeng (1); Shi, Zenglu (1, 2); Wang, Meijing (1); Fu, Hao (1); Wu, Haifeng (1)
Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Xinjiang Key Laboratory of Intelligent Agricultural Equipment, Urumqi; 830052, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 38-50
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In response to the problem of large differences in size of three axes of maize seeds, which are prone to omission and re-taking during seed picking, a swing-clamp type maize precision seed-metering device was designed, its structure and working principle were introduced and analyzed, and the key components were designed. The key factors affecting the seed extraction performance of the seed-metering device were obtained by establishing mechanical and kinematic models for analysis. The simulation model was established by EDEM software to further analyze the influence law of population height and seed-metering device’s rotational speed on population flow speed, and the seed-mertering device’s fetching performance curve was obtained. The seed picking block opening and closing angle, seed feeding cylinder installation height and seed-metering device’s rotation speed were used as experimental factors, and the single seed picking rate, leakage rate and multiple picking rate were used as evaluation indexes for the secondary orthogonal rotation combination simulation test, the results showed that the optimal combination of parameters was 43. 87° of seed picking block opening and closing angle, 37. 84 mm of seed feeding cylinder installation height and 0. 41 r/s of seed-metering device’s rotational speed. Under the optimal combination of parameters, the seed row performance bench validation test was conducted, and the seed row qualification index of the seed rower was 94. 11%, the missed seed index was 2. 52% and the reseeding index was 3. 37%, meeting the industry standard and agronomic requirements. The research result provided a theoretical reference for the design optimization of different working area components of the mechanical corn precision seed-metering device. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 29
Main heading: Cylinders (shapes)
Controlled terms: Computer software? - ?Kinematics
Uncontrolled terms: Closing angle? - ?EDEM? - ?Installation heights? - ?Maize? - ?Opening angle? - ?Performance? - ?Precision seed-metering devices? - ?Rotational speed? - ?Seed-metering device? - ?Swing-clamp type
Classification code: 723 Computer Software, Data Handling and Applications? - ?931.1 Mechanics
Numerical data indexing: Percentage 1.10E+01%, Percentage 3.70E+01%, Percentage 5.20E+01%, Size 8.40E-02m
DOI: 10.6041/j.issn.1000-1298.2023.04.004
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
33. Super-resolution Reconstruction of Unmanned Aerial Vehicle Tea Images Based on Improved RDN Network
Accession number: 20232214170743
Title of translation: RDN
Authors: Bao, Wenxia (1); Wu, Yu’an (1); Hu, Gensheng (1); Yang, Xianjun (2); Wang, Zhenyu (1)
Author affiliation: (1) National Engineering Research Center for Agro-ecological Big Data Analysis and Application, Anhui University, Hefei; 230601, China; (2) Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei; 230031, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 241-249
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: It is a relatively economical, flexible and time-effective method to build a visible light sensor for monitoring of tea growth and diseases, but the resolution of the image will be affected by the flying height of the UAV. Therefore, an improved residual dense network (RDN) for super-resolution reconstruction of UAV tea images was proposed. Specifically, in view of the complex texture of UAV tea images, taking RDN as the baseline network, residual group (RG) was introduced into its structure, combining multiple residual channel attention modules were combined together to treat different channels differently by introducing an attention mechanism, and paying attention to the high-frequency detail information of UAV tea images, thereby improving the representation ability of the network; at the same time, a convolutional long jump structure was designed, using the long-range skip connection with convolution, to dynamically adjust the weight of the feature after passing through the residual dense block (RDB), and making better use of the hierarchical feature information of the UAV tea image, thereby improving the super-resolution of the quality of reconstructed image. The experimental results showed that the improved RDN network performed better than other algorithms on the test set of UAV tea images, and the super-resolution reconstructed images had higher peak signal-to-noise ratio and structural similarity. In the case of quadruple super resolution, it can reach 36. 03 dB and 0. 913 2, respectively, which can provide support for the follow-up research of tea intelligent monitoring. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Image enhancement
Controlled terms: Convolution? - ?Image quality? - ?Image reconstruction? - ?Optical resolving power? - ?Signal to noise ratio? - ?Textures? - ?Unmanned aerial vehicles (UAV)
Uncontrolled terms: Aerial vehicle? - ?Convolutional long jump structure? - ?Dense network? - ?Image-based? - ?Images reconstruction? - ?Light sensor? - ?Residual group? - ?Super-resolution reconstruction? - ?Superresolution? - ?Visible light
Classification code: 652.1 Aircraft, General? - ?716.1 Information Theory and Signal Processing? - ?741.1 Light/Optics
Numerical data indexing: Decibel 3.00E+00dB
DOI: 10.6041/j.issn.1000-1298.2023.04.024
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
34. Path Tracking Algorithm of Agricultural Vehicle Based on Two Stages Pure Tracking Model
Accession number: 20232314185717
Title of translation:
Authors: Xiao, Shide (1); Jiang, Haifeng (1); Du, Jinlan (1); Wang, Yihan (1); Meng, Xiangyin (1); Xiong, Ying (1)
Author affiliation: (1) School of Mechanical Engineering, Southwest Jiaotong University, Chengdu; 610031, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 439-446 and 458
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to realize the automatic navigation of agricultural vehicles, ultra wide band (UWB) wireless positioning technology was used to obtain the current position of the vehicle in real time, and the path tracking research was carried out. In view of the inconsistency between the theoretical steering motion model and the actual steering motion model caused by factors such as the vehicle’s own processing, assembly errors and tire sideslip, in order to improve the control accuracy, the vehicle’s steering motion model was identified based on the least squares method, and the turning motion models at different linear speeds were obtained. At the same time, in order to solve the problem that some of the control variables calculated by the conventional pure tracking algorithm cannot make the vehicle steering system respond, resulting in the decline of the path tracking accuracy, a two-stage pure tracking algorithm considering lateral deviation and lateral deflection angle was proposed. And the strategy of hysteresis switching of setting transition lag was proposed for how to switch between the two stages. The “S” type path tracking test in the simulation environment showed that when the driving speed was 0.6m/s, the average lateral deviation of the pure tracking algorithm with a fixed look-ahead distance was 0.5238m, and the two-stage pure tracking algorithm was 0.3616m, and its tracking accuracy was improved by 30.9%, which had better path tracking performance than that of the pure tracking algorithm with fixed look-ahead distance. The hysteresis switching stratege was adopted to reduce the two stages mutation rate from 2.18% to 1.16%, and the suppression effect was improved by 46.8%. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 32
Main heading: Automobile steering equipment
Controlled terms: Agriculture? - ?Hysteresis? - ?Least squares approximations? - ?Steering? - ?Tracking (position)? - ?Ultra-wideband (UWB)
Uncontrolled terms: Agricultural vehicles? - ?Hysteresis switching? - ?Lateral deviation? - ?Motion models? - ?Path tracking? - ?Pure-pursuit algorithms? - ?Steering control? - ?Steering motion? - ?Tracking accuracy? - ?Tracking algorithm
Classification code: 662.4 Automobile and Smaller Vehicle Components? - ?716.3 Radio Systems and Equipment? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?921.6 Numerical Methods? - ?961 Systems Science
Numerical data indexing: Percentage 2.18E+00% to 1.16E+00%, Percentage 3.09E+01%, Percentage 4.68E+01%, Size 3.616E-01m, Size 5.238E-01m, Velocity 6.00E-01m/s
DOI: 10.6041/j.issn.1000-1298.2023.04.046
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
35. Screening of Drought-tolerant Ramie Based on UAV Multispectral Imagery
Accession number: 20232214170722
Title of translation:
Authors: Fu, Hongyu (1); Wang, Wei (1); Lu, Jianning (1); Yue, Yunkai (1); Cui, Guoxian (1); She, Wei (1)
Author affiliation: (1) College of Agriculture, Hunan Agricultural University, Changsha; 410128, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 206-213
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: High temperature and drought are the main stress sources affecting crop growth and final productivity. At present, UAV remote sensing technology has made great progress in the hierarchical monitoring of crop lodging and pests and diseases, but there are few reports on the use of UAV remote sensing for crop drought resistance grade monitoring. Therefore, taking ramie germplasm resources as the research object, quantitative criteria for ramie drought resistance was proposed, and a method to identify the drought resistance of ramie germplasm resources was providedby multi-spectral remote sensing of UAV. Firstly, totally 36 ramie germplasm resources were graded for drought resistance by experts. Then, combined with the vegetation index obtained by UAV multispectral remote sensing, and three machine learning methods, random forest (RF), support vector machine (SVM) and decision tree (DT) were used to construct ramie drought resistance identification models, and the results were evaluated by testing the phenotypic response of ramie under high temperature and drought stress. Finally, high-quality ramie germplasm resources under high temperature and drought stress were screened based on the remote sensing phenotypes obtained by UAV. The results showed that the accuracy of the ramie drought resistance identification model constructed by SVM reached 0. 74, and the Fl-score of different drought resistance classes was ranged from 0. 69 to 0. 79, indicating that the method could be used to evaluate the drought resistance of ramie germplasm resources. Three phenotypic characters of ramie (SPAD value, leaf area index and plant height) obtained from UAV remote sensing data were strongly correlated with the measured values. On this basis, three high-quality ramie germplasm resources PJ-CD, WS-XM and Xiangzhu 7 were selected from high temperature and drought stress. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 23
Main heading: Support vector machines
Controlled terms: Crops? - ?Decision trees? - ?Drought? - ?Learning systems? - ?Remote sensing? - ?Unmanned aerial vehicles (UAV)
Uncontrolled terms: Drought resistance? - ?Drought stress? - ?Germplasms? - ?High temperature stress? - ?Identification modeling? - ?Ramie? - ?Remote-sensing? - ?Resistance level? - ?Support vectors machine? - ?UAV remote sensing
Classification code: 443.3 Precipitation? - ?444 Water Resources? - ?652.1 Aircraft, General? - ?723 Computer Software, Data Handling and Applications? - ?821.4 Agricultural Products? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?961 Systems Science
DOI: 10.6041/j.issn.1000-1298.2023.04.020
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
36. Path Tracking Algorithm for Mower Based on Virtual Radar and Two-level Neural Network
Accession number: 20232214170723
Title of translation:
Authors: Zhao, Yongchun (1, 2); Zhang, Qing (1, 2); You, Yong (1, 2); Huang, Shaojiong (1); Liu, Wen (1); Wang, Decheng (1, 2)
Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) Grassland Machinery and Equipment Research Center, China Agricultural University, Beijing; 100083, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 222-232 and 267
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to improve the path tracking accuracy of small dual-motor driven crawler mower in orchard under severe road conditions, a path tracking control algorithm based on virtual radar path perception and two-level deep neural network was proposed. Firstly, a two-level serial artificial deep neural network was built, and the first-level deep neural network calculated the relative position relationship between the crawler mower and the target path through the virtual radar path sensing algorithm. The control speed of driving motors on both sides was calculated according to tracking deviation, heading angle, influence factor of lateral deviation, factor of converted track slip rate and relative position relationship between crawler mower and target path, and path tracking control was realized by second-level deep neural network. The U-shaped path tracking tests of crawler mower were carried out on orchard road surface after irrigation. When the vehicle speeds were 0. 4 m/s and 0. 8 m/s, the maximum lateral deviations of path tracking algorithm were 0. 064 m and 0. 072 m, and the average lateral deviations were 0. 026 m and 0. 033 m, respectively. Compared with the traditional pure tracking control algorithm, the maximum lateral deviations at the test speed of 0. 4 m/s and 0. 8 m/s were reduced by 31. 18% and 20. 88%, respectively, and the average lateral deviations were reduced by 35. 00% and 29. 79%, respectively. The path tracking control algorithm combining virtual radar and two-level deep neural network can effectively improve the track tracking accuracy of crawler mower on bad road surface. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 30
Main heading: Deep neural networks
Controlled terms: Lawn mowers? - ?Navigation? - ?Orchards? - ?Roads and streets? - ?Tracking radar
Uncontrolled terms: Crawler mower? - ?Lateral deviation? - ?Path tracking? - ?Path tracking control? - ?Relative positions? - ?Road surfaces? - ?Tracking accuracy? - ?Tracking algorithm? - ?Tracking control algorithms? - ?Virtual radar
Classification code: 406.2 Roads and Streets? - ?461.4 Ergonomics and Human Factors Engineering? - ?716.2 Radar Systems and Equipment? - ?821.3 Agricultural Methods
Numerical data indexing: Percentage 0.00E00%, Percentage 1.80E+01%, Percentage 7.90E+01%, Percentage 8.80E+01%, Size 2.60E+01m, Size 3.30E+01m, Size 6.40E+01m, Size 7.20E+01m, Velocity 4.00E+00m/s, Velocity 8.00E+00m/s
DOI: 10.6041/j.issn.1000-1298.2023.04.022
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
37. Multispectral Diffraction Identification of Rice Disease Spores and Localization Method of Disease Source
Accession number: 20232214170741
Title of translation:
Authors: Yang, Ning (1); Zhang, Tianwei (1); Zhang, Zhaoyuan (1); Zhang, Xiaodong (2); Mao, Hanping (2); Yuan, Shouqi (3)
Author affiliation: (1) School of Electrical and Information Engineering, Jiangsu University, Zhenjiang; 212013, China; (2) School of Agricultural Engineering, Jiangsu University, Zhenjiang; 212013, China; (3) Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang; 212013, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 250-258
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Rice fungal diseases mainly rely on fungal spores for airborne transmission. However, the morphology of various rice disease spores is similar, and it is difficult to distinguish them by traditional spore trap and microscopic image methods. To be able to accurately identify target disease spores and locate the disease source, a multispectral diffraction identification and disease source localization method for rice disease spores was proposed. A large field-of-view, lens-free multispectral diffraction imaging sensor was designed to address the shortcomings of traditional diffraction methods that cannot identify morphological similarities. By analyzing the disease spore diffraction fingerprinting, the multi-spectral diffraction imaging characteristic pattern of rice blast and rice curd spores was analyzed. By integrating the morphological characteristics and absorption properties of spores, two characteristic parameters of fingerprint separation intensity and relative peak difference were proposed to establish the multispectral diffraction identification model of spores. The spore propagation law was analyzed by simulation and calculation experiments, and the diffusion model in the process of spore propagation was established by coupling environmental information. The spatial distribution of spores was analyzed under the conditions of non-directional wind and directional wind, and an iterative plasmodial localization algorithm of the disease outbreak source was proposed. The experimental results showed that the recognition rate of rice disease spores reached 98. 5%, and the localization error was as low as 4. 9% for undirected wind conditions and 7. 1% for directed wind conditions. This method can provide a reference in locating the source of crop disease outbreaks. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 24
Main heading: Diffraction
Controlled terms: Diffusion? - ?Environmental regulations? - ?Fungi? - ?Iterative methods
Uncontrolled terms: Diffraction imaging? - ?Diffusion model? - ?Disease outbreaks? - ?Iterative plasmacentric localization of disease source? - ?Localisation? - ?Multi-spectral? - ?Multispectral diffraction identification? - ?Rice disease spore? - ?Spore diffusion model? - ?Wind conditions
Classification code: 454.2 Environmental Impact and Protection? - ?921.6 Numerical Methods
Numerical data indexing: Percentage 1.00E00%, Percentage 5.00E+00%, Percentage 9.00E+00%
DOI: 10.6041/j.issn.1000-1298.2023.04.025
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
38. Design and Test of Combined Garlic Flexible Peeling Device
Accession number: 20232214170754
Title of translation:
Authors: Li, Xinping (1); Sun, Chenchen (1); Zhang, Wantong (1); Wang, Shengsheng (1); Gao, Lianxing (2)
Author affiliation: (1) College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang; 471003, China; (2) Institute of Intelligent Agriculture, Jilin Agricultural University, Changchun; 130118, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 132-141
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to solve the problems of low peeling rate and easy damage of garlic kernel, a combined garlic flexible peeling device was designed. The garlic peel was separated by the floating rubbing unit, and the vibration mechanism completed the transportation. The garlic peel was flexible peeled by the combined action of floating rubbing, vibrating brush and air blowing. According to the physical and mechanical characteristics of garlic, the key components such as rubbing mechanism, vibration mechanism, brushing mechanism, air blowing mechanism were designed. Through the dynamic analysis of garlic cloves in the floating rubbing unit and the vibrating screen, the main factors and value range that affected the peeling performance test were determined. Taking the rotational speed of the rubbing cylinder shaft, the comb brush spacing and the crank rotational speed as the test factors, and the peeling rate and the breakage rate as the test indexes, the three-factor three-level response surface test was carried out to obtain the optimal parameter combination of the rubbing cylinder shaft rotational speed, the comb brush spacing and the crank rotational speed, and the test verification was carried out. The test results showed that the optimal parameter combination was the rotation speed of rubbing roller shaft of 70. 73 r/min, vibration frequency of 6. 68 Hz, comb brush clearance of 18. 00 mm. Under the optimal parameter combination, the peeling rate of garlic cloves was 93. 68% and the damage rate was 4. 40%. The relative error between the test verification results and the optimization results was less than 5%, which met the requirements of garlic peeling. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 24
Main heading: Cylinders (shapes)
Controlled terms: Vibrations (mechanical)
Uncontrolled terms: Comb brush? - ?Combined actions? - ?Design and tests? - ?Floating rubbing? - ?Garlic peeled device? - ?Optimal parameter combinations? - ?Rotational speed? - ?Test verification? - ?Vibration? - ?Vibration mechanisms
Classification code: 931.1 Mechanics
Numerical data indexing: Angular velocity 1.2191E+00rad/s, Frequency 6.80E+01Hz, Percentage 4.00E+01%, Percentage 5.00E+00%, Percentage 6.80E+01%, Size 0.00E00m
DOI: 10.6041/j.issn.1000-1298.2023.04.012
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
39. Control of Hydrofoil Cloud Cavitation Flow with Different Jet Parameters
Accession number: 20232214170706
Title of translation:
Authors: Wang, Wei (1, 2); Liu, Mingyu (1); Li, Zhijian (1); Ji, Xiang (1); Wang, Xiaofang (1, 2)
Author affiliation: (1) School oj Energy and Power Engineering, Dalian University of Technology, Dalian; 116024, China; (2) Key Laboratory oj Ocean Energy Utilization and Energy Conservation, Ministry of Education, Dalian University of Technology, Dalian; 116024, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 161-169
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: The active jet method on the suction surface of the hydrofoil can well control the cavitation flow around the hydrofoil and reduce the occurrence and development of cavitation. Therefore, based on the method of active jet, with the density-corrected SST k-co turbulence model and the Zwart-Gerber-Belamri cavitation model, the effect of jet parameters on the flow characteristic of cloud cavitation around the NACA66 (MOD) hydrofoil was numerically studied. According to the orthogonal design method, under the condition of incoming flow Re = 5. 07 x 10, the angle of attack a = 8°, and the cavitation number cr = 0. 83, by studying 16 groups of jet structures composed of different jet parameters, the influence of the jet position, jet angle and jet flow rate on the cavitation and hydrodynamic performance of the flow field around the hydrofoil was evaluated, and the optimal jet parameters were obtained. The results showed that the jet position had the greatest influence on the suppression of cavitation flow, and the jet angle had the maximum influence on the hydrodynamic performance. Using the optimal jet parameters can reduce the time-averaged dimensionless cavitation area by 46. 57% and increase the time-average lift-drag ratio by 5. 59% in the hydrofoil cavitation flow field. At this point, the injected jet in the downstream direction collided with re-entrant jet torwards the leading edge, which formed strong mixing and significantly consumed the momentum of the re-entrant jet, thereby preventing the re-entrant jet from continuing to move to the leading edge of the hydrofoil, greatly weakening the destabilizing shedding of attached cavitation. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 30
Main heading: Hydrofoils
Controlled terms: Angle of attack? - ?Cavitation? - ?Design? - ?Flow fields? - ?Hydrodynamics? - ?Lift drag ratio? - ?Turbulence models
Uncontrolled terms: Active injection? - ?Cavitation flow? - ?Cavitation suppression? - ?Cloud cavitations? - ?Hydrodynamics performance? - ?Jet angle? - ?Jet parameters? - ?NACA66 hydrofoil? - ?Orthogonal design? - ?Re-entrant jet
Classification code: 631.1 Fluid Flow, General? - ?631.1.1 Liquid Dynamics? - ?651.1 Aerodynamics, General
Numerical data indexing: Percentage 5.70E+01%, Percentage 5.90E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.015
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
40. Face Recognition Method of Dairy Goat Based on Improved YOLO v5s
Accession number: 20232214170730
Title of translation: YOLO v5s
Authors: Ning, Jifeng (1, 2); Lin, Jingya (1); Yang, Shuqin (2, 3); Wang, Yongsheng (4); Lan, Xianyong (5)
Author affiliation: (1) College of Information Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Shaanxi, Yangling; 712100, China; (3) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (4) College of Veterinary Medicine, Northwest A&F University, Shaanxi, Yangling; 712100, China; (5) College of Animal Science and Technology, Northwest A&F University, Shaanxi, Yangling; 712100, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 331-337
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to accurately and efficiently realize the contactless individual identification of dairy goats, a dairy goat individual identification method based on improved YOLO v5s was proposed by taking the facial images of dairy goats in captive environment as the research object. Firstly, totally 350 sheep face images were randomly collected from the network to form a sheep face facial detection dataset, and the YOLO v5s model was pre-trained by using the transfer learning idea to enable it to detect sheep face positions. Secondly, a facial image dataset was constructed, containing 3 844 different growth stages of 31 dairy goats, based on pre-trained YOLO v5s, SimAM attention module was introduced in the feature extraction layer to enhance the learning ability of the model, and CARAFE was introduced in the feature fusion layer. The sampling module can better restore facial details and improve the recognition accuracy of the model for individual faces of dairy goats. The experimental results showed that the average accuracy of the improved YOLO v5s model was 97. 41%, which was 6. 33 percentage points, 8. 22 percentage points and 15. 95 percentage points higher than that of the Faster R-CNN, SSD and YOLO v4 models, respectively, and 2. 21 percentage points higher than that of the original YOLO v5s model. The detection speed of the improved model was 56. 00 f/s, and the model size was 14. 45 MB. The method proposed can accurately identify dairy goat individuals with similar facial features, which provided a method support for the identification of livestock individuals in smart farming. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 23
Main heading: Face recognition
Controlled terms: Image enhancement? - ?Learning systems
Uncontrolled terms: Attention mechanisms? - ?Contact less? - ?Dairy goat? - ?Face recognition methods? - ?Facial images? - ?Individual identification? - ?Individual recognition? - ?Percentage points? - ?Transfer learning? - ?YOLO v5s
Numerical data indexing: Percentage 4.10E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.034
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
41. Experiment on Pressure Pulsation in Impeller of Large Submersible Tubular Pump
Accession number: 20232214170734
Title of translation:
Authors: Sun, Zhuangzhuang (1); Wang, Lin (1); Ge, Hengjun (2); Yuan, Haixia (2); Tang, Fangping (1)
Author affiliation: (1) College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou; 225100, China; (2) Yangzhou Survey and Design Institute Co., Ltd., Yangzhou; 225100, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 155-160 and 169
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In order to study the charaeteristics of pressure pulsation in the impeller of submersible tubular pump, three pressure monitoring points were set up near the leading edge, middle and trailing edge of the impeller using a dynamic pressure sensor to measure the pressure pulsation under multiple working conditions. The test results showed that the blade frequency and the blade frequency multiple were the main frequencies of the pressure pulsation in the blade area under different flow conditions. Under the large flow conditions, the main frequency at the leading edge and trailing edge of the blade was twice of the blade frequency, the middle of the blade was the blade frequency, and the main frequency of each monitoring point was the blade frequency under other conditions. The influence of cavitation on the pressure pulsation of the leading edge of the blade was more complicated. Under the large flow condition, the main frequency of the critical cavitation was changed from twice of the blade frequency to one time of the blade frequency, and the amplitude of the main frequency was decreased significantly when the deep cavitation reached. Under the design flow condition, the cavitation made the harmonic frequency rise, and the frequency domain distribution was wider. Under the small flow condition, the main frequency amplitude showed an upward trend with the development of cavitation. The amplitude of the dominant frequency in the middle and trailing edge of the blade showed an increasing trend with the development of cavitation. Under the same flow conditions, the pressure pulsation intensity was generally decreased from the middle, trailing edge to the leading edge of the blade, and the pressure pulsation intensity of each monitoring point in the impeller was generally decreased with the increase of flow rate. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 23
Main heading: Submersibles
Controlled terms: Cavitation? - ?Frequency domain analysis? - ?Hydraulic machinery? - ?Impellers? - ?Submersible pumps
Uncontrolled terms: Blade frequency? - ?Dynamic pressures? - ?Flow condition? - ?Main frequency? - ?Monitoring points? - ?Pressure monitoring points? - ?Pressure pulsation? - ?Submersible tubular pump? - ?Trailing edges? - ?Tubular pumps
Classification code: 601.2 Machine Components? - ?618.2 Pumps? - ?631.1.1 Liquid Dynamics? - ?632.2 Hydraulic Equipment and Machinery? - ?674.1 Small Marine Craft? - ?921.3 Mathematical Transformations
DOI: 10.6041/j.issn.1000-1298.2023.04.014
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
42. Design and Experiment of Two-degree-of-freedom Canopy Shaking Equipment Based on 5R Parallel Mechanism
Accession number: 20232214170740
Title of translation: 5R
Authors: Du, Xiaoqiang (1, 2); Han, Xintao (1); Shen, Tengfei (1); Li, Songtao (1); He, Leiying (1, 2)
Author affiliation: (1) Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province, Hangzhou; 310018, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 96-106
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Vibratory harvesting is an efficient form of mechanized harvesting of tree fruits. In the existing excitation form, non-circular excitation can produce effective vibrations in fruit trees, which can achieve an overall harvesting effect. In order to further improve the harvesting efficiency of fruits, the trajectories of different types of cycloid in non-circular excitation were researched in depth. Fruit tree flexible body models were built through SolidWorks, ANSYS, ADAMS and other software. The cycloid displacement loads of different trajectory parameters were imported into ADAMS, being applied to the excitation point of fruit tree model. By comparing the responses of the tree model to the cycloid displacement loads of different trajectories, the 3-branch No. 1 epitrochoid trajectory E was determined as the optimal excitation trajectory. According to the optimal excitation trajectory, a two-degree-of-freedom canopy shaking equipment driven by a 5R parallel mechanism was designed. The Camellia oleifera tree was used as the shaking object, and the excitation frequency of 6 Hz and amplitude of 90 mm were determined. An experiment prototype was designed and built. Experimental results showed that the shaking rod layout with 7x7 staggered distribution was the optimal layout, and the average synthetic acceleration of the canopy under this layout was 22. 38 m/s. The excitation acceleration transmission efficiency under the shaking rod layout was 77. 63%, which verified the effectiveness of the two-dimensional excitation trajectory. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 22
Main heading: Trajectories
Controlled terms: Degrees of freedom (mechanics)? - ?Efficiency? - ?Fruits? - ?Harvesting? - ?Orchards? - ?Transmissions
Uncontrolled terms: 5r mechanism? - ?Acceleration transmission efficiency? - ?Cycloid trajectory? - ?Excitation trajectory? - ?Non-circular? - ?Parallel mechanisms? - ?Shaking rod layout? - ?Transmission efficiency? - ?Two-degree-of-freedom? - ?Vibrating harvester
Classification code: 602.2 Mechanical Transmissions? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?913.1 Production Engineering? - ?931.1 Mechanics
Numerical data indexing: Frequency 6.00E+00Hz, Percentage 6.30E+01%, Size 9.00E-02m, Velocity 3.80E+01m/s
DOI: 10.6041/j.issn.1000-1298.2023.04.009
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
43. Effects of Exogenous Polyphenols Addition on Color and Anthocyanins of Dry Red Wine
Accession number: 20232314185720
Title of translation:
Authors: Li, Yunkui (1, 2); Zhang, Yu (1); Fan, Shuyue (1); Tao, Yongsheng (1, 2)
Author affiliation: (1) College of EnologyNorthwest a and F University, Shaanxi, Yangling; 712100, China; (2) Ningxia Helan Mountain’s East Foothill Wine Experiment and Demonstration Station, Northwest A&F University, Yongning; 750104, China
Corresponding author: Tao, Yongsheng(taoyongsheng@nwsuaf.edu.cn)
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 399-406
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: Color is an important sensory characteristic and quality evaluation index of red wine; while anthocyanins are the important material basis for the color, stability and nutritional functions of red wine. The effect of exogenous addition of natural pigments on the color quality and anthocyanins of red wine was rarely discussed in previous studies. Cabernet Sauvignon dry red wine was added natural pigments and , as well as three kinds of polyphenols, baicalin, chlorogenic acid and gallic acid which have been studied intensively as control, before and after alcoholic fermentation to explore the effects of the basic physical and chemical properties, color quality and anthocyanins of the wine samples. The results showed that the color of the wine was deepened, the redness hue was intensified and the anthocyanin content was increased along with the adding of natural pigment and natural pigment before alcoholic fermentation. In contrast, the effect of the additions after alcoholic fermentation were weaker than that before alcoholic fermentation. The adding of natural pigment after alcoholic fermentation was beneficial to the stability of anthocyanins, but the effect was weaker than that before alcoholic fermentation. The treatment of other polyphenols had less effect on the color quality of the tested wine. The research result clarified that the addition of polyphenols before alcoholic fermentation was more beneficial for the improvement and stability of the color quality of red wine, as well as for the stability of anthocyanins. Relatively, natural pigment was the best copigment. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 28
Main heading: Quality control
Controlled terms: Anthocyanins? - ?Color? - ?Fermentation? - ?Stability? - ?Wine
Uncontrolled terms: ’Dry’ [? - ?Alcoholic fermentation? - ?Color quality? - ?Color visualization? - ?Copigmentation? - ?Natural pigment? - ?Polyphenols? - ?Red wine? - ?Sensory characteristics? - ?Sensory qualities
Classification code: 741.1 Light/Optics? - ?804.1 Organic Compounds? - ?822.3 Food Products? - ?913.3 Quality Assurance and Control
DOI: 10.6041/j.issn.1000-1298.2023.04.042
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
44. Research Progress Analysis of Auto-orientation Technologies in Agriculture
Accession number: 20232214170718
Title of translation:
Authors: Gui, Yongjie (1, 2); Wang, Minghui (1, 3)
Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Shaanxi, Yangling; 712100, China; (3) Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Shaanxi, Yangling; 712100, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 1-20
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: With the rapid development of information perception technology and robotics technology, automatic orientation has more requirements and implementation methods. Automatic orientation technology provides favorable conditions for the automation and intelligence of intelligent agricultural production process. Automatic orientation is one of the important links to improve operation efficiency and quality. Automatic orientation technology has become the development direction of agricultural production automation and intelligent operation technology. Firstly, the basic concept and connotation of automatic orientation technology was expounded, the research progress of automatic orientation technology at home and abroad in agricultural fields such as field sowing, post mining treatment, livestock breeding and processing was summarized, and the characteristics, advantages and disadvantages of different application fields were analyzed and compared. Then the application research of the key technology of automatic orientation was systematically analyzed, including the common key problems of the orientation mechanism and method, the orientation mechanism and device, the automatic detection and control, and the openness of the technology in this field was summarized. Finally, the challenges and opportunities of automatic orientation technology were summarized. And the future research direction of automatic orientation technology and device were prospected, such as automatic orientation technology and equipment for agricultural machinery and agronomy integration, special and general automatic orientation technology and equipment, automatic orientation technology and equipment with multi-function and comprehensive integration, automatic orientation technology and equipment combined with intelligent technology. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 124
Main heading: Agricultural technology
Controlled terms: Agricultural machinery? - ?Mining
Uncontrolled terms: Agricultural equipment? - ?Agricultural productions? - ?Automatic orientation? - ?Favorable conditions? - ?Information perception? - ?Orientation mechanism? - ?Overview? - ?Production process? - ?Robotic technologies? - ?Technology and equipments
Classification code: 502.1 Mine and Quarry Operations? - ?821.1 Agricultural Machinery and Equipment
DOI: 10.6041/j.issn.1000-1298.2023.04.001
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
45. Dynamic Flow Field Analysis and Parameter Optimization of Premixing Device of Spray
Accession number: 20232214170731
Title of translation:
Authors: Sun, Wenfeng (1); Wang, Jin (1); Chang, Jinkai (1); Wang, Hao (1); Lu, Jiaqi (1); Zhu, Xiaoxin (1)
Author affiliation: (1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 83-95
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: In view of the practical problems existing in plant protection operations such as long premixing time, uneven premixing effect and uniformity of the premixing device of the spray, based on the existing sprayer premixing device, the basic parameters of key components such as premixing tank, premixing nozzle and feeding valve were determined by combining the pesticide formulation usage and premixing liquid delivery demand of 1 000 L sprayer in the field operation process. ANSYSFluent was used to analyze the dynamic flow field characteristics of premixing at different liquid level heights, and the dynamic distribution law of the flow field in the premixing tank was obtained. Using the quadratic regression orthogonal rotation center combination optimization test method, taking the working pressure and spatial position parameters of the premixed nozzle as the influencing factors, and the variation coefficient of the uniformity of the liquid pesticide as the evaluation index, the multi island genetic algorithm was used to optimize and obtain a better premixed parameter combination; the working pressure of the premixed nozzle is 0. 3 MPa, the distance from the bottom plane is 200 mm, and the distance from the back vertical plane is 70 mm. Field tests were conducted on powdered pesticides, and the results showed that the coefficient of variation of uniformity of the premixed solution was 32. 99%. The feeding valve delivers the pesticide stably at a pressure of 0. 2 ~ 0. 5 MPa without backflow. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 46
Main heading: Feeding
Controlled terms: Flow fields? - ?Genetic algorithms? - ?Pesticides? - ?Spray nozzles? - ?Tanks (containers)
Uncontrolled terms: Boom sprayer? - ?Dynamic flow field? - ?Feeding valve? - ?Field parameters? - ?Flow fields analysis? - ?Premixed? - ?Premixed nozzle? - ?Premixing? - ?Premixing device? - ?Working pressures
Classification code: 619.2 Tanks? - ?631.1 Fluid Flow, General? - ?691.2 Materials Handling Methods? - ?803 Chemical Agents and Basic Industrial Chemicals
Numerical data indexing: Percentage 9.90E+01%, Pressure 3.00E+06Pa, Pressure 5.00E+06Pa, Size 2.00E-01m, Size 7.00E-02m, Volume 0.00E00m3
DOI: 10.6041/j.issn.1000-1298.2023.04.008
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
46. Real-time Detection Method of Fruit Leaf Wall Area Based on Improved YOLACT
Accession number: 20232214170721
Title of translation: YOLACT
Authors: Xiao, Ke (1, 2); Liang, Congzhe (1); Xia, Weiguang (1)
Author affiliation: (1) College of Information Science and Technology, Hebei Agricultural University, Baoding; 071001, China; (2) Hebei Key Laboratory oj Agricultural Big Data, Baoding; 071001, China
Source title: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Abbreviated source title: Nongye Jixie Xuebao
Volume: 54
Issue: 4
Issue date: 2023
Publication year: 2023
Pages: 276-284
Language: Chinese
ISSN: 10001298
CODEN: NUYCA3
Document type: Journal article (JA)
Publisher: Chinese Society of Agricultural Machinery
Abstract: To reduce the environmental pollution and pesticide waste in orchards, a real-time method to detect the fruit tree leaf wall area (LWA) based on the improved YOLACT model was proposed to estimate average distance and density in the videos that captured by depth-color binocular camera, which can provide data for the real-time adjustment of pesticide spraying dose and spraying distance on intelligence pesticide spraying. Firstly, the YOLACT model was improved by using the ConvNeXt backbone network, and the NAM channel attention mechanism was introduced to optimize the model. Secondly, a leaf wall density estimation method based on deep learning was proposed. Finally, the average distance calculation method of LWA was proposed by excluding the interference information in the depth image through the threshold algorithm to simplify processing flow. The experimental results showed that the segmentation APall metrics of the improved YOLACT model was 91. 6%, which was increased by 3. 0 percentage points compared with that of the original model, and 2. 9 percentage points, 1. 2 percentage points and 4. 1 percentage points compared with that of YOLACT + +, Mask R-CNN, and Querylnst. The root mean square error (RMSE) of the leaf wall density estimation method was 1. 49%, 0. 82% and 2. 20%. And the processing speed of the real-time LWA detection method could reach 29. 96 f/s. ? 2023 Chinese Society of Agricultural Machinery. All rights reserved.
Number of references: 31
Main heading: Orchards
Controlled terms: Deep learning? - ?Fruits? - ?Mean square error? - ?Palmprint recognition? - ?Pesticides
Uncontrolled terms: Area-based? - ?Average Distance? - ?Detection methods? - ?Fruit trees? - ?Leaf wall density? - ?Percentage points? - ?Real- time? - ?Targets detection? - ?Wall density? - ?YOLACT model
Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?723.5 Computer Applications? - ?803 Chemical Agents and Basic Industrial Chemicals? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?922.2 Mathematical Statistics
Numerical data indexing: Percentage 2.00E+01%, Percentage 4.90E+01%, Percentage 6.00E+00%, Percentage 8.20E+01%
DOI: 10.6041/j.issn.1000-1298.2023.04.028
Compendex references: YES
Database: Compendex
Data Provider: Engineering Village
Compilation and indexing terms, Copyright 2023 Elsevier Inc.
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