农业机械学报

2022年第5期共收录49篇

1. Soil Erosion Law of Contour Rotary Tillage of Hillside Tractoron Sloping Land

Accession number: 20222212174438

Title of translation:

Authors: Sun, Jingbin (1, 2); Liu, Qi (1, 2); Luo, Pengxin (1); Yang, Fuzeng (1, 2); Liu, Zhijie (1, 2); Wang, Zheng (3)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling; 712100, China; (2) Scientific Observing and Experimental Station of Agricultural Equipment for the Northern China, Ministry of Agriculture and Rural Affairs, Yangling; 712100, China; (3) College of Forestry, Northwest A&F University, Yangling; 712100, China

Corresponding authors: Yang, Fuzeng(yangfzkm@nwafu.edu.cn); Yang, Fuzeng(yangfzkm@nwafu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 44-56

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem of soil tillage erosion (soil migration from the higher side of the sloping land to the lower side) and its unknown mechanism during the contour rotary tillage operation of the slopes in the hilly and mountainous areas of the Loess Plateau. Through the combination of theoretical analysis, simulation test, soil trough and field test, the research on the erosion mechanism of rotary tillage by hillside tractor on sloping land was carried out in depth. Firstly, the parameter equation of soil disturbing volume of H245 standard rotary blade under sloping conditions was constructed, the classical mechanical analysis of the soil disturbing process of the rotary blade was completed, and the main influencing factors of soil erosion were determined: tillage depth, rotary blade shaft speed and rotary tillage forward speed. Then, based on the EDEM simulation software, the soil disturbance law of a single rotary blade and the whole rotary cultivator was studied, and it was concluded that the soil particles moved backwards under the dynamic sliding action of the side cutting edge of the rotary blade. The displacement of soil particles in the shallow layer was the largest, the displacement in the deep layer was the smallest, and the displacement of soil particles in the deep layer near the rotation center of the rotary blade was the largest. The lateral displacement direction of soil was affected by the direction of the tangential edge of the rotary blade, and the bending angle of the tangential edge largely determined the lateral throwing effect of soil particles. The vertical position of soil particles showed a trend of becoming deeper and then shallower as the rotary blade was immersed in the soil. Finally, the single factor and orthogonal tests of rotary tillage were carried out on the spot with the rotational speed of the rotary tiller shaft, the rotational tillage speed and the slope angle as the test factors. The single factor test obtained the law of soil horizontal and lateral displacement changing with the above three factors. The variance analysis of the orthogonal test showed that the factors affecting the lateral displacement of the soil were the slope angle, the rotational speed of the rotary tiller shaft, the speed of the rotary tillage, and the factors affecting the horizontal displacement of the soil were the speed of the rotary tillage, the slope angle, and the rotational speed of the rotary tiller shaft. The regression equation between the soil lateral displacement, the horizontal displacement and the independent variables was obtained by fitting, and the optimal operating parameters combination of the rotary tiller was determined under the five setting slope angles through parameter optimization. The research result can provide good technical guidance for the high-efficiency and low-erosion operation of the existing rotary cultivator in the sloping tillage area of the Loess Plateau, and it can also provide research ideas for the innovative design of the subsequent rotary cultivator for sloping land. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 25

Main heading: Soils

Controlled terms: Computer software? - ?Cultivation? - ?Erosion? - ?Factor analysis? - ?Landforms? - ?Mechanisms? - ?Rotating machinery? - ?Rotation? - ?Sediments? - ?Speed ? - ?Tractors (agricultural)? - ?Tractors (truck)? - ?Turbomachine blades

Uncontrolled terms: Contour rotary tillage? - ?Erosion law? - ?Hillside tractor? - ?Lateral displacements? - ?Rotary blades? - ?Rotary tillages? - ?Sloping land? - ?Soil particles? - ?Tillage erosion? - ?Tillage erosion law

Classification code: 481.1 Geology? - ?483 Soil Mechanics and Foundations? - ?483.1 Soils and Soil Mechanics? - ?601.1 Mechanical Devices? - ?601.3 Mechanisms? - ?663.1 Heavy Duty Motor Vehicles? - ?723 Computer Software, Data Handling and Applications? - ?821.1 Agricultural Machinery and Equipment? - ?821.3 Agricultural Methods? - ?922.2 Mathematical Statistics? - ?931.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2022.05.005

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

2. Design and Experiment of Precise Feeding System for Pond Crab Culture

Accession number: 20222212173748

Title of translation:

Authors: Sun, Yueping (1, 2); Chen, Zuxu (1); Zhao, Dean (1); Zhan, Tingting (1); Zhou, Wenquan (3); Ruan, Chengzhi (4)

Author affiliation: (1) School of Electrical and Information Engineering, Jiangsu University, Zhenjiang; 212013, China; (2) Changzhou Dongfeng Agricultural Machinery Group Co., Ltd., Changzhou; 213200, China; (3) Changzhou Jintan District Aquatic Products Technical Guidance Station, Changzhou; 213299, China; (4) School of Mechanical and Electrical Engineering, Wuyi University, Wuyishan; 354300, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 291-301

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Traditional pond crab culture mainly relies on fishermen to estimate the total bait based on experience, and feed bait by manual punting, which has low bait utilization rate and high labor intensity. Because river crabs have territorial awareness and small moving range, the distribution of river crabs in the pond is uneven, thus the scientific and accurate feeding is required for the crab culture. The existing feeding operation mode of river crab culture is extensive, which can not meet the needs of efficient ecological culture of river crab. In order to grasp the growth law of river crabs and feed more scientifically and effectively, a precise feeding system based on river crab growth model was designed. The grey correlation analysis method was adopted in the growth model of the river crab to determine the environmental factors that have the greatest impact on the growth and development of the river crab. Based on the traditional aquatic biological growth model, environmental factors were added to improve the river crab growth model, which was optimized and fitted from the linear and exponential perspectives. The GA-BP neural network was used to train the accurate feeding prediction model, and the optimal environmental impact factor value was calculated by inputting environmental parameters such as water temperature, dissolved oxygen content, and pH value. Then the total weight of the crabs was obtained according to the growth model, breeding density and breeding area of the river crab. Combined with the survival rate and feeding rate of river crab during the growth period, the total bait weight can be determined. Finally, according to the actual distribution density of crabs and water quality parameters, the bait distribution coefficient of each area in the pond was determined, and the total bait was allocated to each area of the pond scientifically. The simulation results showed that the determination coefficient R2 of predicted total bait weight was 0.990, and the fitting effect of the prediction model was good. Through pond feeding experiments, the results showed that based on the total bait determination by using the growth model of river crab, the pond area that could be accurately fed by the automatic feeding boat was 5.33 hm2, saving the labor cost of three farmers. Compared with the preset feeding density for each area of the pond, the average absolute error of the actual feeding density performed by the feeding boat was 0.32 g/m2 and the average relative error was 3.90%. In addition, the feeding weight can be adjusted timely by the system according to the changes of the environmental parameters and the feedback from feeding table, which was conducive to saving bait, cultivating large crabs, increasing crab production, improving breeding efficiency, and promoting cost-effective development of crab culture. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 32

Main heading: Feeding

Controlled terms: Boats? - ?Correlation methods? - ?Dissolved oxygen? - ?Environmental impact? - ?Factor analysis? - ?Hydrodynamics? - ?Lakes? - ?Location? - ?Neural networks? - ?Rivers ? - ?Shellfish? - ?Wages? - ?Water quality

Uncontrolled terms: BP neural networks? - ?Crab? - ?Environmental factors? - ?Environmental parameter? - ?Feeding system? - ?GA-BP neural network? - ?Grey correlation analysis? - ?Growth models? - ?Precise feeding? - ?Prediction modelling

Classification code: 445.2 Water Analysis? - ?454.2 Environmental Impact and Protection? - ?461.9 Biology? - ?674.1 Small Marine Craft? - ?691.2 Materials Handling Methods? - ?912.4 Personnel? - ?922.2 Mathematical Statistics

Numerical data indexing: Linear density 3.20E-04kg/m, Percentage 3.90E+00%

DOI: 10.6041/j.issn.1000-1298.2022.05.030

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

3. Simulation of Land Use Change in Typical Coal Mining City Based on CLUE-S Model

Accession number: 20222212173659

Title of translation: CLUE-S

Authors: Zhao, Mingsong (1, 2); Xu, Shaojie (1, 2); Deng, Liang (3); Liu, Binyin (1); Wang, Shihang (1, 2); Wu, Yunjin (4, 5)

Author affiliation: (1) School of Geomatics, Anhui University of Science and Technology, Huainan; 232001, China; (2) Key Laboratory of Aviation-Aerospace-Ground Cooperative Monitoring and Early Warning of Coal Mining-induced Disasters of Anhui Higher Education Institutes, Anhui University of Science and Technology, Huainan; 232001, China; (3) Anhui Institute of Geological Surveying and Mapping, Hefei; 230022, China; (4) Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing; 210042, China; (5) State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing; 210042, China

Corresponding authors: Wu, Yunjin(wyj@nies.org); Wu, Yunjin(wyj@nies.org)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 158-168

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Huainan in Anhui Province was selected as study area. The dynamic change characteristics of land use was explored by using land use data of 1985, 1995, 2005 and 2016. And then the future land use patterns were simulated and predicted based on CLUE-S model. The results showed that from 1985 to 2016, the cultivated land area in the study area was decreased by 11.62%; the area percentage of construction land and water body was increased by 7.98 percentage points and 4.29 percentage points, respectively. From 2005 to 2016, the comprehensive dynamic degree was the largest, and it was the stage where the change of each land use type was the strongest, which was 13.46%. The change rate of construction land was the fastest, with land use dynamic index of 5.19%. Land use types mainly changed between cultivated land, water area and construction land. Cultivated land converted to construction land and water area were the dominant land use change types. The area of cultivated land converted to construction land reached 207.61 km2, and the newly added water body was mainly distributed in the Panxie mining area. After adding soil quality factor and spatial autocorrelation, the Logistics regression effect of cultivated land and construction land was significantly improved, and the ROC was increased by 0.201 and 0.133, respectively. The main driving factor of cultivated land change was mean annual precipitation, which was negatively correlated with the cultivated land distribution probability; and the main driving force of construction land was GDP. Kappa index of land use simulation was 0.74, indicating that CLUE-S model had good capabilities of land use simulation in study area. On this basis, the CLUE-S model was used to predict the spatial distribution of land use in study area in 2028, 2034 and 2040. There was no significant change in the spatial distribution of land use in the future, and the area change of each land use was relatively stable. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 42

Main heading: Land use

Controlled terms: Probability distributions? - ?Regression analysis? - ?Spatial distribution

Uncontrolled terms: Autologistic regression? - ?Change simulation? - ?CLUE-S models? - ?Construction land? - ?Cultivated lands? - ?Land areas? - ?Landscape pattern? - ?Landuse change? - ?Study areas? - ?Waterbodies

Classification code: 403 Urban and Regional Planning and Development? - ?405.3 Surveying? - ?902.1 Engineering Graphics? - ?921 Mathematics? - ?922.1 Probability Theory? - ?922.2 Mathematical Statistics

Numerical data indexing: Percentage 1.162E+01%, Percentage 1.346E+01%, Percentage 5.19E+00%, Size 2.0761E+05m

DOI: 10.6041/j.issn.1000-1298.2022.05.016

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

4. Design and Test of Detecting System for Impurities in Walnut Based on Full Convolutional Neural Network Algorithm

Accession number: 20222212173728

Title of translation:

Authors: Xie, Lijuan (1, 2); Dai, Benhui (1, 2); Hong, Youjun (3); Ying, Yibin (1, 2)

Author affiliation: (1) College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou; 310058, China; (2) Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province, Hangzhou; 310058, China; (3) The East Red Forest in Wucheng, Jinhua; 321025, China

Corresponding authors: Ying, Yibin(ibeying@zju.edu.cn); Ying, Yibin(ibeying@zju.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 385-391

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming to solve the needs of foreign matter detection in walnut production line, a set of walnut impurity detection equipment was designed and built based on the existing universal walnut processing production line, including portable frame, image acquisition system, and constant light source system. The overall size was 470 mm¡Á600 mm¡Á615 mm. Walnuts from Zhejiang Province and impurities, including leaves, stones, paper, screws and fabric were photographed as detection objects by industrial camera above the production line in real time for intuitive image information data. An image segmentation technology combined with deep learning and computer vision, and the fully convolutional network (FCN) algorithm were applied to detect impurities that might occur in walnut production and processing. According to the test, the accuracy for detection and classification of walnut and foreign body was effective, which was 92.75% of training set and 90.35% of testing set. The speed of production line was 1 m/s. The recognition speed of detecting was 4.28 f/s, which can meet the requirements of real-time detecting of impurities. The biggest error was in the ¡°walnut-background¡±, where original walnut was predicted to be the background. The main reason was that some features in walnuts (such as cracks and lines) were similar to the background. Focusing on the analysis of foreign body error, it showed that impurities were mis-predicted as the ¡°background¡± much more than the impurities were mis-predicted as the ¡°walnut¡±. Two main reasons led to this difference. On the one hand, when labelling manually, the pollutants on the conveyor belt were not judged as foreign bodies. On the other hand, because the size of impurities was generally small and the cardinality of pixel points was insufficient, the influence of false prediction was greater, thus amplifying the error. The reliability of the model was good. Even if the artificial labeling error occurred, walnut was mislabeled as impurities, but the trained model could still distinguish walnut and adjacent impurities well. The method proposed was worthy of further study for the online detection of impurities in automatic production of walnut, and it was of great significance to broaden the market of nut food and improve its economic benefits. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 21

Main heading: Image segmentation

Controlled terms: Belt conveyors? - ?Classification (of information)? - ?Deep learning? - ?Error detection? - ?Light sources? - ?Object detection

Uncontrolled terms: Deep learning? - ?Design and tests? - ?Foreign bodies? - ?Images segmentations? - ?Impurities in? - ?Impurity detections? - ?Labelings? - ?Production line? - ?Real- time? - ?Walnut production line

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?692.1 Conveyors? - ?716.1 Information Theory and Signal Processing? - ?723.2 Data Processing and Image Processing? - ?903.1 Information Sources and Analysis

Numerical data indexing: Percentage 9.035E+01%, Percentage 9.275E+01%, Size 4.70E-01m, Size 6.00E-01m, Size 6.15E-01m, Velocity 1.00E00m/s

DOI: 10.6041/j.issn.1000-1298.2022.05.041

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

5. Prediction Model of Ammonia Emission from Chicken Manure Based on Fusion of Multiple Environmental Parameters

Accession number: 20222212173736

Title of translation:

Authors: Ding, Luyu (1); L¨¹, Yang (2); Li, Qifeng (1, 2); Wang, Chaoyuan (3); Yu, Ligen (1); Zong, Weixun (4)

Author affiliation: (1) Qingyuan Intelligent Agricultural Research Institute, Qingyuan; 511500, China; (2) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (3) College of Water Resources and Civil Engineering, China Agricultural University, Beijing; 100083, China; (4) Qingyuan Agricultural Science Research Institute, Qingyuan; 511500, China

Corresponding author: Yu, Ligen(yulg@nercita.org.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 366-375

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: NH3 is a major harmful gas that affects the growth of broilers in a chicken house. The accurate measurement and prediction of its emissions will help establish environmental regulation model and improve the welfare in the chicken house. The electrochemical sensors are commonly used in the real practice for measuring NH3 concentration, which shows a low accuracy and short life time and makes it difficult to measure NH3 emissions directly. Combined with the mechanism process of NH3 released from manure, CO2 and H2O emissions that are relatively easier and cheaper obtained are selected to predict NH3 emissions. The gaseous emissions from chicken manure housed in a deep litter system were experimentally simulated. The same amount of chicken manure was injected into the experimental setup for multiple days to simulate the daily manure generated in a chicken house, and to monitor the temperature, relative humidity and the emission of CO2, H2O and NH3 from manure. The prediction model for the NH3 emission was developed based on a variety of machine learning methods and environmental parameters. The importance of features and permutation were analyzed to explore the importance of parameters, and the partial dependence graph as well as the individual condition expectation graph were analyzed to explore the dependence of the model on the parameters. Water pressure difference (VPD) was calculated using the temperature and relative humidity and introduced in modeling according to the knowledge of mechanism process of ammonia emissions. Comparisons were made to investigate the influence of different parameters on the optimal model after the introduction of VPD. The model based on extreme random tree showed the best performance in predicting NH3 emissions, with R2 of 0.916 7, RMSE of 0.289 7 mg/(kg?h), and MAPE of 10.82%. The most important parameter in the model was the H2O emission, and the extreme random tree model had the greatest dependence on H2O emission. The introduction of VPD did not improve the prediction ability of extreme random trees. Therefore, the optimal model was the extreme random tree model established based on T, H, EH2O, ECO2 to predict the NH3 emission from broiler manure in a deep litter system. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 34

Main heading: Ammonia

Controlled terms: Animals? - ?Carbon dioxide? - ?Environmental regulations? - ?Fertilizers? - ?Forecasting? - ?Houses? - ?Machine learning? - ?Manures

Uncontrolled terms: Ammonia emissions? - ?Chicken manure? - ?Deep litter system? - ?Emissions rates? - ?Environmental parameter? - ?Harmful gas? - ?Optimal model? - ?Prediction modelling? - ?Random tree? - ?Tree modeling

Classification code: 402.3 Residences? - ?454.2 Environmental Impact and Protection? - ?804 Chemical Products Generally? - ?804.2 Inorganic Compounds? - ?821.2 Agricultural Chemicals? - ?821.5 Agricultural Wastes

Numerical data indexing: Mass 7.00E-06kg, Percentage 1.082E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.039

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

6. Identification and Counting Method of Potted Kumquat Fruits Based on Point Cloud Registration

Accession number: 20222212173612

Title of translation:

Authors: Zhu, Qibing (1); Zhang, Meng (1); Liu, Zhenfang (1); Huang, Min (1); Li, Xuecheng (1)

Author affiliation: (1) Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi; 214122, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 209-216

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Kumquat is a kind of indoor ornamental plant that is deeply loved by consumers. The number and spatial distribution of its fruits are important indicators that determine the quality and sales price of kumquat. The recognition methods based on RGB images or single-view point clouds were difficult to accurately complete the calculation of the total fruits amount of the whole plant, and could not comprehensively display the three-dimensional spatial distribution of fruits. Therefore, a fruit recognition method based on point cloud registration was proposed to solve the problems of fruit recognition and total counting of the whole plant. Firstly, plants were placed on a rotating platform, and a low-cost RGB-D camera was used to collect the point cloud of plants at six angles for 60¡ã every interval. The background was removed according to the spatial distance. The outlier noise was removed by radius filtering algorithm. The white color noise was removed based on the color information. And the ¡°flying pixels¡± and edge noises were removed according to normal vector features and Euclidean clustering algorithm. Based on the random sampling consensus algorithm, the cylindrical point cloud of the rotating platform was segmented and the central axis was calculated. The point cloud was rotated around the central axis by a corresponding angle for initial registration. Then the point-to-plane ICP algorithm was used for accurate registration. Finally, Euclidean clustering algorithm was used to divide the plant point cloud into multiple clusters. And the spherical segmentation of each cluster was performed based on the random sampling consensus algorithm. The segmented spherical point clouds were the identified fruits, and its three-dimensional spatial distribution could be displayed according to the center and radius of the sphere. Totally nine potted kumquat plants (149 fruits in total) were identified in the fruit growing stage. The results showed that the total recall was 85.91%, precision was 79.01% and F1 value was 82.32%. Compared with the ground truth, the coefficient of determination and mean absolute percentage error of the number of fruits calculated by the proposed method were 0.97 and 16.02%, respectively. The experimental results showed that the proposed method was independent of color information and could effectively recognition immature green fruits in the whole plant, which could provide a reference for fruit identification and yield estimation. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 30

Main heading: Cameras

Controlled terms: Clustering algorithms? - ?Color? - ?Fruits? - ?Spatial distribution? - ?Spheres? - ?Surface measurement

Uncontrolled terms: Color information? - ?Fruit recognition? - ?Point cloud registration? - ?Point cloud segmentation? - ?Point-clouds? - ?Potted kumquat? - ?Recognition methods? - ?RGB-D camera? - ?Rotating platform? - ?Whole plants

Classification code: 405.3 Surveying? - ?741.1 Light/Optics? - ?742.2 Photographic Equipment? - ?821.4 Agricultural Products? - ?902.1 Engineering Graphics? - ?903.1 Information Sources and Analysis? - ?921 Mathematics? - ?943.2 Mechanical Variables Measurements

Numerical data indexing: Percentage 1.602E+01%, Percentage 7.901E+01%, Percentage 8.232E+01%, Percentage 8.591E+01%, Percentage 9.70E-01%

DOI: 10.6041/j.issn.1000-1298.2022.05.021

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

7. Soil Moisture Inversion Based on Environmental Variables and Machine Learning

Accession number: 20222212174412

Title of translation:

Authors: Wang, Sinan (1); Li, Ruiping (1, 2); Wu, Yingjie (3); Zhao, Shuixia (3); Wang, Xiuqing (4)

Author affiliation: (1) College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Huhhot; 010018, China; (2) Inner Mongolia Autonomous Region Key Laboratory of Big Data Reseach and Application of Agriculture and Animal Husbandry, Huhhot; 010018, China; (3) Institute of Water Resources for Pastoral Area, China Institute of Water Resources and Hydropower Research, Huhhot; 010020, China; (4) Inner Mongolia Autonomous Region Surveying and Mapping Geographic Information Center, Huhhot; 010050, China

Corresponding authors: Li, Ruiping(nmglrp@163.com); Li, Ruiping(nmglrp@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 332-341

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to construct the modeling indicators of soil moisture content in the Mu Us sandy land using multi-source data, totally 17 variables, including microwave backscattering coefficient, surface temperature, silk hat transform factor, band reflectance, drought index and topographic factor were used as modeling factors. PLSR, extreme learning machine (ELM) and random forest (RF) were used to construct soil water content inversion models, verify and compare the models, and map soil water distribution in the study area. The results showed that the determination coefficient of temperature vegetation drought index was 0.64, followed by land surface temperature (0.6), ¦ÒVV (0.38), vegetation index (0.38), band 7 reflectance (0.35), ¦ÒVH (0.32), band 6 reflectance (0.3) and Albedo (0.26). Compared with the model constructed with unscreened variables, the accuracy of the model constructed with best subset selection (BSS) variables was improved. PLSR had the best performance in collinearity, and ELM regression model was the most stable. RF model had the highest accuracy, with a determination coefficient of 0.74, root mean square error of 8.85% and mean absolute error of 7.86% in April. In August, the determination coefficient was 0.75, the root mean square error was 8.86%, and the mean absolute error was 7.41%. There was no significant difference in soil water distribution trend between different methods. The highest soil water content occurred in the north and southeast of the study area, and the lower soil water content occurred in the flat area in the central and northern part of the study area. Using spectral index, environmental factor and topographic data, the multi-factor and multi-index comprehensive model can accurately retrieve the surface soil moisture in the Mu Us sandy land, which had reference value for the study of land desertification and ecological environment control in this area. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 40

Main heading: Least squares approximations

Controlled terms: Atmospheric temperature? - ?Backscattering? - ?Decision trees? - ?Drought? - ?Errors? - ?Forestry? - ?Knowledge acquisition? - ?Machine learning? - ?Mean square error? - ?Reflection ? - ?Regression analysis? - ?Remote sensing? - ?Soil moisture? - ?Soil surveys? - ?Surface properties? - ?Vegetation

Uncontrolled terms: Determination coefficients? - ?Environmental variables? - ?Partial least square regression? - ?Random forests? - ?Remote sensing inversion? - ?Remote-sensing? - ?Root mean square errors? - ?Soil water content? - ?Soil-water distribution? - ?Study areas

Classification code: 443.1 Atmospheric Properties? - ?443.3 Precipitation? - ?444 Water Resources? - ?483.1 Soils and Soil Mechanics? - ?723.4 Artificial Intelligence? - ?821.0 Woodlands and Forestry? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics? - ?931.2 Physical Properties of Gases, Liquids and Solids? - ?951 Materials Science? - ?961 Systems Science

Numerical data indexing: Percentage 7.41E+00%, Percentage 7.86E+00%, Percentage 8.85E+00%, Percentage 8.86E+00%

DOI: 10.6041/j.issn.1000-1298.2022.05.035

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

8. Spatial Pattern Differentiation and Influential Factors of Urban Underused Land in County Territories in Shanxi Province

Accession number: 20222212173686

Title of translation:

Authors: Liu, Huifang (1); Bi, Rutian (1); Wang, Jin (1); Guo, Yonglong (1)

Author affiliation: (1) College of Resource and Environment, Shanxi Agricultural University, Taigu; 030801, China

Corresponding author: Bi, Rutian(brt@sxau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 169-180 and 208

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Based on the theory of human-environment system, a theoretical analytical framework for the urban underused land was built. Taking 106 counties in Shanxi Province as the study unit, the spatial auto-correlation method and Geodetector method were employed, the spatial differentiation pattern of urban underused land in Shanxi Province was analyzed, also the leading factors for spatial differentiation of urban underused land in county territories in Shanxi Province were quantitatively detected, so as to explore the interaction mechanism between the urban underused land in county territories and spatial factors. The results showed that with the analytical framework of ¡°inefficiency-nature-economy-society¡± built, the acting path between urban underused land and spatial factors as well as their pattern of manifestation analyzed.It was found that, on the whole, two types of factors, respectively ¡°human¡± and ¡°earth¡±, and three dimensions, respectively, the natural dimension, the economical dimension and the social dimension, were there, among which the natural factor played a basic role in the spatial differentiation of underused land, while the economic factor played a decisive role, and the social factor had a strengthening and amplifying effect. Totally 89.09% of the urban underused land in county territories in Shanxi Province was less than 265.86 hm2, showing the features of low-value agglomeration and weak homogeneous agglomeration; in spatial distribution, the urban underused land in highly-developed county territories was more than that in not so highly-developed county territories, and the urban underused land in counties which were in a flat area was more than that in counties which were in a mountainous and hilly area. The size of permanent resident population, GDP, degree of external transportation convenience, regional average GDP and the number of industrial enterprises above designated size were the leading factors for spatial differentiation of urban underused land in Shanxi Province, though the driving forces of each factor were obviously different at the county level. Among various factor interactions, the non-linear enhancement type was of majority, supplemented by the double-factor enhancement type. Since the size of permanent resident population had the strongest influence on the factor interactions, the active effect of the population factor got highlighted. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 28

Main heading: Agglomeration

Controlled terms: Urban transportation

Uncontrolled terms: Autocorrelation methods? - ?County? - ?Human-environment systems? - ?Influence factor? - ?Influential factors? - ?Interaction mechanisms? - ?Spatial differentiation? - ?Spatial factors? - ?Spatial patterns? - ?Underused land

Classification code: 432 Highway Transportation? - ?433 Railroad Transportation? - ?802.3 Chemical Operations

Numerical data indexing: Percentage 8.909E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.017

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

9. Product Characteristics Changes during Animal Bone Pyrolysis

Accession number: 20222212174397

Title of translation:

Authors: Wang, Mengyan (1); Liu, Ye (1); Yao, Yumei (1); Zhang, Xinyan (1); Han, Lujia (1); Liu, Xian (1)

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

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 357-365

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Pyrolysis is an effective method to treat waste bones from livestock slaughter and a large amount of chars, which can be effectively used as adsorbents and other materials, are produced in the pyrolysis process. Based on the thermogravimetry, Fourier transform infrared spectroscopy and mass spectrometry (TG-FTIR-MS) as well as scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDX), the pyrolysis process and product information of bovine bones and porcine bones were systematically studied. The release characteristics of gaseous products had a relationship with the characteristics of thermogravimetry. More organic gases were produced in porcine bones during pyrolysis because of the high fat contents, including CH4, C2H4, and C2H6. CO2 and NH3 were released in the main pyrolysis stage (350~600). The aromaticity of bone char formed and was at a relatively high level at 500 and bone chars had a strong stability. During the carbonization stage, a small amount of CO was gradually released, and substances containing metal carbonyls were formed in the char. C was lost in the form of gas, while Ca and P accumulated during pyrolysis and remaind in inorganic components such as hydroxyapatite (Ca10(PO4)6(OH)2). Further, bovine bone char and porcine bone char were prepared at different pyrolysis temperatures (500~900), and the yields of them were maintained at 60% and 50%, respectively. The yield of low-temperature chars was higher. For the two types of bone char, the pyrolysis temperature and the types of raw materials had certain effects on their physical and chemical properties. The alkalinity and ash content of the bone char were increased with the increase of the pyrolysis temperature. The ash content of bone chars exceeded 90% at 900, and the pH value of the bovine bone char was significantly higher than that of porcine bone char. As the pyrolysis temperaturewas increased, the pore volume of bone char was decreased and the pore diameter was increased. The BET specific surface area of bovine bone char prepared at 500 was 172 m2/g, and its pore structure was more conducive to physical adsorption. The research results can provide theoretical basis and data support for the pyrolysis treatment of livestock bone and the production and application of bone char. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 29

Main heading: Carbonization

Controlled terms: Agriculture? - ?Alkalinity? - ?Ammonia? - ?Carbonyl compounds? - ?Carbonylation? - ?Energy dispersive spectroscopy? - ?Fourier transform infrared spectroscopy? - ?Hydroxyapatite? - ?Mammals? - ?Mass spectrometry ? - ?pH? - ?Pore structure? - ?Pyrolysis? - ?Scanning electron microscopy? - ?Temperature? - ?Thermochemistry? - ?Thermogravimetric analysis

Uncontrolled terms: Animal bones? - ?Ash contents? - ?Bone char? - ?Bovine bone? - ?Carbonisation? - ?Infrared: spectroscopy? - ?Porcine bones? - ?Product characteristics? - ?Pyrolysis process? - ?Pyrolysis temperature

Classification code: 641.1 Thermodynamics? - ?801 Chemistry? - ?801.1 Chemistry, General? - ?801.4 Physical Chemistry? - ?802.2 Chemical Reactions? - ?804.1 Organic Compounds? - ?804.2 Inorganic Compounds? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?931.2 Physical Properties of Gases, Liquids and Solids

Numerical data indexing: Inductance 2.00E+00H, Percentage 5.00E+01%, Percentage 6.00E+01%, Percentage 9.00E+01%, Size 1.72E+02m

DOI: 10.6041/j.issn.1000-1298.2022.05.038

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

10. Algorithm for Distribution Planning of Agricultural IoT Nodes Considering Wireless Transmission Loss

Accession number: 20222212174643

Title of translation:

Authors: Xie, Jiaxing (1, 2); Liang, Gaotian (1); Gao, Peng (1); Wang, Weixing (1, 3)

Author affiliation: (1) College of Electronic Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) Guangdong Modern Agricultural Science and Technology Innovation Center for Intelligent Orchard, Guangzhou; 510642, China; (3) Guangdong Engineering Research Center for Monitoring Agricultural Information, Guangzhou; 510642, China

Corresponding authors: Wang, Weixing(weixing@scau.edu.cn); Wang, Weixing(weixing@scau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 275-281

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The node location of the agricultural IoT node is of great significance for reducing power consumption. However, the existing literature rarely considers the loss in the signal transmission process in the node location problem, especially the diffraction loss caused by the terrain factor. A method of node location based on K-means and PSO algorithm was proposed. Firstly, the K-means algorithm was used to determine the approximate location of each route and the terminal which were responsible for docking according to the distance of the straight line. Then, considering the electromagnetic wave free space loss and diffraction loss, combined with the modeling of the nodal topography, using the Fresnel integral and free space loss formula, a fitness function was constructed. A variable inertia coefficient PSO algorithm was used to solve this function. This method increased the inertia weight factor to improve the particle search ability when the global optimal point was updated. Anyway, the inertia to accelerate the convergence of the algorithm was reduced. The improved PSO algorithm was used to optimize the location of routers and gateways. The simulation found that the routing position was optimized through the PSO algorithm, which can reduce the maximum transmission loss by up to 27.82%. Field inspection showed that the optimal communication quality selected by this algorithm was significantly higher than that of the nearby points, and the RSSI was improved by as much as 12% to 20%. In addition, the model gave the maximum electromagnetic wave loss data, which can be used to determine the maximum transmission power of the node and estimate the energy loss of the node, so as to make a more rational estimate of the overall energy consumption of the node, and effectively reduced the subjectivity and arbitrariness of nodes planning. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 23

Main heading: Agriculture

Controlled terms: Diffraction? - ?Electromagnetic waves? - ?Energy dissipation? - ?Energy utilization? - ?Internet of things? - ?K-means clustering? - ?Location? - ?Topography

Uncontrolled terms: Agricultural internet of thing? - ?Diffraction loss? - ?Free space loss? - ?Free spaces? - ?K-mean algorithms? - ?Node location? - ?Particle swarm optimization algorithm? - ?PSO algorithms? - ?Space loss? - ?Transmission-loss

Classification code: 525.3 Energy Utilization? - ?525.4 Energy Losses (industrial and residential)? - ?711 Electromagnetic Waves? - ?722.3 Data Communication, Equipment and Techniques? - ?723 Computer Software, Data Handling and Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?903.1 Information Sources and Analysis? - ?951 Materials Science

Numerical data indexing: Percentage 1.20E+01% to 2.00E+01%, Percentage 2.782E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.028

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

11. Optimized Design and Performance Test of Axial Flow Orchard Sprayer Air Delivery System

Accession number: 20222212173596

Title of translation:

Authors: Ru, Yu (1); Chen, Xuyang (1); Liu, Bin (1); Wang, Shuijin (1); Lin, Ming (2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing; 210037, China; (2) China Association of Agricultural Machinery Manufacturers, Beijing; 100083, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 147-157

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of short air delivery distance and chemical waste of traditional air-driven sprayers, an axial-flow air-delivery system suitable for traditional orchard sprayers was designed. By setting the installation angle, quantity, length of different air duct guide vanes, taper and outlet layout of the conical multi-outlet device, the airflow field of the air delivery system was further guided, and the corresponding airflow field distribution model was established. The best optimal design scheme of the air delivery system was selected by comparison, and a verification test was carried out. The research results showed that the influence of the parameters of the fan guide vanes on the outlet wind speed was significant from large to small as the length, installation angle, and quantity. When the angle was 10¡ã, the number was 6, the length was 20 cm, the taper of the conical multi-outlet device was 2.25, and the outlet layout was type A, the uniformity and size of the outlet wind speed of the air delivery system were the best. The relative errors was 4.66% and coefficients of variation of the experimental values was 3.63%, which verified the reliability of the numerical simulation results. On this basis, through the external flow field test of the sprayer, it could be seen that the boundary range of the jet was increased with the increase of outlet diameter and rotation speed, and the air delivery distance was also increased. At the wind delivery distance of 0~2 m, the wind speed was above 5 m/s and the attenuation range was obvious, when the air delivery distance was greater than 2 m, the attenuation of the airflow was relatively gentle, and the wind speed at 4 m reached about 1.5 m/s. After optimization, the air delivery system of the axial-flow orchard sprayer had a reasonable structure, and it could meet the needs of orchard plant protection machinery in terms of wind speed uniformity, size, boundary and range. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 30

Main heading: Wind

Controlled terms: Axial flow? - ?Ducts? - ?Flow fields? - ?Speed

Uncontrolled terms: Air conveying system? - ?Air delivery systems? - ?Air ducts? - ?Conical multi-outlet device? - ?Conveying systems? - ?Flow field simulation? - ?Installation angle? - ?Orchard sprayers? - ?Outlet device? - ?Wind speed

Classification code: 443.1 Atmospheric Properties? - ?631.1 Fluid Flow, General

Numerical data indexing: Percentage 3.63E+00%, Percentage 4.66E+00%, Size 0.00E00m to 2.00E+00m, Size 2.00E+00m, Size 2.00E-01m, Size 4.00E+00m, Velocity 1.50E+00m/s, Velocity 5.00E+00m/s

DOI: 10.6041/j.issn.1000-1298.2022.05.015

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

12. Design and Experiment of Panax notoginseng Bionic Excavating Shovel Based on EDEM

Accession number: 20222212173689

Title of translation:

Authors: Zhang, Zhaoguo (1, 2); Xue, Haotian (1, 2); Wang, Yichi (1, 2); Xie, Kaiting (1, 2); Deng, Yuxuan (1, 2)

Author affiliation: (1) Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming; 650500, China; (2) Mechanization Engineering Research Center of Chinese Medicinal Materials in Yunnan Universities, Kunming; 650500, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 100-111

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to reduce the digging resistance during Panax notoginseng harvesting, the roots and planting soil of Panax notoginseng were taken as the research object, the intrinsic physical parameters were measured, Bonding parameters were set to establish the discrete element model of roots and stems of Panax notoginseng, and the root and soil bonding mechanism was analyzed. The Hertz-Mindlin with JKR was used to establish the discrete element composite model of roots and stems and planting soil of Panax notoginseng. The theoretical mechanical model of the digging shovel was established and analyzed, and the design model size of the bionic digging shovel was determined as follows: 360 mm¡Á150 mm¡Á8 mm, entry angle of 30¡ã, half angle of the shovel tip of 60¡ã. The point cloud data of the three-dimensional boar head model were collected, the structural curve equation of the bionic shovel was determined, and the three-dimensional model of the bionic excavator shovel was established. The simulation comparison test of bionic excavator shovel and plane excavator shovel was carried out, the average displacement and average excavation resistance were obtained by tracking the particle displacement flow direction, and the drag reduction mechanism of excavation shovel surface was defined by analyzing the particle velocity vector. The drag reduction rate of the bionic excavator was 19.15% in the simulation test. The soil groove test was carried out with high-speed photography equipment and resistance acquisition equipment. The results showed that the flow direction of soil particles was consistent with the simulation trend. The average digging resistance of the bionic excavator and the surface excavator was 1 207.23 N and 1 594.49 N, and the drag reduction rate of the bionic excavator was 24.29%, which was very close to the drag reduction rate of the simulation test. It was verified that the discrete element model was accurate and reliable, the mechanical model of excavation shovel was constructed accurately, and the bionic structure design was reasonable. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 26

Main heading: Excavation

Controlled terms: Bionics? - ?Drag reduction? - ?Excavators? - ?High speed photography? - ?Shovels? - ?Soils? - ?Velocity control

Uncontrolled terms: Bionic digging shovel? - ?Digging shovels? - ?Discrete element models? - ?Discrete elements method? - ?Drag-reduction rate? - ?Mechanical modeling? - ?Mining mechanism? - ?Panax notoginseng? - ?Panax notoginseng rhizome? - ?Planting soils

Classification code: 461.1 Biomedical Engineering? - ?483.1 Soils and Soil Mechanics? - ?731.3 Specific Variables Control? - ?742.1 Photography

Numerical data indexing: Force 2.0723E+02N, Force 5.9449E+02N, Percentage 1.915E+01%, Percentage 2.429E+01%, Size 1.50E-01m, Size 3.60E-01m, Size 8.00E-03m

DOI: 10.6041/j.issn.1000-1298.2022.05.011

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

13. Design and Experiment of Yield Monitoring System of Grain Combine Harvester

Accession number: 20222212173798

Title of translation:

Authors: Jin, Chengqian (1, 2); Cai, Zeyu (1); Yang, Tengxiang (1); Liu, Zheng (1); Yin, Xiang (2); Da, Feipeng (3)

Author affiliation: (1) Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing; 210014, China; (2) School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo; 255000, China; (3) School of Automation, Southeast University, Nanjing; 210096, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 125-135

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of high cost, complex structure and low stability of grain combined harvester yield monitoring system, a grain harvester yield monitoring system was designed based on duty cycle measurement, which consisted of photoelectric sensor, GPS module, data processing unit, data storage unit and visualization unit. When the system worked, two voltage signals of grain covering and non-covering on the scraper were monitored by the reflection photoelectric sensor, and the highly corresponding duty ratio in the signal was processed by the software system. The relationship between the duty ratio and the output measurement model was used to obtain the output data, which was stored in the system together with the time and GPS data of the system. Through EDEM simulation and theoretical model analysis, the direct proportional relationship between the measured duty ratio and grain mass was deduced. The global model and local model were fitted to the measured duty cycle and grain mass by bench test, and the R2 of all the fitting lines were not less than 0.988. Then the global model and the local model were analyzed by the bench test. The bench test results showed that although the local model may be better for the measured data at fixed speed, the global model was more versatile. With the increase of measurement data, the relative error was decreased gradually. In the field experiment, the abnormal signals in the system measurement process were counted and analyzed. In order to reduce the influence of abnormal signals on the measurement error, the measured values of the system were calibrated with the actual output. The field experiment results showed that the maximum relative error of the yield monitoring system was 3.83%, the average relative error was 0.40%, and the overall error and error fluctuation of the system were small. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 35

Main heading: Harvesters

Controlled terms: Data handling? - ?Data visualization? - ?Digital storage? - ?Errors? - ?Grain (agricultural product)? - ?Monitoring? - ?Photoelectricity

Uncontrolled terms: Combine harvesters? - ?Duty ratios? - ?Global models? - ?Grain combine harvester? - ?Grain combines? - ?Grain flow? - ?Monitoring system? - ?Photoelectric sensors? - ?Production monitoring? - ?Yield monitoring

Classification code: 701.1 Electricity: Basic Concepts and Phenomena? - ?722.1 Data Storage, Equipment and Techniques? - ?723.2 Data Processing and Image Processing? - ?723.5 Computer Applications? - ?741.1 Light/Optics? - ?821.1 Agricultural Machinery and Equipment? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 3.83E+00%, Percentage 4.00E-01%

DOI: 10.6041/j.issn.1000-1298.2022.05.013

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

14. Severity Detecting of Pantana phyllostachysae Chao Infestation of Moso Bamboo by Selecting Optimal Sentinel-2A MSI Features

Accession number: 20222212173824

Title of translation: Sentinel-2A MSI

Authors: Xu, Zhanghua (1, 2); Zhou, Xin (1, 3); Yao, Xiong (4); Li, Qiaosi (5); Li, Zenglu (2, 6); Guo, Xiaoyu (2)

Author affiliation: (1) College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350108, China; (2) Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization, Sanming; 365004, China; (3) Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou; 350108, China; (4) College of Architecture and Planning, Fujian University of Technology, Fuzhou; 350118, China; (5) Department of Earth Sciences, The University of Hong Kong, Hong Kong; 999077, Hong Kong; (6) Faculty of Education, SEGi University, Kota Damansara; 47810, Malaysia

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 191-200

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Pantana phyllostachysae Chao (PPC) is one of the most important leaf-eating pests of bamboo forests in China. It has become a major factor threatening the health of Moso bamboo forest and restricting the high quality and sustainable development of bamboo industry. It also has the characteristics of group-occurring, periodicity, and extremely serious harm, etc. How to quickly and accurately detect the damage of the Moso bamboo forest is a problem that needs to be solved at this stage. Whereas remote-sensing products can support the quickly, accurate, and comprehensive monitoring of forest health. Therefore, Sentinel-2A MultiSpectral Instrument (MSI) data, with three bands at the red-edge position, was of great significance for pest and disease detection in forests. By screening 22 spectrally derived indicators (e.g. leaf abscission, greenness and water content) using ANOVA combined with recursive RFE, totally 10 features were finally obtained to identify PPC damage. Based on the above results, the XGBoost detection model was established to detect PCC damage with high recognition accuracy. The results showed that Sentinel-2A MSI bands 6, 7, 8, and 8a exhibited strong responses to PPC damage; the index constructed by the red-edge and near-infrared bands effectively reflected the damage to bamboo forests; the overall detection accuracy of model was 83.70% compared with 94.72%, 72.06%, 79.77%, and 92.41% for ¡®healthy¡¯, ¡®mildly damaged¡¯, ¡®moderately damaged¡¯, and ¡®severely damaged¡¯ categories, respectively. These results indicated that the XGBoost detection model provided valuable support for the large-scale monitoring of pest damage to Moso bamboo forests. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 37

Main heading: Bamboo

Controlled terms: Damage detection? - ?Diagnosis? - ?Forestry? - ?Infrared devices? - ?Remote sensing

Uncontrolled terms: Bamboo forests? - ?Detection models? - ?High quality? - ?Major factors? - ?Moso bamboo? - ?Multispectral instruments? - ?Optimal feature selections? - ?Pantana phyllostachysae chao? - ?Sentinel-2a multispectral instrument image? - ?Xgboost

Classification code: 461.6 Medicine and Pharmacology? - ?811.1 Pulp and Paper? - ?821.0 Woodlands and Forestry? - ?821.4 Agricultural Products

Numerical data indexing: Electric current -2.00E+00A, Percentage 7.206E+01%, Percentage 7.977E+01%, Percentage 8.37E+01%, Percentage 9.241E+01%, Percentage 9.472E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.019

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

15. Kinematic Analysis of Dual-mode Fusion 6-[(RPRRRP)R-R]US Parallel Mechanism

Accession number: 20222212173842

Title of translation: 6-[(RPRRRP)R-R]US

Authors: Chen, Yuhang (1); Zhao, Tieshi (2, 3); Guo, Jian¡¯gang (1); Chen, Lihuan (1); Hao, Zengliang (1)

Author affiliation: (1) School of Mechanical and Electrical, North China Institute of Aerospace Engineering, Langfang; 065000, China; (2) Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao; 066004, China; (3) Key Laboratory of Advanced Forging and Stamping Technology and Science, Ministry of Education, Yanshan University, Qinhuangdao; 066004, China

Corresponding authors: Zhao, Tieshi(tszhao@ysu.edu.cn); Zhao, Tieshi(tszhao@ysu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 438-448

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In many engineering applications, the fusion motion involving many components is required, each motion component has different properties. The different motion properties can be roughly divided into two types according to frequency and amplitude, namely, low frequency high amplitude and high frequency low amplitude, however, the commonly used driving device often works in only one mode. For this kind of application demand, a 6-[(RPRRRP)R-R]US parallel mechanism was designed to realize dual-mode motion fusion. The novel mechanism evolved from the typical 6-RUS configuration. The method of transforming the original driving pair R into (RPRRP)R-R dual-input sub closed loop mechanism was discussed. The forward and inverse kinematics solutions of the novel mechanism under single montion component mode and two components fusion mode were analyzed respectively. Two kinds of strategies, which was for allocation of dual-input inverse solution, were proposed. The forward kinematics of the novel mechanism was divided into two steps: firstly, according to the characteristics of dual-input sub closed loop, dichotomy method was used; secondly, for the outer 6-RUS configuration, forward kinematics was conducted by means of Newton method. Flow charts of the two steps were given. Through numerical examples, theoretical calculations were carried out for the inverse solution of dual-mode fusion under uniaxial motion, inverse solution of dual-mode fusion under multi-axial composite motion and for the forward solution driven by dual-input fusion, meanwhile, the kinematics simulation of numerical examples in different cases was carried out. The results showed that the difference between the theoretical value and the simulation value was on the order of 10-6, the correctness and validity of the theoretical method were proved. The mechanism proposed can be used as the pointing and stability coordinate adjustment device of vehicle-borne, shipborne and space-borne equipment to improve the operation performance. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 21

Main heading: Mechanisms

Controlled terms: Inverse kinematics? - ?Inverse problems? - ?Newton-Raphson method

Uncontrolled terms: Closed-loop? - ?Dual modes? - ?Dual-mode fusion? - ?Engineering applications? - ?Forward kinematics? - ?Inverse solution? - ?Kinematic Analysis? - ?Parallel mechanisms? - ?Property? - ?Sub closed-loop

Classification code: 601.3 Mechanisms? - ?921.6 Numerical Methods? - ?931.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2022.05.048

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

16. Simulation Optimization and Experiment of Finger-clamping Seedling Picking Claw Based on EDEM-RecurDyn

Accession number: 20222212173829

Title of translation: EDEM-RecurDyn

Authors: Hu, Jianping (1); Pan, Jie (2); Chen, Fan (2, 3); Yue, Rencai (1); Yao, Mengjiao (1); Li, Jing (1)

Author affiliation: (1) Jiangsu Provincial Key Laboratory of Modern Agricultural Equipment and Technology, Jiangsu University, Zhenjiang; 212013, China; (2) HUST-Wuxi Research Institute, Wuxi; 214174, China; (3) School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan; 430074, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 75-85 and 301

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to achieve efficient and high-quality seedling picking by the automatic transplanter, one working method of picking seedlings in a row and throwing them at the same time was proposed. Taking the finger-clamping seedling picking claw as the research object, the structure and working principle of seedling picking claw were expounded. A mathematical model of the seeding picking claw movement was established, combined with the mechanical characteristics of the pot and the root distribution characteristics, the size parameters of the various structural parts that made up the claws were optimized, and the virtual prototype model was established in RecurDyn. The mechanical properties of the bowl were tested through experiments, the data obtained from the experiment were processed, and the physical characteristic parameters of the particles were obtained, and then the bowl particle model was established in EDEM. Through EDEM-RecurDyn coupling to simulate the process of inserting, clamping and lifting the seedling picking claws. The influence of claws insertion depth and initial clamping depth on the effect of bowl while picking was analyzed. Simulation optimization showed that when the insertion depth of the seedling claw Id=34 mm, the average insertion velocity Iv=280 mm/s, the initial clamping depth Ci=4 mm, and the average clamping velocity Cv=250 mm/s, a better pot body integrity can be obtained. At 16 times/min, 20 times/min, 24 times/min, the claw picking test was carried out. The test showed that the finger-clamp claw picking success rate was above 96%, the pot body fragmentation rate was less than 1%, which had a good effect of picking and putting seedlings, which can maintain a good pot body integrity during seedling picking operations. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 30

Uncontrolled terms: Automatic transplanter? - ?Cosimulation? - ?EDEM? - ?High quality? - ?Insertion depth? - ?Parameter optimization? - ?Recurdyn? - ?Seeding picking claw? - ?Simulation optimization? - ?Working methods

Numerical data indexing: Percentage 1.00E00%, Percentage 9.60E+01%, Size 3.40E-02m, Size 4.00E-03m, Velocity 2.50E-01m/s, Velocity 2.80E-01m/s

DOI: 10.6041/j.issn.1000-1298.2022.05.008

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

17. Design and Test of Near Infrared Detecting Instrument for Available Nitrogen in Coco-peat Substrate

Accession number: 20222212173555

Title of translation:

Authors: Lu, Bing (1); Wang, Xufeng (2); He, Ke (1); Hu, Can (2); Gao, Xin (1); Tang, Xiuying (1)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) College of Mechanical and Electronic Engineering, Tarim University, Alar; 843300, China

Corresponding author: Tang, Xiuying(txying@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 316-324

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to realize rapid and real-time detection of available nitrogen in coco-peat substrate, a detecting instrument based on near infrared (NIR) diffuse reflectance spectroscopy was designed. The hardware system of this instrument mainly consisted of pretreatment device, pneumatic conveyor, gravity settling sample chamber, near infrared spectrum detection device, sample recovery device and air compressor. Totally 135 samples of coco-peat substrate with different available nitrogen contents were prepared. Original spectral data of these samples were obtained by the hardware system of the developed instrument. An optimal partial least squares regression model for predicting available nitrogen content of coco-peat substrate was established. The corresponding correlation coefficients of correction set and validation set were 0.973 and 0.965, respectively; the root mean square errors of correction set and validation set were 14.025 mg/(100 g) and 15.757 mg/(100 g), respectively; and the residual prediction deviation was 3.72. Based on the MFC development tool, the software interface of hardware control and real-time detection and analysis of the instrument was developed in C/C++ language. The optimal coco-peat substrate available nitrogen prediction model established was built into the software, and the functional hardware control and available nitrogen NIR spectroscopy detection was realized by one-button operation. The test results showed that the correlation coefficient between the predicted value of the developed instrument and the measured value of national standard was 0.883, and the root mean square error was 18.605 mg/(100 g). The instrument can realize the rapid and real-time detection of available nitrogen in coco-peat substrate, and the prediction performance was good, which can meet the actual needs of rapid evaluation of coco-peat substrate fertilizer. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 38

Main heading: Near infrared spectroscopy

Controlled terms: C++ (programming language)? - ?Forecasting? - ?Infrared devices? - ?Least squares approximations? - ?Mean square error? - ?Nitrogen fertilizers? - ?Peat? - ?Signal detection

Uncontrolled terms: Available nitrogen? - ?Coco-peat substrate? - ?Correlation coefficient? - ?Detecting instrument? - ?Hardware control? - ?Hardware system? - ?Nitrogen content? - ?Real-time detection? - ?Root mean square errors? - ?Validation sets

Classification code: 524 Solid Fuels? - ?716.1 Information Theory and Signal Processing? - ?723.1.1 Computer Programming Languages? - ?804 Chemical Products Generally? - ?821.2 Agricultural Chemicals? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics

Numerical data indexing: Mass 1.00E-01kg, Mass 1.4025E-05kg, Mass 1.5757E-05kg, Mass 1.8605E-05kg

DOI: 10.6041/j.issn.1000-1298.2022.05.033

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

18. Dispersion and Environmental Influencing for Bioaerosols in Dairy Farm in Summer

Accession number: 20222212174381

Title of translation:

Authors: Ru, Lin (1); Deng, Shuhui (2); Ding, Luyu (3, 4); L¨¹, Yang (3, 4); Li, Qifeng (3, 4); Shi, Zhengxiang (5)

Author affiliation: (1) College of Engineering, Heilongjiang Bayi Agricultural University, Daqing; 163319, China; (2) College of Civil and Hydraulic Engineering, Heilongjiang Bayi Agricultural University, Daqing; 163319, China; (3) Research Centre for Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (4) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (5) College of Water Resources and Civil Engineering, China Agricultural University, Beijing; 100083, China

Corresponding author: Deng, Shuhui(dsh@vip.sina.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 376-384 and 399

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Bioaerosol and environmental parameters were continuously collected in a large-scale dairy farm in Tianjin of China to explore the distribution of bioaerosols and the influence of multiple environmental factors on its concentration for dairy farm in typical a season. The temporal and spatial variations of concentration and particle size for bioaerosols in the dairy farm in summer were analyzed, and the importance of measured environmental factors on the concentration of bioaerosols was illustrated. Results showed that the concentration of bioaerosols at 1 m height above the ground was significantly greater than that at 4 m (P0.05). A smaller proportion was observed at the smaller particle size of carriers. About 80% of carriers had the particle size over 2.1 ¦Ìm. The importance of 10 environmental factors were analyzed on affecting the concentration of bioaerosols based on the random forest algorithm. Wind direction (WD), temperature (T), ultraviolet radiation intensity (UV) and suspended particulate matter concentration (PM100) showed a greater influence than other factors. The collinearity relationship among different influencing factors were analyzed through the hierarchical clustering method. There was a strong collinearity relationship among PM10, PM1 and PM2.5, and so did that between UV and GHI. This suggested that the strong collinearity influence factor can be removed to leave one factor within the group to saving the sampling cost. The conclusions obtained can provide a reference for the determination of air pollution emissions from domestic dairy farms. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 40

Main heading: Aerosols

Controlled terms: Cluster analysis? - ?Decision trees? - ?Environmental regulations? - ?Farms? - ?Particle size

Uncontrolled terms: Bioaerosols? - ?Concentration prediction? - ?Concentration prediction model? - ?Dairy farms? - ?Dispersion law? - ?Environmental factors? - ?Importance of environmental factor? - ?Particles sizes? - ?Prediction modelling? - ?Spatiotemporal dispersion law

Classification code: 454.2 Environmental Impact and Protection? - ?723 Computer Software, Data Handling and Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?961 Systems Science

Numerical data indexing: Percentage 8.00E+01%, Size 1.00E00m, Size 2.10E-06m, Size 4.00E+00m

DOI: 10.6041/j.issn.1000-1298.2022.05.040

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

19. Design and Experiment of Intermittent Synchronous Seeding and Reseeding Device of Duck-billed Corn Seed Metering Machine in Sloping Farmland

Accession number: 20222212174355

Title of translation:

Authors: Wang, Jinwu (1); Wang, Ziming (1); Xu, Changsu (1); Zhou, Wenqi (1); Du, Mujun (2); Tang, Han (1)

Author affiliation: (1) College of Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) Heilongjiang DEWO Technology Development Co., Ltd., Harbin; 150086, China

Corresponding author: Tang, Han(tanghan19910102@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 57-66

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of poor seeding quality and unstable performance of the duck-billed corn seed metering device under slope farming conditions, taking duckbill corn metering device as carrier, an intermittent synchronous seeding and reseeding device was designed. The overall structure and working principle of the seed metering device were described, the seeding, reseeding and seed guiding process of the corn seeds inside the seed metering device were analyzed, the structure parameters of key components such as the intermittent synchronous seeding and reseeding device of rocker, inner ratchet and duckbill type seed metering device of right-angle seed guide components were optimized. Combining theoretical analysis and agronomic requirements for sloping farmland sowing, the single factor test, orthogonal test and bed comparison experiment were carried out by selecting operating speed, return spring preload and operating slope angle as test factors, and taking seeding qualified index and seeding coefficient of variation as test indicators. The experiment results showed that the performance index was increased first and then decreased with the increase of working speed and working slope angle, as the return spring preload increased, it was firstly increased and then stabilized. When the operating speed was 1 m/s, the return spring preload was 15.6 N (model T4, wire diameter was 1 mm, middle diameter was 7 mm, original length was 25 mm), and the operating slope angle was 12¡ã, the seeding performance was the best, with seeding qualified index of 98.7% and seeding coefficient of variation of 10.2%. Compared with the traditional duckbill precision seed metering device, its eligibility index was increased by 9.5 percentage points, and it can meet the requirements of planting operations in sloping farmland environment. The research result can provide reference for the R&D and design of key technologies and supporting working parts for seeding under sloping farmland conditions. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 27

Main heading: Seed

Controlled terms: Farms? - ?Structural design

Uncontrolled terms: Condition? - ?Corn? - ?Corn seeds? - ?Duck-billed? - ?Operating speed? - ?Pre loads? - ?Seed-metering device? - ?Slope angles? - ?Sloping farmlands? - ?Synchronoi seeding and reseeding device

Classification code: 408.1 Structural Design, General? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.4 Agricultural Products

Numerical data indexing: Force 1.56E+01N, Percentage 1.02E+01%, Percentage 9.87E+01%, Size 1.00E-03m, Size 2.50E-02m, Size 7.00E-03m, Velocity 1.00E00m/s

DOI: 10.6041/j.issn.1000-1298.2022.05.006

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

20. Mechanism and Anti-clogging of Labyrinth-channel Emitters under Fluctuated Water Pressure

Accession number: 20222212173574

Title of translation:

Authors: Yu, Liming (1); Yu, Xingjiao (1); Guo, Huanhuan (1); Wang, Tiantian (1); Cui, Ningbo (2); Li, Na (1)

Author affiliation: (1) Faculty of Agriculture and Food, Kunming University of Science and Technology, Kunming; 650500, China; (2) State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu; 610065, China

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 342-349

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The clogging of emitter is one of the bottlenecks restricting the application and popularization of drip irrigation technology. Fluctuated water pressure was adopted to alleviate the problem of emitter clogging inwater with high sediment load.The control effect of three water pressure patterns (constant water pressure, step wave water pressure, trigonometric function wave water pressure) on the clogging of the emitter was evaluated, and the particle size characteristics of clogging substance in emitters and particle size gradation of the substance discharged from emitters under different pressure patterns were analyzed. The results showed that the anti-clogging performance of emitters under fluctuated water pressure treatment was better than that under constant water pressure, and the service life of emitters under fluctuated water pressure emitter was extended by 79.06%, while the waveform change of fluctuated water pressure had little effect on the anti-clogging performance of emitters, and the effective irrigation times provided by emitters under two different waveform of fluctuated water pressure were only 2.77% separated, under fluctuated water pressure treatment, the water flow in the labyrinth channel was violently turbulent, and the sand-carrying capacity of the water flow was enhanced, so that clogging substances deposited and attached to the labyrinth channel can be better removed, compared with the constant water pressure, the content of clay and silt in the emitter clogging substance was decreased by 22.19%~36.75% and 13.22%~25.06%, respectively. In addition, the particle size of emitter under fluctuated pressure was greater than that under constant pressure, and the maximum particle size of the sediment discharged from the emitter under the fluctuated pressure was 54.24 ¦Ìm. which was increased by 44.34% compared with that under constant water pressure. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 37

Main heading: Flow of water

Controlled terms: Hydraulics? - ?Irrigation? - ?Particle size? - ?Pressure effects? - ?Water treatment

Uncontrolled terms: Anti-clogging? - ?Clogging substance? - ?Constant water pressure? - ?Emitter? - ?Fluctuated water pressure? - ?Labyrinth channels? - ?Particle size gradations? - ?Particles sizes? - ?Water pressures

Classification code: 445.1 Water Treatment Techniques? - ?631.1.1 Liquid Dynamics? - ?632.1 Hydraulics? - ?821.3 Agricultural Methods? - ?931.1 Mechanics

Numerical data indexing: Percentage 1.322E+01%, Percentage 2.219E+01%, Percentage 2.506E+01%, Percentage 2.77E+00%, Percentage 3.675E+01%, Percentage 4.434E+01%, Percentage 7.906E+01%, Size 5.424E-05m

DOI: 10.6041/j.issn.1000-1298.2022.05.036

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

21. Grading Detection Method of Grape Downy Mildew Based on K-means Clustering and Random Forest Algorithm

Accession number: 20222212173601

Title of translation: K-meansRF

Authors: Li, Cuiling (1, 2); Li, Yukang (1, 3); Tan, Haoran (1, 3); Wang, Xiu (1, 2); Zhai, Changyuan (1, 2)

Author affiliation: (1) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (2) National Engineering Research Center of Intelligent Equipment for Agriculture, Beijing; 100097, China; (3) College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling; 712100, China

Corresponding authors: Zhai, Changyuan(zhaicy@nercita.org.cn); Zhai, Changyuan(zhaicy@nercita.org.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 225-236 and 324

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the difficulty of grape downy mildew grading detection under the complex background of natural environment, a method of grape downy mildew grading detection based on semantic segmentation combined with K-means clustering and random forest was proposed to realize the rapid grading of grape downy mildew. The image data set of grape downy mildew under the complex background of natural environment was constructed, and the semantic segmentation model of grape leaf was established by HRNet v2+OCR network to extract grape leaf image. The K-means clustering algorithm was used to decompose grape leaf image into several subregion images, and a small number of data sets were marked for random forest learning to realize grape leaf disease spot segmentation and extraction from leaf image. At the same time, in the process of grape leaf extraction and disease spot extraction, an image size transformation method was designed to solve the problem of low accuracy caused by image resolution. The accuracy of grape leaf segmentation model based on HRNet v2+OCR network was 98.45%, and the mean intersection over union was 97.23%. The accuracy rates of downy mildew grading of grape leaf front, back and both sides were 52.59%, 73.08% and 63.32%, respectively, and the accuracy rates of disease grade error less than or equal to grade 2 were 88.67%, 96.97% and 92.98%, respectively. The research results showed that the grape downy mildew grading detection method based on K-means clustering and random forest could accurately segment grape leaf and grape downy mildew spots under the complex background of natural environments, and achieve grape downy mildew rapid grading, providing method and model support for precise control of grape downy mildew. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 27

Main heading: K-means clustering

Controlled terms: Decision trees? - ?Disease control? - ?Extraction? - ?Fungi? - ?Image resolution? - ?Semantic Segmentation? - ?Semantics

Uncontrolled terms: Complex background? - ?Disease grading? - ?Downy mildew? - ?Grape downy mildew? - ?Grape leaves? - ?HRNet v2? - ?K-means++ clustering? - ?Natural environments? - ?Random forest algorithm? - ?Random forests

Classification code: 723.4 Artificial Intelligence? - ?802.3 Chemical Operations? - ?903.1 Information Sources and Analysis? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?961 Systems Science

Numerical data indexing: Percentage 5.259E+01%, Percentage 6.332E+01%, Percentage 7.308E+01%, Percentage 8.867E+01%, Percentage 9.298E+01%, Percentage 9.697E+01%, Percentage 9.723E+01%, Percentage 9.845E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.023

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

22. Analysis of Slope Trafficability and Optimized Design of Crawler Chassis in Hillside Orchard

Accession number: 20222212173678

Title of translation:

Authors: Han, Zhenhao (1, 2); Zhu, Licheng (2); Yuan, Yanwei (2); Zhao, Bo (2); Fang, Xianfa (1, 2); Zhang, Tianfu (2)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) State Key Laboratory of Soil-Plant-Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing; 100083, China

Corresponding authors: Fang, Xianfa(fangxf@caams.org.cn); Fang, Xianfa(fangxf@caams.org.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 413-421 and 448

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: It is a preferred scheme to use the crawler chassis as an available chassis for agricultural machinery. There is ample space for optimization in applying this scheme in the hillside orchard environment. To further improve the adaptability of the crawler chassis under complex driving road conditions, the topographic and geomorphological characteristics of the hillside orchard were referred to to carry out the slope trafficability analysis of the crawler chassis. And based on the simulation results of the multi-body dynamics analysis software RecurDyn, the prototype was improved, and experimental verification was carried out. Firstly, the critical structural parameters that affected straight-line driving, overcoming obstacles of the tracked chassis were discussed through theoretical analysis based on the available chassis. Then, a virtual machine prototype was constructed to analyze the impact of critical parameters on trafficability. According to the simulation analysis results, a center of gravity adjustment system to improve the slope trafficability of the crawler chassis was proposed. Finally, the indoor soil tank test was carried out. The test results showed that on the test road with slope of 10¡ã, the average maximum traction force of the improved prototype at yaw of 45¡ã was 1 926 N, which was an increase of 14.03% compared with that before improvement. After the improvement, the maximum obstacle height of the prototype was 230 mm, which was an increase of 27.78% compared with that before improvement. The maximum trench width of the prototype was 640 mm, which was increased by 28% compared with that before improvement. The research result could provide a practical reference for improving the slope driving performance of the crawler chassis in hillside orchards. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 18

Main heading: Computer software

Controlled terms: Automobile drivers? - ?Chassis? - ?Orchards? - ?Roads and streets? - ?Software prototyping? - ?Verification

Uncontrolled terms: Center of gravity? - ?Center of gravity adjustment system? - ?Crawler chassi? - ?Hillside orchard? - ?Multi-body dynamic analysis? - ?Optimisations? - ?Optimized designs? - ?Road condition? - ?Slope trafficability? - ?Trafficability

Classification code: 406.2 Roads and Streets? - ?432 Highway Transportation? - ?662.4 Automobile and Smaller Vehicle Components? - ?663.2 Heavy Duty Motor Vehicle Components? - ?721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory? - ?723 Computer Software, Data Handling and Applications? - ?723.1 Computer Programming? - ?821.3 Agricultural Methods? - ?912.4 Personnel

Numerical data indexing: Force 9.26E+02N, Percentage 1.403E+01%, Percentage 2.778E+01%, Percentage 2.80E+01%, Size 2.30E-01m, Size 6.40E-01m

DOI: 10.6041/j.issn.1000-1298.2022.05.045

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

23. Image Detection System of Corn Seed Internal Crack Based on CNN

Accession number: 20222212173795

Title of translation: CNN

Authors: Zhang, Yuzhuo (1); Wang, Decheng (1); Fang, Xianfa (2); L¨¹, Chengxu (2); Dong, Xin (2); Li, Jia (2)

Corresponding author: Wang, Decheng(wdc@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 309-315

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to efficiently detect the internal cracks of corn seeds, a detection system and batch detection method based on convolutional neural network (CNN) were designed, and the cracked and non-cracked corn seeds were collected to make a data set, and four classics of AlexNet, VGG11, InceptionV3 and ResNet18 were constructed. Convolutional neural network, and compared with the traditional algorithm model SVM and BP neural network at the same time. It was found that the convolutional neural network model was better than those two traditional algorithm models. The ResNet18 model had the best comprehensive detection performance. The recognition accuracy of single seeds with cracks was 95.04%, and the recognition accuracy of single seeds without cracks was 95.04% and 98.06%, and the per grain detection time was 4.42 s. During the corn seed internal crack recognition system based on ResNet18, the system experiment carried out 10 sets of batch recognition. The average accuracy rate of cracked seeds was 94.25%, and the average recognition accuracy rate of non-cracked seeds was 97.25%. The transmission of light source in batch recognition was not equivalent. Accuracy can be affected by reasons such as the internal cracks of all seeds and the lack of generalization caused by multiple loading of model weights. Finally, an automatic identification device for internal cracks in the seeds was built, and a software control device for identification was designed to complete the internal crack identification system of corn seeds. The deep learning algorithm provided a guarantee for the detection of internal cracks in corn seeds. The research result would lay a foundation for the detection of internal cracks in corn seeds in the assembly line. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 27

Main heading: Image recognition

Controlled terms: Convolution? - ?Convolutional neural networks? - ?Crack detection? - ?Deep learning? - ?Light sources? - ?Light transmission

Uncontrolled terms: Accuracy rate? - ?Algorithm model? - ?Convolution neural network? - ?Convolutional neural network? - ?Corn seeds? - ?Detection system? - ?Image detection systems? - ?Internal crack? - ?Recognition accuracy? - ?Single seeds

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?716.1 Information Theory and Signal Processing? - ?741.1 Light/Optics

Numerical data indexing: Percentage 9.425E+01%, Percentage 9.504E+01%, Percentage 9.725E+01%, Percentage 9.806E+01%, Time 4.42E+00s

DOI: 10.6041/j.issn.1000-1298.2022.05.032

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

24. Estimation of Winter Wheat LAI Based on Multi-dimensional Hyperspectral Vegetation Indices

Accession number: 20222212173777

Title of translation:

Authors: Umut, Hasan (1, 2); Nijat, Kasim (1, 2); Chen, Chen (1, 2); Mamat, Sawut (3)

Author affiliation: (1) Institute of Resources and Ecology, Yili Normal University, Yining; 835000, China; (2) College of Biological and Geographical Sciences, Yili Normal University, Yining; 835000, China; (3) College of Geographical Science, Xinjiang University, Urumqi; 830046, China

Corresponding authors: Nijat, Kasim(Nejatkasim@126.com); Nijat, Kasim(Nejatkasim@126.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 181-190

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Winter wheat is one of the important food crops in China, and its planting area and output are the second only to rice. In order to improve the accuracy of remote sensing estimation of winter wheat leaf area index (LAI) in arid regions, taking the LAI of winter wheat at the jointing stage as research object, based on the first derivative (FD) and second derivative (SD) differential preprocessing of the canopy hyperspectral data, the two-dimensional vegetation index (2DVI) and three-dimensional vegetation index (3DVI) of any band combination was calculated, and the correlation with LAI was carried out. To find the vegetation index of the best band combination; the artificial neural network (ANN), K-nearest neighbors (KNN) and support vector regression (SVR) were used to establish LAI estimation respectively model and verify the accuracy. The results showed that the correlation between vegetation index and LAI in any combination of wavelength bands was significantly improved, especially the correlation coefficient of FD-3DVI-4(714 nm, 400 nm, 1 001 nm) based on the FD preprocessing spectrum reached 0.93 (P2=0.89, the root mean square error (RMSE) was the lowest (0.31), and the relative analysis error (RPD) was 2.41. It was conclused that the K-nearest neighbor algorithm was more suitable for solving the nonlinear problem and improve the estimation accuracy, and it can provide a theoretical basis for the later crop growth evaluation and reasonable fertilization. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 33

Main heading: Crops

Controlled terms: Finite difference method? - ?Mean square error? - ?Motion compensation? - ?Nearest neighbor search? - ?Neural networks? - ?Pattern recognition? - ?Remote sensing? - ?Vegetation

Uncontrolled terms: Any band combination? - ?Band combinations? - ?First derivative? - ?HyperSpectral? - ?Leaf Area Index? - ?Multi dimensional? - ?Nearest-neighbor algorithms? - ?Vegetation index? - ?Wheat leaves? - ?Winter wheat

Classification code: 821.4 Agricultural Products? - ?921.5 Optimization Techniques? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics

Numerical data indexing: Size 1.00E-09m, Size 4.00E-07m, Size 7.14E-07m

DOI: 10.6041/j.issn.1000-1298.2022.05.018

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

25. Detection Model of Moisture Content of Single Maize Seed Based on Hyperspectral Image and Ensemble Learning

Accession number: 20222212173584

Title of translation:

Authors: Wu, Jingzhu (1); Zhang, Le (1); Li, Jiangbo (2); Liu, Cuiling (1); Sun, Xiaorong (1); Yu, Le (1)

Author affiliation: (1) Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing; 100048, China; (2) Beijing Agricultural Intelligent Equipment Technology Research Center, Beijing; 100097, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 302-308

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to establish a high-precision detection model of moisture content in single maize seed, totally 80 maize seed samples with different moisture content were prepared. Hyperspectral reflection image acquisition was carried out for maize embryo up and embryo down respectively. Totally 100 grains were sampled for each sample, and the wavelength range was 968.05~2 575.05 nm. PCA was used to quickly extract the spectrum of a single seed. After multiple scattering correction pretreatment, the random forest (RF) and AdaBoost algorithm were used to establish the moisture content detection model of a single seed, and the characteristics of the two algorithms were integrated. An improved RF based on weighting strategy was proposed to model the moisture content of a single seed. The improved RF model was established by using the upward spectral information of single maize seed embryo. The correlation coefficient R of the training set was 0.969, the root mean square error RMSEC of the training set was 0.094%, the test set R was 0.881, and the root mean square error RMSEP of the test set was 0.404%. The improved RF model was established by using the downward spectral information of single maize seed embryo. The training set R was 0.966, RMSEC was 0.100%, the test set R was 0.793 and RMSEP was 0.544%. The experimental results showed that the generalization ability and prediction accuracy of the improved RF were significantly better than that of RF and AdaBoost algorithms. The moisture content detection model of single maize seed with seed embryo upward was better than that with seed embryo downward. The maize seed moisture detection model established by hyperspectral detection technology combined with integrated learning algorithm had high prediction accuracy and good robustness. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 20

Main heading: Moisture

Controlled terms: Adaptive boosting? - ?Decision trees? - ?Information use? - ?Mean square error? - ?Moisture determination

Uncontrolled terms: %moisture? - ?Adaptive weighting? - ?Detection models? - ?Ensemble learning? - ?HyperSpectral? - ?Maize seeds? - ?Single maize seed? - ?Single seeds? - ?Test sets? - ?Training sets

Classification code: 723 Computer Software, Data Handling and Applications? - ?903.3 Information Retrieval and Use? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?922.2 Mathematical Statistics? - ?944.2 Moisture Measurements? - ?961 Systems Science

Numerical data indexing: Percentage 1.00E-01%, Percentage 4.04E-01%, Percentage 5.44E-01%, Percentage 9.40E-02%, Size 5.7505E-07m

DOI: 10.6041/j.issn.1000-1298.2022.05.031

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

26. Tea Bud Detection Based on Faster R-CNN Network

Accession number: 20222212173581

Title of translation: Faster R-CNN

Authors: Zhu, Hongchun (1); Li, Xu (1); Meng, Yang (2); Yang, Haibin (3); Xu, Ze (3); Li, Zhenhai (1)

Author affiliation: (1) College of Surveying Mapping and Spatial Information, Shandong University of Science and Technology, Qingdao; 266590, China; (2) Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (3) Tea Research Institute, Chongqing Academy of Agricultural Sciences, Chongqing; 402160, China

Corresponding author: Li, Zhenhai(lizh323@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 217-224

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Effective detection of tea buds is an important prerequisite for improving the precision of mechanical picking and planning the picking route to avoid harming tea plants. Considering the problems of low detection accuracy, poor robustness and slow speed of traditional target detection algorithm in complex background, Faster R-CNN was applied to recognize tea bud in complex background. Firstly, collected pictures were processed by equal cutting, label making and data enhancement to make VOC2007 dataset. The deep learning model on detecting tea bud types (single bud and one bud with one leaf/two leaves) was trained after setting up the environment and adjusting the model parameters, and the trained model was evaluated. The results showed that the average precision (AP) was 54%, and the root mean square error (RMSE) were 3.32 when the tea bud type was not distinguished. When distinguishing tea bud types, the AP of single bud and one bud with one leaf/two leaves were 22% and 75%, with RMSE of 2.84. When single bud was removed, the AP of one bud with one leaf/two leaves was 76%, with RMSE of 2.19. Compared with tea bud detection algorithm based on excess green and image binarization (traditional target detection algorithm), the deep learning target detection algorithm was superior to traditional target detection algorithm, with RMSE of 5.47, in accuracy and speed, especially under complex background. Deep learning algorithm demonstrated an important application prospect in realizing tea bud detection and automatic picking in intelligent tea garden image real-time detection system. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 31

Main heading: Mean square error

Controlled terms: Complex networks? - ?Convolutional neural networks? - ?Deep learning? - ?Plants (botany)? - ?Signal detection

Uncontrolled terms: CNN network? - ?Complex background? - ?Convolutional neural network? - ?Deep learning? - ?Identification and detection? - ?Mechanical? - ?Root mean square errors? - ?Target detection algorithm? - ?Tea bud? - ?Tea plants

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?716.1 Information Theory and Signal Processing? - ?722 Computer Systems and Equipment? - ?922.2 Mathematical Statistics

Numerical data indexing: Percentage 2.20E+01%, Percentage 5.40E+01%, Percentage 7.50E+01%, Percentage 7.60E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.022

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

27. Design and Test of Self-propelled Orchard Organic Fertilizer Strip-spreader

Accession number: 20222212173745

Title of translation:

Authors: Zhu, Xinhua (1); Li, Xudong (1); Gao, Xiang (1); Tan, Chen (2); Deng, Haitao (1)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling; 712100, China; (2) Engine R&D Center, Weichai Power Co., Ltd., Weifang; 261061, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 136-146

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to expand the function of the orchard straw mulching machine and solve the problem of the shortage of organic fertilizer fertilization machine in a hilly orchard, a self-propelled orchard organic fertilizer strip-spreader was developed based on the straw mulching machine. The machine was mainly composed of the vehicle body and the strip-spreading device. The strip-spreading device adopted a telescopic structure, and the spacing of the strip-spreading was 1.8~2.7 m, which was suitable for ditch fertilization or two-side strip spreading of organic fertilizer in orchard with row spacing of 3.0~4.5 m or applying base fertilizer along the rows for field crops or spreading cultivation substrate in strips. The discrete element method was used to optimize the fertilizing outlet structure of the strip-spreading device, and the best XK type fertilizing outlet structure was decided. The strip-spreading test results showed that the fertilizing amount of the decomposed cow manure was ranged from 29.40 t/hm2 to 53.10 t/hm2, and the coefficient of variation was less than or equal to 15.48%. The amount of the mushroom residue applied was 21.45~75.00 t/hm2, and the coefficient of variation was less than or equal to 6.57%. The determination coefficients of the fertilization quantitative models of the decomposed cow manure and the mushroom residue were 0.871 3 and 0.963 1, respectively. In the field test of orchard, the strip-spreader showed a good operation effect. The self-propelled orchard organic fertilizer strip-spreader can adapt to large-scale fertilization in a hilly orchard. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 34

Main heading: Fertilizers

Controlled terms: Crops? - ?Cultivation? - ?Manures? - ?Orchards? - ?Spreaders

Uncontrolled terms: Coefficients of variations? - ?Decomposed cow manures? - ?Ditch-fertilizing? - ?Fertilisation? - ?Orchard? - ?Organic fertilizers? - ?Outlet structures? - ?Straw mulching? - ?Strip-spreading device? - ?Telescopic spiral fertilizer apparatus

Classification code: 804 Chemical Products Generally? - ?821.2 Agricultural Chemicals? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?821.5 Agricultural Wastes

Numerical data indexing: Percentage 1.548E+01%, Percentage 6.57E+00%, Size 1.80E+00m to 2.70E+00m, Size 3.00E+00m to 4.50E+00m

DOI: 10.6041/j.issn.1000-1298.2022.05.014

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

28. Configuration Selection and Parameter Optimization of 6-PSS Parallel Mechanism with Planar Platform

Accession number: 20222212174475

Title of translation: 6-PSS

Authors: Wang, Qiming (1); Zhang, Hanzu (1); Jiang, Jiangyue (1); Song, Jing (1); Qin, Junxiong (1)

Author affiliation: (1) School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai; 200093, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 449-458

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The configuration selection and parameter optimization of 6-PSS parallel mechanism with planar platform were studied. According to the characteristics of 6-PSS parallel mechanism with planar platform, the essence of configuration selection was to solve layout problem of linear guides on base, and four typical configurations of 6-PSS parallel mechanism with planar platform were given. Firstly, the inverse kinematics model was established and the Jacobian matrix was derived and verified by ADAMS simulation. Secondly, in order to observe the shapes and ranges of workspace, workspace maps and their projections were drawn. Similarly, dexterity distribution diagrams were drawn to intuitively observe the distribution of dexterity. In addition, their workspace volume and global dexterity were calculated. By comparing the reachable workspace range, volume, dexterity distribution and global dexterity value of the four configurations, it was concluded that configuration had better performance in the above aspects. Then, for configuration , for the purpose of analyzing the effects of structural parameters on its workspace and dexterity. The projections of workspace corresponding to different structural parameters were drawn, and the workspace volume and the global dexterity corresponding to different structural parameters were calculated. The results showed that the workspace volume and global dexterity were positively correlated within a certain range of structural parameters, and its reasons were analyzed. Finally, the workspace volume was optimized and the optimal structural parameters were obtained. The workspace volume and global dexterity were significantly improved after optimization. And error analysis of the optimized mechanism was carried out. The research result had a strong guiding significance and reference value for the design of 6-PSS parallel mechanism with planar platform. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 25

Main heading: Mechanisms

Controlled terms: Inverse kinematics? - ?Inverse problems? - ?Jacobian matrices? - ?Structural optimization

Uncontrolled terms: 6-PSS parallel mechanism? - ?Configuration selection? - ?Dexterity? - ?Global dexterity? - ?Layout problems? - ?Optimization design? - ?Parallel mechanisms? - ?Parameter optimization? - ?Structural parameter? - ?Workspace

Classification code: 601.3 Mechanisms? - ?921.1 Algebra? - ?921.5 Optimization Techniques? - ?931.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2022.05.049

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

29. Full Coverage Path Planning Method of Agricultural Machinery under Multiple Constraints

Accession number: 20222212173605

Title of translation:

Authors: Chen, Kai (1); Xie, Yinshan (1); Li, Yanming (1); Liu, Chengliang (1); Mo, Jinqiu (1)

Author affiliation: (1) School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai; 200240, China

Corresponding author: Mo, Jinqiu(mojinqiu@sjtu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 17-26 and 43

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to meet the requirements for automatic navigation operations and optimize the efficiency of agricultural machinery operations, a path planning algorithm formed by mixed rules was proposed based on simulated annealing method, after dealing with the constraints of various turning methods and agricultural plots. In terms of multi-constraint processing, the adjacency matrix of agricultural machinery turning cost was introduced to quantify the influence of different turning modes, and the block boundary and obstacle boundary were respectively dealt by using improved Douglas-Peucker fitting algorithm and the minimum convex hull of sampling points was solved. After the reserved area for turning were obtained by using the parallel migration of angle bisectors, the optimal crop rows of multi-shape parcels were generated in order to reduce the cost of turning. In traversal order of agricultural machinery, full coverage traversal order was formed by disassembling crop rows into units, solving the optimal units with simulated annealing method and assembling to a whole path. The algorithm solved the problem that traditional planning methods were hard to adapt to different conditions and classical simulated annealing method fell into local optimal solution easily in large scale planning. The experiment results showed that coverage of the paths obtained by proposed method was up to 90.78% in average and the average duty cycle was 85.10%. Under the same conditions, the proposed path can save up to 30.3% distance consumption compared with the traditional path, and 6.9% compared with the path formed by simulated annealing algorithm. The results showed that the proposed algorithm can plan the operation path for agricultural machinery under various constraints and reach a better planning effect. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 30

Main heading: Simulated annealing

Controlled terms: Agricultural machinery? - ?Crops? - ?Motion planning

Uncontrolled terms: Condition? - ?Coverage path planning? - ?Crop row unit disassembling and composing? - ?Crop rows? - ?Dougla-peucke fitting algorithm? - ?Douglas-Peucker? - ?Fitting algorithms? - ?Multiple constraint? - ?Navigation of agricultural machinery? - ?Simulated annealing method

Classification code: 537.1 Heat Treatment Processes? - ?821.1 Agricultural Machinery and Equipment? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 3.03E+01%, Percentage 6.90E+00%, Percentage 8.51E+01%, Percentage 9.078E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.002

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

30. Structural Synthesis and Innovative Design of Multi-link Planting Mechanism Based on Graph Theory

Accession number: 20222212173752

Title of translation:

Authors: Sun, Liang (1, 2); Zheng, Guanghui (1); Ye, Zhizheng (1); Yu, Gaohong (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

Corresponding authors: Yu, Gaohong(yugh@zstu.edu.cn); Yu, Gaohong(yugh@zstu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 67-74

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In view of the limited configuration of multi-link planting mechanism at present, a complete multi-link planting mechanism library was constructed by means of graph theory. Firstly, based on the method of weighted fourth power matrix and weighted minimum distance matrix, the similarity feature code of vertices was obtained in the kinematic chain synthesis of linkage mechanism. In accordant with the uniqueness of the feature code, the similarity recognition and isomorphism identification of the kinematic chain were conducted. Secondly, the specific screen rule of the planting mechanism configuration was established based on similarity of vertices, and then the functional vertices for input link, output link and rack were determined. The mechanism topology library of six-link to nine-link was established: the number of 6-link 1-DOF KCs was 14, the number of 7-link 2-DOF KCs was 17, the number of 8-link 1-DOF KCs was 510, and the number of 9-link 2-DOF KCs was 917. Finally, the configuration of different links consisted of six-link to eight-link in the planting mechanism library was selected for kinematics modeling, and the new size of six-, seven- and eight-link planting mechanisms suitable for planting operation were obtained. The correctness of the configuration synthesis method was verified by comparing the theoretical results with the motion simulation results, which provided more optional configurations for the innovative design of diversified planting mechanism. The use of structural synthesis method is conducive to the innovative design of planting mechanism. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 31

Main heading: Kinematics

Controlled terms: Codes (symbols)? - ?Design? - ?Graph theory? - ?Matrix algebra? - ?Set theory

Uncontrolled terms: Feature codes? - ?Innovative design? - ?Isomorphism identification? - ?Kinematic chain? - ?Multi-link? - ?Planting mechanism? - ?Plantings? - ?Similarity recognition? - ?Structural synthesis? - ?Synthesis method

Classification code: 723.2 Data Processing and Image Processing? - ?921.1 Algebra? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?931.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2022.05.007

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

31. Optimization Design and Tests of Picking Mechanism of Automatic Feeding Device for Willow Cuttings

Accession number: 20222212173565

Title of translation:

Authors: Ye, Bingliang (1, 2); Tang, Tao (1, 2); Yang, Qiulan (3); Mo, Canlin (1)

Author affiliation: (1) Faculty of Mechinical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province, Hangzhou; 310018, China; (3) Natural Science Education Center, Minghsin University of Science and Technology, Hsinchu; 30401, Taiwan

Corresponding author: Mo, Canlin(774526207@qq.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 93-99

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 high labor intensity and low efficiency of manual feeding in the semi-automatic cuttage operation for willow cuttings in China, a kind of automatic feeding device for willow cuttings that can realize the functions of orderly discharging, picking and feeding willow cuttings was proposed. The optimization design of the picking mechanism and related tests of the device was conducted in laboratory. The kinematics model and optimization design model of the picking mechanism were established, the self-developed software was used to analyze and determine the parameter range of the picking mechanism, and then the genetic algorithm toolbox of Matlab software was used to realize the parameter optimization of the picking mechanism. The structure design of the picking mechanism was completed, and the virtual motion simulation verification of the picking mechanism was carried out. The prototype of the picking mechanism and the test bench of the automatic feeding device were developed, and the high-speed camera test of the picking mechanism and feeding test of the automatic feeding device were carried out. The movement characteristics of the picking mechanism were studied, and the working performance of the device was inspected. When the automatic feeding efficiency reached 55 plants per minute, the success ratio of willow cuttings feeding was about 83%, which showed that the device had the feasibility of being applied to the automatic cuttage machine for willow cuttings. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 23

Main heading: Feeding

Controlled terms: Efficiency? - ?Genetic algorithms? - ?High speed cameras? - ?MATLAB

Uncontrolled terms: Automatic feeding? - ?Automatic feeding device? - ?Design and tests? - ?Feeding devices? - ?Labour intensity? - ?Optimization design? - ?Picking mechanism? - ?Semi-automatics? - ?Test? - ?Willow cutting

Classification code: 691.2 Materials Handling Methods? - ?723.5 Computer Applications? - ?742.2 Photographic Equipment? - ?913.1 Production Engineering? - ?921 Mathematics

Numerical data indexing: Percentage 8.30E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.010

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

32. Preparation and Application of Flexible Surface-enhanced Raman Substrates Based on Corn Straw

Accession number: 20222212173683

Title of translation:

Authors: Yu, Haitao (1); Zhang, Hui (1); Liang, Xueyan (1); Han, Lujia (1); Xiao, Weihua (1)

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

Corresponding author: Xiao, Weihua(xwhddd@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 350-356 and 365

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Due to the advantages of strong specificity and high sensitivity, surface-enhanced Raman spectroscopy (SERS) has been widely used in the detection of trace compounds. SERS substrates used for detection had become a research highlight in recent years. However, researchers mostly focused on the reduction of limits of detection, and seldom considered the cost. Cellulose acetate membrane was prepared by using cheap corn straw. Then, coupled with gold nanoparticles, an SERS substrate with stable test performance and low limits of detection was prepared. The characterization of the SERS substrates showed that the gold nanoparticles formed regular multilayer structure on the surface of cellulose acetate, which was conducive to the formation of ¡°hot spots¡± and increased the signal. Abundant pore structure and hydrophilicity of the SERS substrates made the enrichment test feasible. It also had a certain thermal stability, to ensure that a short time of laser irradiation would not burn the substrate. The SERS test results showed that the enrichment test had a lower limit of detection than the drop test. It can reach 10-7 g/mL, and had a good linear relationship in the concentration range of 10-7~10-6 g/mL. Applicability analysis showed that it had good detection effect on several kinds of water pollutants, and provided a technological process for preparing surface-enhanced Raman substrates from corn straw. Due to the cheap raw material and simple preparation process, the preparation cost of SERS substrates could be effectively reduced. Thus, it laid the application foundation for high value utilization of straw and rapid and high sensitivity detection of water pollutants. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 31

Main heading: Metal nanoparticles

Controlled terms: Cellulose? - ?Cost reduction? - ?Fiber optic sensors? - ?Gold nanoparticles? - ?Hydrophilicity? - ?Light transmission? - ?Pore size? - ?Pore structure? - ?Raman spectroscopy? - ?Substrates ? - ?Testing? - ?Water pollution? - ?Water treatment

Uncontrolled terms: Cellulose acetate membrane? - ?Characterization analyse? - ?Corn straws? - ?Flexible surfaces? - ?High sensitivity? - ?Lower limits of detections? - ?Raman substrates? - ?Surface enhanced Raman? - ?Surface enhanced Raman spectroscopy? - ?Water pollutants

Classification code: 445.1 Water Treatment Techniques? - ?453 Water Pollution? - ?741.1 Light/Optics? - ?741.1.2 Fiber Optics? - ?761 Nanotechnology? - ?811.3 Cellulose, Lignin and Derivatives? - ?815.1.1 Organic Polymers? - ?931.2 Physical Properties of Gases, Liquids and Solids? - ?951 Materials Science

Numerical data indexing: Mass density 1.00E+04kg/m3 to 6.00E+03kg/m3, Mass density 1.00E+04kg/m3 to 7.00E+03kg/m3

DOI: 10.6041/j.issn.1000-1298.2022.05.037

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

33. Design and Experiment of Rotary Cutter Disc Type Flat Stubble Cutting Device for King Grass Harvester

Accession number: 20222212174630

Title of translation:

Authors: Huan, Xiaolong (1); You, Yong (1); Wang, Decheng (1); Li, Sibiao (1); Zhu, Lu (1); Liao, Yangyang (1)

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

Corresponding author: Wang, Decheng(wdc@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 112-124

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In view of lack of special mechanical harvesting equipment, a rotary cutter disc flat stubble cutting device of King grass harvester was designed. According to the biological characteristics of King grass and the harvest requirements of flat stubble cutting, the overall structure design of the cutting device was completed. Through theoretical analysis, the key structures and working parameters of cutter and conveyor were determined. ANSYS/LS-DYNA was used to simulate and compare the cutting effects of single moving knife cutting and moving fixed knife combination cutting. The results showed that the flatness of cutting section with moving and fixed cutter was better than that with single moving cutter. When the cutter head was cutting at low speed, the cutting power consumption of the combination of moving and fixed cutter was less than that of single moving cutter. The conveyor had good conveying effect and can realize the continuous stubble conveying of King grass stalk after cutting. The cutter test-bed was built. Through NSGA- algorithm, the optimal parameter combination of cutter was determined: the blade clearance was 2.98 mm, the cutter head speed was 84.7 r/min, and the cutter head inclination was 28.65¡ã. Under this parameter combination, the stubble breaking rate was 8.66% and the unit cutting power consumption was 7.78 mJ/mm2. On this basis, the field experiment was carried out, and the experimental results were basically consistent with the optimization results. The results showed that the overall harvest quality was better when the rotary cutter disc flat stubble cutting device was applied to the harvest of King grass. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 31

Main heading: Harvesters

Controlled terms: Conveyors? - ?Cutting? - ?Electric power utilization? - ?Harvesting

Uncontrolled terms: Cutter heads? - ?Cutting power? - ?Disc cutter? - ?Disk-type? - ?King grass harvester? - ?Mechanical? - ?Rotary cutters? - ?Rotary knife disk cutter? - ?Stubble cutting? - ?Tower-wheel conveyor

Classification code: 692.1 Conveyors? - ?706.1 Electric Power Systems? - ?821.1 Agricultural Machinery and Equipment? - ?821.3 Agricultural Methods

Numerical data indexing: Angular velocity 1.41449E+00rad/s, Energy 7.78E-03J, Percentage 8.66E+00%, Size 2.98E-03m

DOI: 10.6041/j.issn.1000-1298.2022.05.012

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

34. Pear Leaf Disease Spot Counting Method Based on GC-Cascade R-CNN

Accession number: 20222212174495

Title of translation: GC-Cascade R-CNN

Authors: Xue, Wei (1); Cheng, Runhua (1); Kang, Yalong (2); Huang, Xinzhong (3); Xu, Yangchun (2); Dong, Caixia (2)

Author affiliation: (1) College of Artificial Intelligence, Nanjing Agricultural University, Nanjing; 210095, China; (2) College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing; 210095, China; (3) Fruit Research Institute, Fujian Academy of Agriculture Sciences, Fuzhou; 350013, China

Corresponding author: Dong, Caixia(cxdong@njau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 237-245

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to improve the efficiency and accuracy of pear leaf disease degree diagnosis, a pear leaf disease spot counting method was proposed based on global context Cascade region-based convolutional neural network (GC-Cascade R-CNN). The backbone feature extraction network of the model was embedded in a global context feature model (GC-Model), to establish effective long-range dependency and channel dependency for enhancing the feature information. The model fused shallow detail features and deep rich semantic features by feature pyramid networks (FPN). ROI Align was used to replace ROI Pooling for regional feature aggregation and enhance the target feature representation. Bounding box regression and classification of target regions were performed by using multilayer Cascade networks to complete the disease spot counting task. In the test of pear leaf disease images, the mean average precision (mAP) of the model reached 89.4% for all types of disease spots, and a single image processing average time of 0.347 s, ensuring real-time operation while improving detection accuracy. The results showed that the model could effectively detect multiple types of disease spot targets from pear leaf disease images, especially for the detection of anthracnose spots; and the coefficient of determination R2 of the regression of disease spot counting values and true values of different kinds of pear leaf diseases were all greater than 0.92, indicating that the model had high accuracy of disease spot counting. This study solved the difficulty of pear leaves disease degree diagnosis, and provided a new idea for the diagnosis of pear disease conditions and symptoms in automated agricultural production. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 33

Main heading: Fruits

Controlled terms: Convolutional neural networks? - ?Diagnosis? - ?Feature extraction? - ?Image enhancement? - ?Multilayer neural networks? - ?Object detection? - ?Semantics

Uncontrolled terms: Attention mechanisms? - ?Cascade R-CNN? - ?Cascade regions? - ?Context features? - ?Disease spot counting? - ?Global context? - ?Global context feature? - ?Leaf disease? - ?Pear leaf? - ?Small object detection

Classification code: 461.6 Medicine and Pharmacology? - ?723.2 Data Processing and Image Processing? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 8.94E+01%, Time 3.47E-01s

DOI: 10.6041/j.issn.1000-1298.2022.05.024

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

35. Wavelet Packet Characterization of 3D Fluorescence Characteristic Information of Gas in Storage Room and Early Warning Method of Apple Spoilage

Accession number: 20222212173587

Title of translation: 3D

Authors: Yu, Huichun (1); Li, Ying (1); Yin, Yong (1); Yuan, Yunxia (1); Li, Jianmeng (1)

Author affiliation: (1) College of Food and Bioengineering, Henan University of Science and Technology, Luoyang; 471023, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 392-399

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to effectively characterize the three-dimensional (3D) fluorescence spectrum of gas in apple storage room, a feature information representation method based on wavelet packet decomposition coefficient was proposed. On this basis, the research on apple spoilage early warning methods was carried out. Firstly, the triangular interpolation method and Savitzky-Golar (SG) convolution smoothing were used to preprocess the spectrum data to eliminate the influence of Rayleigh scattering and ambient noise on the original fluorescence spectrum. After preprocessing, the 3D fluorescence data was converted into one-dimensional (1D) data vector, and the converted method was the corresponding emission spectrum, which was smoothly connected end to end according to the order of excitation wavelength, the 1D vector was decomposed by 3-layer sym4 wavelet packet, and the low-frequency coefficient set after the wavelet packet decomposing was extracted as fluorescence characteristic information. Secondly, partial least squares (PLS) was used to analyze the characteristic information and six physico-chemical indexes, and spectral clustering analysis (SCA) was adopted to determine the spoilage benchmark based on the results of PLS. Finally, a spoilage early warning model was constructed by using Mahalanobis distance (MD). The results showed that the fluorescence characteristic information represented method of wavelet packet decomposition coefficient was effective. With the increase of storage days, the Mahalanobis distance of the sample to the spoilage benchmark was gradually decreased, which better described the change trend of apple quality during storage, and it could realize the early warning of apple spoilage during storage. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 25

Main heading: Fruits

Controlled terms: Chemical analysis? - ?Cluster analysis? - ?Clustering algorithms? - ?Digital storage? - ?Emission spectroscopy? - ?Fluorescence? - ?Least squares approximations? - ?Spoilage? - ?Wavelet analysis? - ?Wavelet decomposition

Uncontrolled terms: 3d fluorescence characteristic information? - ?3d fluorescences? - ?Decomposition coefficient? - ?Early-warning method? - ?Fluorescence characteristics? - ?Mahalanobis distances? - ?Partial least-squares? - ?Spoilage warning? - ?Wavelet Packet? - ?Wavelet Packet Decomposition

Classification code: 461.9 Biology? - ?722.1 Data Storage, Equipment and Techniques? - ?723 Computer Software, Data Handling and Applications? - ?741.1 Light/Optics? - ?821.4 Agricultural Products? - ?903.1 Information Sources and Analysis? - ?921 Mathematics? - ?921.3 Mathematical Transformations? - ?921.6 Numerical Methods

DOI: 10.6041/j.issn.1000-1298.2022.05.042

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

36. Effect of Stearic Acid on Properties of Soy Protein Isolate/Sodium Alginate Films

Accession number: 20222212173543

Title of translation: /

Authors: Zhu, Xiuqing (1); Chen, Hua (1); He, Mingyu (1); Feng, Xumei (1); Li, Yang (1, 2); Teng, Fei (1)

Author affiliation: (1) College of Food Science, Northeast Agricultural University, Harbin; 150030, China; (2) Heilongjiang Green Food Science Research Institute, Harbin; 150028, China

Corresponding author: Teng, Fei(tengfei@neau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 406-412

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Soy protein isolate/sodium alginate composite films were prepared with stearic acid to improve the water resistance of soy protein isolate/sodium alginate composite films. Effects of different stearic acid additions (0, 2%, 4%, 6%, 8%, 10%) on composite films were evaluated by measuring mechanical properties, water resistance and microstructure of composite films. The results showed that with the 6% and 8% stearic acid addition, elongation at break and water vapor transmittance was significantly decreased, and water content and water solubility were also greatly affected compared with that of the composite film without stearic acid. When the adding amount was 8%, ternary composite films had the lowest water vapor permeability value ((2.95¡À0.49) g?mm/(m2?h?kPa)) and highest contact angle value (91.68¡ã¡À9.02¡ã). Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) analysis showed that soy protein isolate and sodium alginate formed the network structure through covalent crosslinking, and stearic acid was distributed in the gaps of the network structure. Therefore, when 8% stearic acid was added, the formation of a good network structure made the molecular structure of the composite films denser, and imparted smother surfaces and flatter cross-sections to the composite films, which can improve the water-resistance performance of the composite films. These results showed that the water resistance of soy protein isolate/sodium alginate composite films can be improved by using appropriate stearic acid effectively, which would have important implications in the development of biopolymer-based packaging materials with moisture barrier properties. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 38

Main heading: Stearic acid

Controlled terms: Composite films? - ?Contact angle? - ?Fourier transform infrared spectroscopy? - ?Packaging materials? - ?Proteins? - ?Scanning electron microscopy? - ?Sodium? - ?Sodium alginate? - ?Water vapor

Uncontrolled terms: Acid addition? - ?Alginate films? - ?Elongation-at-break? - ?Network structures? - ?Property? - ?Resistance to water? - ?Soy protein isolates? - ?Water microstructure? - ?Water vapour? - ?Water-resistances

Classification code: 549.1 Alkali Metals? - ?694.2 Packaging Materials? - ?801 Chemistry? - ?804.1 Organic Compounds? - ?931.2 Physical Properties of Gases, Liquids and Solids

Numerical data indexing: Percentage 1.00E+01%, Percentage 2.00E+00%, Percentage 4.00E+00%, Percentage 6.00E+00%, Percentage 8.00E+00%

DOI: 10.6041/j.issn.1000-1298.2022.05.044

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

37. Agricultural Short Text Matching Technology Based on Multi-semantic Features

Accession number: 20222212173863

Title of translation:

Authors: Jin, Ning (1, 2); Zhao, Chunjiang (3, 4); Wu, Huarui (3, 4); Miao, Yisheng (3, 4); Wang, Haichen (3, 5); Yang, Baozhu (3, 4)

Author affiliation: (1) School of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang; 110866, China; (2) Graduate School, Shenyang Jianzhu University, Shenyang; 110168, China; (3) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (4) Beijing Research Center for Information Technology in Agriculture, Beijing; 100097, China; (5) School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang; 110168, China

Corresponding authors: Zhao, Chunjiang(zhaocj@nercita.org.cn); Zhao, Chunjiang(zhaocj@nercita.org.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 325-331

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: With the development of information technology, agricultural information consultant service based on mobile Internet has become an important part of agro-technical extension system. More than ten million questions in all have been collected by agro-technical extension Q&A community. With the continuous popularization of Q&A community, answering questions manually only by agricultural experts and technicians can neither follow the rapid growth of the questions nor meet the needs of farmers who want to be answered quickly and accurately. Agricultural intelligent Q&A is one of the effective ways to solve the problem. High quality text matching for new questions is the key technology. The accuracy of text matching is limited by the characteristics of agricultural text, such as large amount of data, poor standardization, wide range, much noise, and sparse features. In order to improve the accuracy, the deep semantics, word co-occurrence and maximum matching degree of agricultural short text were extracted and Co_BiLSTM_CNN model composed of bi-long short-term memory, convolutional neural networks, dense networks and Siamese network of shared parameters, was proposed to extract multi-semantic features. The precision, recall, F1, accuracy and time complexity were selected as evaluation indexes to comprehensively measure the performance of the model. The experimental results showed that the model could extract text features more comprehensively, with an accuracy of 94.15%. Compared with the other six text matching models, the experimental results showed obvious advantages. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 37

Main heading: Long short-term memory

Controlled terms: Agriculture? - ?Brain? - ?Convolution? - ?Convolutional neural networks? - ?Semantic Web? - ?Semantics

Uncontrolled terms: Agricultural short text matching? - ?Bi-long short-term memory network? - ?Convolutional neural network? - ?Matching technology? - ?Memory network? - ?Multi-semantic feature? - ?Semantic features? - ?Short texts? - ?Text-matching? - ?Word co-occurrence

Classification code: 461.1 Biomedical Engineering? - ?716.1 Information Theory and Signal Processing? - ?723 Computer Software, Data Handling and Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?903 Information Science

Numerical data indexing: Percentage 9.415E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.034

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

38. Design of 1-DOF Non-circular Gear Five Bar Finger Mechanism with Three Finger Joint Position and Pose Constraints

Accession number: 20222212173589

Title of translation:

Authors: Ye, Jun (1); Chen, Jianneng (2); Yu, Chennan (2); Shen, Shanshan (1); Xue, Mingrui (1); Ye, Zhichao (1)

Author affiliation: (1) School of Mechanical and Electrical Engineering, Zhejiang Industry Polytechnic College, Shaoxing; 312000, China; (2) Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou; 310018, China

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 430-437

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to overcome the shortcomings of traditional multi bar finger mechanism and meet more requirements of bionic finger at the same time, a design method of one degree of freedom non-circular gear five bar finger mechanism with position and pose points constraints of finger three joints was proposed. According to the actual size and motion position and pose of the finger, constraints of n position and pose points were established. The kinematic mapping theory and matrix singular value decomposition method were used to solve the hinge point curve meeting the requirements of the given constraints. According to the angular relationship between the two driving input rods, a non-circular gear pair meeting the requirements of position and pose points was designed, and the IO equation of one degree of freedom non-circular gear five bar finger mechanism was further deduced. On this basis, taking the five position and pose points constraint of three finger joint as an example, according to the other constraints of rod length, error, selection range of hinge points and non-circular gear transmission, the feasible curve solution domain was established. Finally, a one degree of freedom non-circular gear five bar finger mechanism parameters meeting all conditions was obtained, a finger mechanism prototype was developed and relevant tests were carried out. The experimental prototype showed that the design method proposed was correct and effective. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 20

Main heading: Degrees of freedom (mechanics)

Controlled terms: Design? - ?Kinematics? - ?Mapping? - ?Singular value decomposition

Uncontrolled terms: Actual sizes? - ?Design method? - ?Finger joints? - ?Finger mechanisms? - ?Hinge point? - ?IO equation? - ?Kinematic mapping? - ?Non-circular gear five bar finger mechanism? - ?Non-circular gears? - ?Pose constraints

Classification code: 405.3 Surveying? - ?921 Mathematics? - ?931.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2022.05.047

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

39. Fast Recognition of Tomato Fruit in Greenhouse at Night Based on Improved YOLO v5

Accession number: 20222212173753

Title of translation: YOLO v5

Authors: He, Bin (1, 2); Zhang, Yibo (1); Gong, Jianlin (1); Fu, Guo (1, 2); Zhao, Yuquan (1); Wu, Ruoding (1)

Author affiliation: (1) College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling; 712100, China; (2) Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling; 712100, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 201-208

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to realize the normal operation of the picking robot and the rapid recognition of tomato in the nighttime environment of solar greenhouse, a nighttime tomato fruit detection method based on improved YOLO v5(You only look once)was proposed. Totally 2000 tomato images in the night environment were collected as the initial training samples, and the original loss function was improved by establishing a CIOU target position loss function based on intersection and union ratio, and then an adaptive anchor frame was generated according to the anchor calculation function, the optimal anchor frame size was determined, the network structure was optimized, and an improved YOLO v5 network model was constructed, and the recognition rate of tomato fruit in night environment was improved. The experimental results showed that the average recognition accuracy of improved YOLO v5 network model for tomato green and red fruits and average recognition accuracy in night environment was 96.2%, 97.6% and 96.8%. Compared with traditional CNN convolution network model and traditional YOLO v5 model, the recognition accuracy of occluded features and features in dark light was improved and the robustness of the model was improved. The improved YOLO v5 network model compiled and wrote the training results into Android system to make a rapid detection application software, which verified the reliability and accuracy of the model for tomato fruit recognition in night environment, and provided a reference for the relevant research of tomato real-time detection system. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 22

Main heading: Greenhouses

Controlled terms: Application programs? - ?Fruits? - ?Image enhancement? - ?Software reliability

Uncontrolled terms: Fast recognition? - ?Improved YOLO v5? - ?Loss functions? - ?Network models? - ?Night? - ?Normal operations? - ?Picking robot? - ?Recognition? - ?Recognition accuracy? - ?Tomato fruits

Classification code: 723 Computer Software, Data Handling and Applications? - ?821.4 Agricultural Products? - ?821.6 Farm Buildings and Other Structures

Numerical data indexing: Percentage 9.62E+01%, Percentage 9.68E+01%, Percentage 9.76E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.020

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

40. Field Boundary Distance Detection Method in Early Stage of Planting Based on Binocular Vision

Accession number: 20222212173738

Title of translation:

Authors: Hong, Zijia (1); Li, Yanming (1); Lin, Hongzhen (1, 2); Gong, Liang (1); Liu, Chengliang (1, 2)

Author affiliation: (1) School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai; 200240, China; (2) State Key Laboratory of Mechanical System and Vibration, Shanghai; 200240, China

Corresponding author: Li, Yanming(ymli@sjtu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 27-33 and 56

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the limitations of the current agricultural machinery automatic driving headland turning method based on global navigation satellite system technology, a binocular vision-based identification and ranging method of farmland ridge boundary was proposed, and the feasibility, applicability and constraints of the specific method were analyzed. In view of the farmland environment with large illumination changes and many repeated textures, Census transform and truncated gradient were integrated to calculate the cost of stereo matching, and cross-scale cost merging algorithm based on segment-tree was used in the cost aggregation step, which can quickly get a good parallax diagram. After constructing a three-dimensional point cloud from a parallax diagram, in view of the actual situation of uneven farmland ground and uneven crop growth height, the adaptive threshold point cloud extraction and interference elimination were carried out, so as to realize the recognition of field ridge boundary. In addition, according to the farmland information, the calculated average boundary distance was corrected. The experimental results showed that this algorithm can realize the boundary distance detection of the early working farmland, and the recognition rate of the algorithm can reach 99% for the ridge of 5~10 m in front of the field of view. The ranging accuracy was increased with the decrease of the detection distance, and the ranging error at 5 m was about 0.075 m. On NVIDIA Jetson TX2 hardware platform, the running time of the algorithm was about 0.8 s, which can meet the real-time requirements of the operation for the agricultural machinery with a driving speed less than 1.5 m/s. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 24

Main heading: Farms

Controlled terms: Automobile drivers? - ?Binocular vision? - ?Forestry? - ?Geometrical optics? - ?Stereo image processing? - ?Stereo vision? - ?Textures? - ?Trees (mathematics)

Uncontrolled terms: ¡¯current? - ?3D point cloud? - ?Automatic driving? - ?Detection methods? - ?Distances detections? - ?Field boundaries? - ?Global Navigation Satellite Systems? - ?Paddy ridge? - ?Plantings? - ?Stereo-matching

Classification code: 432 Highway Transportation? - ?723.2 Data Processing and Image Processing? - ?723.5 Computer Applications? - ?741.1 Light/Optics? - ?741.2 Vision? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.0 Woodlands and Forestry? - ?912.4 Personnel? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory

Numerical data indexing: Percentage 9.90E+01%, Size 5.00E+00m to 1.00E+01m, Size 5.00E+00m, Size 7.50E-02m, Time 8.00E-01s, Velocity 1.50E+00m/s

DOI: 10.6041/j.issn.1000-1298.2022.05.003

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

41. Type Synthesis of Redundant Parallel Mechanism with Actuation Fault Tolerance

Accession number: 20222212174484

Title of translation:

Authors: Shan, Yanxia (1, 2); Su, Kaixing (1, 3); Gao, Xueyuan (1, 3); Li, Shihua (1, 3)

Author affiliation: (1) School of Mechanical Engineering, Yanshan University, Qinhuangdao; 066004, China; (2) School of Liren, Yanshan University, Qinhuangdao; 066004, China; (3) Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao; 066004, China

Corresponding authors: Li, Shihua(shli@ysu.edu.cn); Li, Shihua(shli@ysu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 422-429

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The control methods are mostly used for the fault tolerance of parallel mechanism at present. However, there are few studies on structure design of parallel mechanism with actuation fault tolerance. To quantitatively analyze the influence of driving force invalidity on the operability performance of mechanism, an operability invalidity index was proposed for evaluating the driving force invalidity of the branches of the parallel mechanism based on the Jacobian matrix. The driving identity condition of the redundant parallel mechanism stated as ¡°the driving force screw of the redundant parallel mechanism was expressed in the same form in a fixed coordinate system, and the linear independent number of the driving space was equal to the degree of freedom. If any driving force screw (driving force invalidity fault) was removed, the driving space would not degrade¡±, that satisfied the driving force invalidity tolerance was given. Based on the screw theory and guided by the driving identity condition, which promised that the driving force screws can be mutually substituted, a type synthesis method of redundant parallel mechanism was proposed, and a 3R DOF type of redundant parallel mechanisms with actuation fault tolerance was synthesized. The actuation fault tolerance of the (4-RRR) redundant parallel mechanism synthesized was evaluated by using the proposed operability invalidity index, which verified that the synthesized mechanism had the drive force invalidity tolerance. The research result can provide a way to solve the driving force invalidity of parallel mechanism, and can enrich the types of parallel mechanism, which provided a theoretical basis for the application and development of redundant parallel mechanism with actuation fault tolerance. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 20

Main heading: Fault tolerance

Controlled terms: Degrees of freedom (mechanics)? - ?Jacobian matrices? - ?Mechanisms? - ?Screws

Uncontrolled terms: Actuation fault tolerance? - ?Control methods? - ?Driving force invalidity? - ?Driving forces? - ?Identity conditions? - ?Parallel mechanisms? - ?Redundant parallel mechanism? - ?Redundant parallels? - ?Synthesised? - ?Type synthesis

Classification code: 601.3 Mechanisms? - ?605 Small Tools and Hardware? - ?921.1 Algebra? - ?931.1 Mechanics

DOI: 10.6041/j.issn.1000-1298.2022.05.046

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

42. Color Stability and Mitochondrial MMb Reducing Ability of Gannan Tibetan Sheep Meat by Freezing Point Storage

Accession number: 20222212173580

Title of translation: MMb

Authors: Shi, Xixiong (1); Zhang, Pan¡¯gao (1); Zhao, Ruina (1); Bao, Xiaoming (1); Fan, Xiaoning (1)

Author affiliation: (1) Department of Food Science and Engineering, Gansu Agricultural University, Lanzhou; 730070, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 400-405

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to clarify the effect of controlled freezing point storage on color stability and mitochondria metmyoglobin reduction ability of Tibetan sheep meat, the hind legs meat of Tibetan sheep were used as the material, and Tibetan sheep meat was controlled by freezing point storage and cold storage, and the duration of storage for 0 d, 1 d, 3 d, 5 d, 7 d and 9 d. The changes in MRA, NADH content, SDH activity, mitochondrial membrane permeability, mitochondrial membrane potential, Hue angle duration of storage were determined. The results showed that after aging of 9 d, controlled freezing point storage group MRA, NADH content, mitochondrial membrane permeability, mitochondrial membrane potential, SDH activity were significantly 16.67%, 33.16%, 25.45%, 16.57% and 40.45% higher than that of the cold storage group (P ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 28

Main heading: Mitochondria

Controlled terms: Cold storage? - ?Color? - ?Food storage? - ?Freezing? - ?Meats? - ?Stability

Uncontrolled terms: % reductions? - ?Color stability? - ?Freezing point? - ?Freezing point storage? - ?Metmyoglobin? - ?Metmyoglobin-reduction ability? - ?SDH activities? - ?Storage groups? - ?Tibetan sheep meat? - ?Tibetans

Classification code: 461.2 Biological Materials and Tissue Engineering? - ?644.3 Refrigeration Equipment and Components? - ?694.4 Storage? - ?741.1 Light/Optics? - ?822.1 Food Products Plants and Equipment? - ?822.3 Food Products

Numerical data indexing: Percentage 1.313E+01%, Percentage 1.657E+01%, Percentage 1.667E+01%, Percentage 2.545E+01%, Percentage 3.316E+01%, Percentage 4.045E+01%, Size 5.40E-07m

DOI: 10.6041/j.issn.1000-1298.2022.05.043

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

43. Design and Experimental Optimization of Hand-held Manipulator for Picking Famous Tea Shoot

Accession number: 20222212174440

Title of translation:

Authors: Jia, Jiangming (1, 2); Ye, Yuze (1); Cheng, Peilin (1); Zhu, Yingpeng (1); Fu, Xiaping (1); Chen, Jianneng (1, 2)

Corresponding authors: Chen, Jianneng(Jiannengchen@zstu.edu.cn); Chen, Jianneng(Jiannengchen@zstu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 86-92

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the difficulty of mechanical picking of famous tea, a hand-held famous tea shoot picking manipulator was designed based on the analysis of the agronomic requirements of tea picking and manual picking movements. The kinematic model of the picking manipulator was used to obtain the parameter range of magnet distance, active finger angular velocity and active finger turning angle, which were factors affecting the picking efficiency. The Box-Behnken response surface analysis method was used to investigate the interactive effect of the influencing factors on the picking success rate. A quadratic regression model was established with the picking success rate as the response value. The significance ranking of the influencing factors on the picking success rate was active finger angular velocity, magnet distance and active finger angle. The optimization module of Design-Expert 11.0 software was used to optimize the factors with the maximum picking success rate as the optimization objective, and the optimization results were obtained as follows: magnet distance was 40.04 mm, active finger rotation angle was 153.0¡ã and active finger angular velocity was 3.38 rad/s. The picking experiment of famous tea was carried out with the optimized parameters, and the results showed that the picking success rate was 74.3%, the average speed of three picking was 25.2 pieces/min, the relative error between the test value and the predicted value was less than 5%, and the optimized model results were reliable. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 22

Main heading: Kinematics

Controlled terms: Angular velocity? - ?Magnets? - ?Manipulators? - ?Regression analysis? - ?Surface analysis

Uncontrolled terms: Design optimization? - ?Experimental optimization? - ?Famous tea? - ?Kinematics models? - ?Mechanical? - ?Optimisations? - ?Parameter range? - ?Picking manipulators? - ?Picking success rate? - ?Response surface

Classification code: 922.2 Mathematical Statistics? - ?931.1 Mechanics? - ?951 Materials Science

Numerical data indexing: Angular velocity 3.38E+00rad/s, Percentage 5.00E+00%, Percentage 7.43E+01%, Size 4.004E-02m

DOI: 10.6041/j.issn.1000-1298.2022.05.009

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

44. Review of Semantic Analysis Techniques of Agricultural Texts

Accession number: 20222212173556

Title of translation:

Authors: Wu, Huarui (1, 2); Guo, Wei (2, 3); Deng, Ying (1, 3); Wang, Haoriqin (1); Han, Xiao (4); Huang, Sufang (5)

Author affiliation: (1) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (2) Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (3) Key Laboratory of Digital Village Technology, Ministry of Agriculture and Rural Affairs, Beijing; 100097, China; (4) Beijing Research Center of Intelligent Equipment Technology for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (5) Cangzhou Academy of Agricultural and Forestry Sciences, Cangzhou; 061001, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 1-16

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: With the development of Internet and artificial intelligence technology, agricultural knowledge intelligent services have gradually assumed the role of providing effective technical guidance for agricultural production management, especially during the epidemic. The key technologies and applications in the semantic understanding of agricultural knowledge service texts were reviewed. Firstly, its progress in agriculture was introduced according to the semantic processing methods based on rules, machine learning and deep learning in natural language processing. Then, the semantic analysis method for the characteristics of agricultural knowledge was introduced, covering the storage, expression and calculation of the main process of agricultural text analysis, including knowledge extraction, knowledge fusion, knowledge representation and knowledge inference of agricultural knowledge graph. The representation model of agricultural text such as TF-IDF, Word2Vec and BERT and classification models such as CNN, RNN and Attention were presented. Then the common corpus was described. The application of semantic understanding in agriculture from the aspects of agricultural intelligent question answering, agricultural semantic retrieval and agricultural intelligent management decision as well were introduced. Finally, the research trend of agricultural text semantic understanding was prospected from the aspects of standardization construction of agricultural corpus, complexity of semantic understanding model, multi-modal semantic processing, multi-region and multi-language semantic understanding. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 106

Main heading: Natural language processing systems

Controlled terms: Agriculture? - ?Deep learning? - ?Knowledge graph? - ?Processing? - ?Semantics? - ?Text processing

Uncontrolled terms: Agricultral text? - ?Agricultural knowledge intelligent service? - ?Analysis techniques? - ?Artificial intelligence technologies? - ?Deep learning? - ?Intelligent Services? - ?Semantic analysis? - ?Semantic processing? - ?Semantics understanding? - ?Technical guidances

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?723.2 Data Processing and Image Processing? - ?723.4 Artificial Intelligence? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?903.1 Information Sources and Analysis? - ?903.3 Information Retrieval and Use? - ?913.4 Manufacturing

DOI: 10.6041/j.issn.1000-1298.2022.05.001

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

45. Recognition Method of Pig Cough Based on Deep Neural Network

Accession number: 20222212174437

Title of translation:

Authors: Shen, Mingxia (1, 2); Wang, Mengyu (1, 2); Liu, Longshen (1, 2); Chen, Jia (1, 2); Tai, Meng (1, 2); Zhang, Wei (1, 2)

Author affiliation: (1) College of Engineering, Nanjing Agricultural University, Nanjing; 210031, China; (2) Jiangsu Smart Animal Husbandry Equipment Technology Innovation Center, Nanjing; 210031, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 257-266

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Respiratory diseases of pigs are easily contagious, which affects pig breeding efficiency. Cough is one of the obvious symptoms of respiratory diseases. An algorithm based on deep neural network was proposed to accurately identify pig coughs. Log_filter bank (logFBank) and Mel frequency cepstral coefficents (MFCC) were extracted respectively after spectral subtraction denoising and double threshold endpoint detection of the sound signal. Then the two kinds of extracted features and their first and second order differences were used as inputs to the convolutional neural networks (CNNs) and the deep feed forward sequence memory neural networks (DFSMN) for multi-classification training. The effects of the different features and different iteration times on the effectiveness of the model were compared. Except the accuracy of cough recognition, the recognition effects of other pig sounds, such as sneezing, which was easily confused with cough were also analyzed. The experimental resulst showed that when the number of training rounds reached 200, the CNNs model with MFCC as feature had a good effect. The recognition precision of cough on test set was 97%, the cough recognition recall rate was 96%, the F1-score was 98%, and accuracy reached 96.71%. It was showed that the model was effective and feasible, and can provide technical support for pig cough recognition in pig welfare breeding. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 23

Main heading: Deep neural networks

Controlled terms: Convolutional neural networks? - ?Feedforward neural networks? - ?Iterative methods? - ?Mammals? - ?Pulmonary diseases

Uncontrolled terms: Cepstral? - ?Convolutional neural network? - ?Cough recognition? - ?Filters bank? - ?LoG filter? - ?Log_filter bank? - ?Meishan pig? - ?Mel frequencies? - ?Mel frequency cepstral coefficent? - ?Recognition methods

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?461.6 Medicine and Pharmacology? - ?921.6 Numerical Methods

Numerical data indexing: Percentage 9.60E+01%, Percentage 9.671E+01%, Percentage 9.70E+01%, Percentage 9.80E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.026

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

46. Consortium Blockchain Inter-organizational Contract Transaction Mechanism for Kiwi Fruit Quality Traceability

Accession number: 20222212174427

Title of translation:

Authors: Jing, Xu (1); Qin, Yuanze (1)

Author affiliation: (1) College of Information Engineering, Northwest A&F University, Yangling; 712100, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 282-290

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To solve the problem caused by the ignorance of organization-compositional diversity in blockchain-based kiw fruit traceability system, a consortium blockchain inter-organizational contract transaction mechanism for kiwi fruit quality traceability was proposed. Through two link confirmations on the blockchain, the process of signing and confirming the terms of the contract in the actual transaction was transferred to the consortium blockchain, so as to realize the cross-organization incontestable transaction. The consortium blockchain was chosen to construct the blockchain network for kiwi fruit industry chain traceability system, the smart contract technology was used to make the information of the kiwi fruit production process valuable, and the Hash value was used to light the on-blockchain stress. The transaction contract number was used to realize the association of the trace data, responsible person and responsible enterprise. Result of test analysis showed that each piece of data on the blockchain was about 102 ms. The time of one complete traceability was extended by about 7.11 ms. When on-blockchain contract transaction was increased. The research ensured the data continuity and traceability of multi-organization tracing, which was of great significance to improve the quality and safety of agricultural products. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 26

Main heading: Blockchain

Controlled terms: Distributed ledger? - ?Fruits

Uncontrolled terms: Block-chain? - ?Consortium blockchain? - ?Fruit quality? - ?Hyperledg fabric? - ?Inter-organizational? - ?Kiwifruits? - ?On-blockchain contract transaction? - ?Quality traceabilitys? - ?Transaction mechanism

Classification code: 723.3 Database Systems? - ?821.4 Agricultural Products

Numerical data indexing: Time 1.02E-01s, Time 7.11E-03s

DOI: 10.6041/j.issn.1000-1298.2022.05.029

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

47. Diseased Shrimp Identification Method Based on Adaptive Convolutional Neural Networks

Accession number: 20222212173568

Title of translation:

Authors: Liu, Zihao (1); Zhang, Sulan (1); Jia, Xiaojun (1); Yang, Jun (1); Zhang, Wen (2); Xu, Zhiling (3)

Author affiliation: (1) College of Mathematics Physics and Information Engineering, Jiaxing University, Jiaxing; 314001, China; (2) School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang; 621010, China; (3) College of Quality and Safty Engineering, China Jiliang University, Hangzhou; 310018, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 246-256

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To solve the problem of weak generalization caused by diversity of source of shrimp samples, a novel shrimp features difference model based on shannon information theory was proposed. The model was actually a recognition framework, calculating hyper-parameters based on deep convolutional neural network (DCNN) using entropy reduction rule with multi-source datasets. This rule can clear up the special information entropy from the random input to regular output, breaking the data types changing from three dimensional input to one-dimensional output, realizing dimensionality reduction of shrimp image reducing from high dimension space to low dimensional space. Thus, the DCNN adaptive optimization strategies can be acquired to improve the generlization effectiveness of recognizing diseased shrimp from multiple sources. The experimental results showed that the proposed method in a single dataset can achieve highest accuracy of 97.96%. The generalization experiment was also tested through other four shrimp image datasets, and the generalization precision falling scope was no more than 5 percentage points. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 27

Main heading: Deep neural networks

Controlled terms: Convolution? - ?Convolutional neural networks? - ?Information theory

Uncontrolled terms: Convolutional neural network? - ?Difference models? - ?Diseased shrimp? - ?Feature differences? - ?Generalisation? - ?Generalization accuracy? - ?Identification method? - ?Image entropy? - ?Model-based OPC? - ?Shannon¡¯s Information Theory

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?716.1 Information Theory and Signal Processing

Numerical data indexing: Percentage 9.796E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.025

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

48. Design and Optimization Tests of Reverse Spin-throwing Cyperus edulis Starting Device

Accession number: 20222212173833

Title of translation:

Authors: He, Xiaoning (1, 2); Zhang, Xuejun (1); Zhao, Zhuang (2); Shang, Shuqi (2); Wang, Dongwei (2); Yang, Shuai (2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao; 266109, China

Corresponding author: Zhang, Xuejun(zhxjau@sina.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 34-43

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of high leakage rate, easy congestion and difficult soil fragmentation in the root system, which lead to difficulties in subsequent sorting and separation and low efficiency of combined harvesting. The discrete element simulation method was applied to establish the root-tuber-soil discrete element model of Cyperus edulis, the mechanism of the interaction between root-tuber-soil of Cyperus edulis on the fragmentation of the root-soil annulus of Cyperus edulis was analyzed, and a reverse spin-throw type starting device was designed. The results showed that the optimum combination of parameters for the reverse rotary tiller was as follows: phase angle of 61¡ã, installation spacing of 150 mm, soil fragmentation rate of 94.10%, buried fruit rate of 1.39%, under the same parameter settings with ordinary rotary tiller combination for field verification test, the results showed that buried fruit rate was reduced by 13.33%, soil fragmentation rate was increased by 3.15%, which met the technical requirements of Chinese Cyperus edulis mechanized harvesting standards, the research results can provide a theoretical reference basis for further improvement of Cyperus edulis harvesting equipment development. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 24

Main heading: Soils

Controlled terms: Fruits? - ?Harvesting

Uncontrolled terms: Cyperus eduli? - ?Design and optimization? - ?Discrete element models? - ?Discrete-element simulations? - ?Element simulation method? - ?Leakage rates? - ?Root system? - ?Root tubers? - ?Rotary tiller? - ?Starting device

Classification code: 483.1 Soils and Soil Mechanics? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 1.333E+01%, Percentage 1.39E+00%, Percentage 3.15E+00%, Percentage 9.41E+01%, Size 1.50E-01m

DOI: 10.6041/j.issn.1000-1298.2022.05.004

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

49. Sheep Face Recognition Method Based on Improved MobileFaceNet

Accession number: 20222212173741

Title of translation: MobileFaceNet

Authors: Zhang, Hongming (1); Zhou, Lixiang (1); Li, Yongheng (1); Hao, Jinye (1); Sun, Yang (1); Li, Shuqin (1)

Author affiliation: (1) College of Information Engineering, Northwest A&F University, Yangling; 712100, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 53

Issue: 5

Issue date: May 25, 2022

Publication year: 2022

Pages: 267-274

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The difference between sheep is small, the similarity is high, it is difficult to distinguish, and the accuracy of long-distance recognition is not high. To solve that, a sheep face recognition model with efficient channel attention mechanism integrating spatial information was proposed to recognize sheep non-contact. The model was based on MobileFaceNet network. The research generated sheep face detector based on YOLO v4 target detection method was used to construct sheep face recognition database. An efficient channel attention integrating spatial information was introduced into the deep convolution layer and residual layer of MobileFaceNet to increase the extraction range of trunk features and improve the recognition rate. Cosine annealing was used to optimize the dynamic learning rate, and finally ECCSA-MFC model was built to realize sheep individual recognition. The experimental results showed that the accuracy of the sheep face detection model based on YOLO v4 can reach 97.91% and can be used as a face detector. In sheep face recognition, the recognition rate of ECCSA-MFC algorithm can reach 88.06% in open set verification and 96.73% in closedset verification. The proposed ECCSA-MFC model had higher recognition rate and lighter weight. The model size was only 4.8MB, which can provide a solution for intelligent breeding in sheep farm. ? 2022, Chinese Society of Agricultural Machinery. All right reserved.

Number of references: 30

Main heading: Face recognition

Controlled terms: Agriculture

Uncontrolled terms: Attention mechanisms? - ?ECCSA-MFC? - ?Efficient channels? - ?Face detector? - ?Face recognition methods? - ?Mobilefacenet? - ?Recognition models? - ?Sheep face recognition? - ?Spatial informations? - ?YOLO v4

Classification code: 821 Agricultural Equipment and Methods; Vegetation and Pest Control

Numerical data indexing: Percentage 8.806E+01%, Percentage 9.673E+01%, Percentage 9.791E+01%

DOI: 10.6041/j.issn.1000-1298.2022.05.027

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village