农业机械学报

2024年第1期共收录43篇

1. Hierarchical Multi-label Classification of Agricultural Pest and Disease Interrogative Questions

Accession number: 20240915634821

Title of translation: 基于层级多标签的农业病虫害问句分类方法

Authors: Wei, Tingting (1); Ge, Xiaoyue (1); Xiong, Juntao (1)

Author affiliation: (1) College of Matheinatical Sciences and Information, South China Agricultural University, Guangzhou; 510642, China

Corresponding author: Xiong, Juntao(xiongjt2340@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 263-269

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: With the rapid advancement of infonnation technology, it has become a trend for fanners to address offline agricultural issues through online intelligent question-and-answer systems. Question classification plays a crucial role in question-and-answer systems, as its accuracy directly determines the correctness of the final answers. Traditional single-label text classification models often struggle to accurately capture the precise intent of agricultural queries. Moreover, the lack of large-scale publicly available query datasets about agricultural pest and disease poses a significant challenge to existing research methods. To address these challenges, a hierarchical classification framework for queries about agricultural pest and disease was established based on a tree-like structure. This framework progressively refined the classification from the ambiguity of queries towards precision, aiming to overcome the semantic complexity of agricultural queries. Additionally, adversarial training method was introduced. By constructing adversarial samples and incorporating them into the training of large-scale language models, the model’s generalization capabilities were enhanced, while mitigating issues arising from limited training data. Experimental validation conducted on real question-and-answer corpora demonstrated that the proposed method significantly enhanced the classification performance of queries about agricultural pest and disease. The research result can provide an effective means of identifying the intent behind agricultural queues, thereby offering support for advancing agricultural informatization. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 19

Main heading: Semantics

Controlled terms: Agriculture? - ?Classification (of information)? - ?Computational linguistics? - ?Informatization? - ?Large datasets? - ?Online systems? - ?Query processing? - ?Text processing

Uncontrolled terms: Adversarial training? - ?Agricultural pest and disease? - ?Agricultural pests? - ?Hierarchical multi-label classifications? - ?Language model? - ?Large-scales? - ?Offline? - ?Query classification? - ?Question and answer system? - ?Question classification

Classification code: 716.1 Information Theory and Signal Processing? - ?721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory? - ?722.4 Digital Computers and Systems? - ?723.2 Data Processing and Image Processing? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?903.1 Information Sources and Analysis? - ?903.3 Information Retrieval and Use

DOI: 10.6041/j.issn.1000-1298.2024.01.025

Funding Details: Number: 20YJC740067,72101091, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 广州市基础与应用基础研究项目(202201010184), 国家自然科学基金项目(72101091)和教育部人文社会科学研究一般项目 (20YJC740067)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

2. Lightweight Identification of Rice Diseases Based on Improved ECA and MobileNetV3Small

Accession number: 20240915637096

Title of translation: 基于MobileNetV3SmaU - ECA的水稻病害轻量级识别研究

Authors: Yuan, Peisen (1); Ouyang, Liujiang (1); Zhai, Zhaoyu (1); Tian, Yongchao (1, 2)

Author affiliation: (1) College of Artificial Intelligence, Nanjing Agricultural University, Nanjing; 210095, China; (2) College of Agriculture, Nanjing Agricultural University, Nanjing; 210095, China

Corresponding author: Tian, Yongchao(yctian@njau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 253-262

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to realize the lightweight identification and detection of rice diseases, the ECA attention mechanism was used to improve the MobileNetV3Small model, and shared parameter transfer learning was used to carry out intelligent lightweight identification and detection of rice diseases. Pre-training was perfolined on the PlantVillage dataset, and the shared parameters obtained from the pretraining were transferred to the rice disease recognition model for fine-tuning and optimization. Experiments were on the open-source rice disease dataset. The experimental results showed that the recognition accuracy rate reached 97. 47% under non-transfer learning, and 99.92% under transfer learning, while reducing the number of parameters by 26. 69%. Secondly, the Grad — CAM was used for visualization. Compared with other attention mechanisms CB AM and SENET, the results generated by the ECA module were more consistent with the position and color of the disease spots in the image, indicating that the network can better focus on rice diseases. Characteristics, and the causes of misclassification were analyzed through visualization and each rice disease. The proposed method realized the lightweight of the rice disease recognition model, so that it can be deployed in resource-constrained scenarios such as mobile devices, and achieved the purpose of fast, efficient and portable. At the same time, an Android-based rice disease identification system was developed, which can facilitate the identification and analysis of rice diseases at the edge. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Visualization

Controlled terms: Transfer learning

Uncontrolled terms: Attention mechanisms? - ?ECA attention mechanism? - ?Fine tuning? - ?Mobile deployment? - ?Mohilenetv3small? - ?Parameter transfers? - ?Pre-training? - ?Recognition models? - ?Rice disease identification? - ?Transfer learning

Classification code: 723.4 Artificial Intelligence

Numerical data indexing: Percentage 4.70E+01%, Percentage 6.90E+01%, Percentage 9.992E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.024

Funding text: 国家自然科学基金项目 (61502236)和江苏省农业科技冃主创新资金项目 (CX(21)3059)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

3. Analysis of Formation of Benzenoids Volatile Compounds of Japanese Apricot Fruit

Accession number: 20240915642670

Title of translation: 青梅果实芳香族特征香气的形成分析

Authors: Hao, Yadong (1); Liu, Minxin (2); Li, Jingming (3, 4)

Author affiliation: (1) Beijing Haidian District Food and Drug Safety Monitoring Center, Beijing; 100094, China; (2) Luzhou Laojiao Co., Ltd., Luzhou; 646699, China; (3) College of Food Science and Nutritional Engineering, China Agricultural University, Beijing; 100083, China; (4) CAU - SCCSD Advanced Agricultural and Industrial Institute, Chengdu; 611430, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 379-385

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Benzenoids volatile compounds significantly contribute to the distinctive aroma of both Japanese apricot fruit and its processed products. However, the accumulation pattern and formation mechanism of such characteristic aroma have not been sufficiently studied. In order to investigate the formation and accumulation of the characteristic aroma substances in Japanese apricot fruit and their origin mechanisms, Japanese apricot fruit at different ripening stages were analyzed by headspace - solid - phase microextraction - gas chromatography - mass spectrometry (HS - SPME - GC - MS), and correlation analysis was performed by combining specific amino acids and other precursors. The results showed that the aroma characteristics varied significantly during the ripening process, and the metabolism of aroma substances was the most active and the amino acid content was the lowest in the middle stage of ripening (80 ~ 100 d after flowering). The changes in the accumulation of characteristic aroma substances in Japanese apricot fruit indicated that the aromatic aroma substances originated from the phenylalanine metabolic pathway, and there was a competitive relationship between the benzaldehyde and phenylacetaldehyde synthesis pathways. Benzaldehyde was formed through the non-(3 oxidation pathway. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Amino acids

Controlled terms: Fruits? - ?Gas chromatography? - ?Mass spectrometry? - ?Metabolism? - ?Odors? - ?Volatile organic compounds

Uncontrolled terms: Amino-acids? - ?Apricot fruits? - ?Aroma precursor? - ?Aroma substances? - ?Benzenoid volatile compound? - ?Characteristic aroma? - ?Japanese apricot fruit? - ?Japanese apricots? - ?Processed products? - ?Volatile compounds

Classification code: 801 Chemistry? - ?802.3 Chemical Operations? - ?804.1 Organic Compounds? - ?821.4 Agricultural Products

DOI: 10.6041/j.issn.1000-1298.2024.01.036

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

4. Single Wood Extraction Method Combining LiDAR Data and Spectral Images

Accession number: 20240915637095

Title of translation: 基于LiDAR数据与光谱影像融合的单木提取方法

Authors: Meng, Xiaoqian (1); Li, Junlei (1); Hu, Wei (1); Tian, Maojie (1); Ma, Chuntian (1); Wang, Ruirui (2)

Author affiliation: (1) State Grid Power Space Technology Co., Ltd., Beijing; 102209, China; (2) College of Forestry, Beijing Forestry University, Beijing; 100083, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 203-211 and 262

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Existing airborne data single-tree segmentation methods exhibit low universality for different forest types, particularly in areas with high canopy closure where the extraction accuracy is notably compromised. Spectral images and LiDAR data from the tropical broad-leaved forest region within the jurisdiction of Haikou City, Hainan Province, China, were employed. Initially, a distance thresholdbased single-tree segmentation method was employed to extract tree crown edges from the high-resolution spectral image. Subsequently, the obtained positions of initial detected tree vertices were constrained using the segmented tree crown edges, and precise positioning of single-tree vertices was achieved. Following this, a seed-point-based single-tree segmentation method was applied for final tree extraction in the broad-leaved forest. The results indicated that compared with existing single-tree segmentation methods based on the relative distances between trees, by selecting the optimal segmentation scale in combination with spectral imagery for precise positioning, the issue of over-segmentation caused by traditional single-scale segmentation methods was ameliorated. The accuracy of single-tree identification was improved from 0.67 to 0.92. This method proved to be more effective in the segmentation of forest trees using remote sensing, demonstrating high applicability across various forest types. It established a solid data foundation for subsequent single-tree information extraction and held promising prospects for practical applications. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Remote sensing

Controlled terms: Data fusion? - ?Data mining? - ?Forestry? - ?Image segmentation? - ?Optical radar

Uncontrolled terms: Airborne LiDAR? - ?Broad-leaved forests? - ?Coniferous and broad-leaved mixed forest? - ?Forest type? - ?Mixed forests? - ?Segmentation methods? - ?Single tree segmentation? - ?Spectral images? - ?Tree crowns? - ?Tree segmentation

Classification code: 716.2 Radar Systems and Equipment? - ?723.2 Data Processing and Image Processing? - ?741.3 Optical Devices and Systems? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control

DOI: 10.6041/j.issn.1000-1298.2024.01.019

Funding text: 国家电网有限公司科技项目 (5500-202220144A-1-1-ZN)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

5. Completeness Measurement and Identification of Geometric Error of Rotary Axis of Boring Machine

Accession number: 20240915642701

Title of translation: 精密镗床旋转轴几何误差完备性测量与辨识

Authors: Guo, Shijie (1, 2); Ding, Qiangqiang (1, 2); Zou, Yunhe (1, 2); Sa, Rina (1, 2); Tang, Shufeng (1, 2)

Author affiliation: (1) College of Mechanical Engineering, Inner Mongolia University oj Technology, Huhhot; 010051, China; (2) Key Laboratory of Special Service Robot of Inner Mongolia Autonomous Region, Huhhot; 010051, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 446-458

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To address the problem that the number of geometric errors were inconsistent and incompleteness which needed to be measured for the rotary axis of four axis horizontal boring machine, an analyzing methodology of PIGEs formation mechanism based on the shape generation function and a method of the completeness measuring, identifying geometric errors of the rotary axis were proposed for a four axis horizontal boring machine. Firstly, the generation function of PIGEs of horizontal boring machines was constructed based on the shape generation mechanism, and the minimum number of position-independent geometric error (PIGEs) that the rotary axis can be adjusted through error compensation was determined. Secondly, the completeness function model was established consisted of four terms PIGEs, six terms position-dependent geometric error (PDGEs), six terms setup error (SEs) and DBB measurement track radius length of the rotary axis of horizontal boring machine, the Viviani curve measurement track based on DBB was designed based four-axis synchronized motion, and the NURBS characterization of six item PDGEs, identification methods of PIGEs, and SEs of the rotary axis were constructed. Finally, the comparative experiment by error compensating was carried out. The results showed that the error compensation using the geometric error completeness measurement and identification results included four terms PIGEs, six terms PDGEs, and six terms SEs can improve the measurement accuracy of circular trajectory by 40. 69% compared with that of compensate six PDGEs simply. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Error compensation

Controlled terms: Geometry

Uncontrolled terms: Completeness measurement? - ?Formation mechanism? - ?Four-axis? - ?Geometric errors? - ?Horizontal boring machine? - ?Identification? - ?Position dependents? - ?Rotary axis? - ?Setup errors? - ?Shape generations

Classification code: 921 Mathematics

Numerical data indexing: Percentage 6.90E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.043

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

6. Path Tracking and Turning Control Algorithm of Tracked Vehicle Based on ICR

Accession number: 20240915642659

Title of translation: 基于ICR的履带车辆路径跟踪与转向控制算法研究

Authors: Wang, Faan (1, 2); Yang, Quanhe (1, 2); Zhang, Zhaoguo (1, 2); Li, Annan (1, 2); Xu, Hongwei (1, 2)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 386-395 and 425

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of low path tracking accuracy, many control times and large turning deviation of unilateral braking agricultural tracked vehicles in hilly and mountainous areas, the path tracking control of tracked vehicles under different load conditions was studied. Firstly, the turning kinematics of the tracked vehicle was theoretically analyzed, and the kinematics model of the tracked vehicle was established. Secondly, according to the unilateral braking turning characteristics of the tracked vehicles, an instantaneous center of rotation was proposed for instantaneous control, which can plan the optimal turning target point, according to the turning point position of the planned path and the turning instantaneous center of the tracked vehicle, and controlling the tracked vehicle to turn to the required course at the turning target point at one time. Meanwhile, the design of the turning controller was completed. Finally, the simulation and field experiments of the tracked vehicle under three different load conditions were carried out. The simulation results showed that the average error area of the tracking path and the average turning control times generated by the large angle turning control algorithm were reduced by 68. 95% and 68. 77%, respectively. The mean value of the mean lateral deviation of the tracking path, the mean turning control times and the mean minimum deviation of the turning point generated by the large angle turning control algorithm were reduced by 57. 27%, 33. 93% and 62. 29%, respectively. And the path tracking effect was better, which verified the effectiveness of the large angle turning control algorithm. The test results met the requirements of tracked vehicle path tracking and provided a theoretical basis and reference for the path tracking of agricultural tracked vehicles. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 33

Main heading: Tracked vehicles

Controlled terms: Agriculture? - ?Braking? - ?Kinematics

Uncontrolled terms: Agricultural tracked vehicle? - ?Control time? - ?Instantaneous turning center? - ?Load condition? - ?Path tracking? - ?Path tracking control? - ?Target point? - ?Turning center? - ?Turning control? - ?Turning-points

Classification code: 602 Mechanical Drives and Transmissions? - ?663 Buses, Tractors and Trucks? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?931.1 Mechanics

Numerical data indexing: Percentage 2.70E+01%, Percentage 2.90E+01%, Percentage 7.70E+01%, Percentage 9.30E+01%, Percentage 9.50E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.037

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

7. Potato Sprouting and Surface Damage Detection Method Based on Improved Faster R - CNN

Accession number: 20240915642681

Title of translation: 基于改进Faster R-CNN的马铃薯发芽与表面损伤检测方法

Authors: Liu, Yijun (1, 2); He, Yakai (3, 4); Wu, Xiaomei (1, 2); Wang, Wenjie (3, 4); Zhang, Li’na (1, 2); Lu, Huangzhen (1, 2)

Author affiliation: (1) Chinese Academy of Agricultural Mechanization Sciences Group Co.,Ltd., Beijing; 100083, China; (2) National Key Laboratory of Agricultural Equipment Technology, Beijing; 100083, China; (3) China National Packaging and Food Machinery Corporation, Beijing; 100083, China; (4) Key Laboratory of Agricultural Product Processing Equipment, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 371-378

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Germination and surface damage detection are crucial steps in the commercialization of fresh table potatoes. To address the low accuracy rate of high-pixel image object recognition in the high-throughput grading and sorting process of fresh table potatoes, a method for detecting potato sprouting and surface damage based on improved Faster R - CNN was proposed. Using Faster R - CNN as the baseline network, the feature extraction network in Faster R - CNN was replaced with the residual network (ResNet50), and a feature pyramid network (FPN) integrated with ResNet50 was designed to increase the depth of the neural network. A comparative model assessment and ablation studies were performed to empirically validate the efficacy of the proposed model and its modifications. The findings delineated that the enhanced algorithm demonstrated an average precision rate of 98.89% in identifying potatoes, 97. 52% in discerning sprouting events, and 92. 94% in recognizing surface defects. When benchmarked against the Faster R - CNN model, the adapted model incurred no additional computational time or memory overhead while manifesting a marginal decline of 0. 04 percentage points in potato identification accuracy. Notably, it significantly elevated the average precision in detecting sprouting and surface imperfections by 7.79 percentage points and 34.54 percentage points, respectively. This augmented model was robust in high-resolution imaging environments facilitated by industrial-grade cameras and served as a cornerstone for the methodological advancement of automated grading and sorting processes in the commercial potato industry. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Damage detection

Controlled terms: Grading? - ?Image enhancement? - ?Object recognition? - ?Surface defects

Uncontrolled terms: Commercialisation? - ?Detection methods? - ?Fast R - CNN? - ?Grading process? - ?High resolution? - ?Percentage points? - ?Potato? - ?Sorting process? - ?Sprouting? - ?Surface damages

Classification code: 951 Materials Science

Numerical data indexing: Percentage 5.20E+01%, Percentage 9.40E+01%, Percentage 9.889E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.035

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

8. Canopy Transpiration Water Consumption Simulation of Orange Forest in Dry and Hot Valley Area Based on Bayesian Analysis

Accession number: 20240915637116

Title of translation: 基于贝叶斯分析的干热河谷区橙子林冠层蒸腾耗水模拟

Authors: Zhang, Jingying (1); Chen, Dianyu (1); Ma, Yongsheng (2); Hu, Xiaotao (1); Du, Jingbin (2); Wang, Shujian (1)

Author affiliation: (1) Key Laboratory of Agricultural Soil, Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Yan’an Fruit Industry Research and Development Center, Luochuan, 727400, China

Corresponding author: Chen, Dianyu(875948920@qq.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 305-315

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The mechanism of water consumption is the basis for management and regulation of water in farmland/orchards. Focusing on the transpiration mechanism of water consumption, the simulation effect of different Jarvis - Stewart model configurations on transpiration consumption in orange forests in dry and hot valleys was compared based on Bayesian parameter estimation methods, and the applicability of Jarvis - Stewart model in the simulation of transpiration water consumption under the condition of strong interaction effect of influence factors was explored. The results showed that considering different influencing factors and their limiting functions would have a great impact on the simulation effect, among which considering soil moisture content and leaf area index had obvious effects on the improvement of the simulation effect, while the introduction of saturated water vapor pressure difference and air temperature would reduce the simulation accuracy to varying degrees. The more impact factors considered, the more complex the model structure was, and the better the simulation effect was. The best model structure screened out basically realized the reliable simulation of water consumption of transpiration in orange forest, but there was still obvious room for improvement in the simulation effect, so the model complexity, simulation accuracy and uncertainty should be comprehensively considered to further explore the appropriate model structure. The research can provide scientific basis for the establishment of water?saving irrigation technology system and water management optimization in orchards, and also provide data support for the further development and improvement of water consumption models. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 42

Main heading: Transpiration

Controlled terms: Citrus fruits? - ?Forestry? - ?Information management? - ?Parameter estimation? - ?Soil moisture? - ?Water management

Uncontrolled terms: ‘Dry’ [? - ?Bayesian parameter estimation? - ?Dry and hot valley area? - ?Jarvis — stewart model? - ?Orange forest? - ?Simulation accuracy? - ?Simulation effects? - ?Transpiration water consumption simulation? - ?Valley areas? - ?Water consumption

Classification code: 461.9 Biology? - ?483.1 Soils and Soil Mechanics? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.4 Agricultural Products

DOI: 10.6041/j.issn.1000-1298.2024.01.029

Funding text: 国家自然科学基金青年基金项目 (51909232) 和中国博士后基金面上项目 (2019M663588)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

9. Review on Path Tracking Control of Unmanned Articulated Steering Vehicles

Accession number: 20240915630256

Title of translation: 无人驾驶絞接转向车辆路径跟踪控制研究综述

Authors: Zhu, Qingyuan (1); Cheng, Jiaqi (1); Chen, Xuanwei (1); Yang, Changlin (1); Gao, Yunlong (1); Shao, Guifang (1)

Author affiliation: (1) Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen; 361005, China

Corresponding author: Shao, Guifang(gfshao@xmu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 1-21

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The path tracking of unmanned articulated steering vehicles is the key to accurately and smoothly carrying out operational tasks, which can effectively improve the operational efficiency and safety of articulated steering vehicles in industries such as agriculture, forestry, mining, and construction. The research on path tracking control typically included three aspects : vehicle model construction, control algorithm design, and algorithm validation and evaluation, from which the research progress of path tracking control technology for articulated steering vehicles was systematically analyzed. Firstly, the geometric, kinematic, and dynamic models of articulated steering vehicles were reviewed, and then the applicable scenarios and limitations of these models in path tracking control research were discussed. Above that, the research status of path tracking algorithms for articulated steering vehicles was elaborated, and the advantages and disadvantages of each algorithm as well as its scope of application were summarized in comparison, with further generalization about the methods of validation and evaluation of the algorithms. The research focuses and directions of articulated steering vehicle path tracking technology were proposed as follows : the research of vehicle modeling considering vehicle dynamics factors and dynamic time-varying characteristics of model parameters, the design of multi?condition adaptive control algorithms incorporating the adaptation of different algorithms and combining the intelligent algorithms, the development of standardized and process-oriented high-fidelity simulation scenarios, and the research of evaluation methods for integrating multiple performances included accuracy, stability, and security. This review can serve as a valuable reference for further research on the path tracking strategies of articulated steering vehicles. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 146

Main heading: Dynamic models

Controlled terms: Accident prevention? - ?Automobile steering equipment? - ?Forestry? - ?Petroleum reservoir evaluation? - ?Steering

Uncontrolled terms: Articulated steering? - ?Articulated steering vehicle? - ?Control strategies? - ?Dynamics models? - ?Operational tasks? - ?Path tracking? - ?Path tracking control? - ?Unmanned drivings? - ?Vehicle modelling? - ?Verification evaluation

Classification code: 512.1.2 Petroleum Deposits : Development Operations? - ?662.4 Automobile and Smaller Vehicle Components? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?914.1 Accidents and Accident Prevention? - ?921 Mathematics

DOI: 10.6041/j.issn.1000-1298.2024.01.001

Funding text: 国家自然科学基金面上项目（52075461）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

10. Synergistic Estimation of Soil Salinity Based on Sentinel-1/2 Improved Polarization Combination Index and Texture Features

Accession number: 20240915640265

Title of translation: 基于 Sentinel – 1/2 改进极化指数和纹理特征的土壤含盐量反演模型

Authors: Zhang, Zhitao (1, 2); He, Yujie (1, 2); Yin, Haoyuan (1, 2); Xiang, Ru (1, 2); Chen, Junying (1, 2); Du, Ruiqi (1, 2)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 175-185

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Most of the current studies on Sentinel – 1/2 synoptic inversion of vegetation soil salinity were based on Sentinel–2 spectral information and Sentinel – 1 backscattering coefficients, without considering the two aspects that Sentinel – 2 spectral information was susceptible to soil brightness and Sentinel – 1 backscattering coefficients were susceptible to soil roughness and moisture. Therefore, in order to further improve the accuracy of Sentinel – 1/2 synoptic inversion of vegetation soil salinity, the Sentinel - 1 backscatter coefficients were corrected with a water cloud model to eliminate the influence of vegetation. Then, the corrected backscatter coefficients and Sentinel – 2 texture features screened by VIP, 00B and PCA were used to construct soil salinity inversion models based on RF, ELM and Cubist. The results showed that the correlation between the radar backscatter coefficient and the soil salinity was improved to some extent after the removal of vegetation effects by the water cloud model. For the coupled models of different variable selection methods and different machine learning methods, 00B had the best performance in soil salinity inversion when being coupled with RF, ELM and Cubist, with R2 above 0. 750 for both modeling and validation sets. And 00B - Cubist model had the highest accuracy and [Formula presented] was 0. 955, which had good robustness. It provided some ideas for further applications of machine learning in collaboration with physical models and optical satellites in collaboration with radar satellites in soil salinity inversion. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 52

Main heading: Machine learning

Controlled terms: Backscattering? - ?Cloud computing? - ?Soils? - ?Textures? - ?Vegetation

Uncontrolled terms: Backscatter coefficients? - ?Improving polarization index? - ?Machine-learning? - ?Polarization indices? - ?Sentinel – 1/2? - ?Sentinel-1? - ?Soil salinity? - ?Spectral information? - ?Texture features? - ?Water cloud models

Classification code: 483.1 Soils and Soil Mechanics? - ?722.4 Digital Computers and Systems? - ?723.4 Artificial Intelligence

DOI: 10.6041/j.issn.1000-1298.2024.01.016

Funding Details: Number: 2022YFD1900404,51979232,52179044,52279047, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 国家自然科学基金项目(51979232、52279047、52179044) 和国家重点研发计划项目 (2022YFD1900404)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

11. Automated Measurement Method of Phenotypic Parameters of Edible Mushroom Mycelium Based on VGG-UNet

Accession number: 20240915637713

Title of translation: 基于VGG UNet的食用菌菌丝体表型参数自动测量方法

Authors: Chen, Yan (1, 2); Lu, Jiahao (1); Hu, Xiaochun (3); Qi, Liangliang (4)

Author affiliation: (1) College of Computer and Electronic Information, Guangxi University, Nanning; 530004, China; (2) Guangxi Key Laboratory of Multiinedia Communications Network Technology, Nanning; 530004, China; (3) College of Big Data and Artificial Intelligence, Guangxi University of Finance and Economics, Nanning; 530003, China; (4) Microbiology Research Institute, Guangxi Academy of Agricultural Sciences, Nanning; 530007, China

Corresponding author: Hu, Xiaochun(hxch@gxufe.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 233-240

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Mycelium phenotypic characteristics of edible mushroom are an important basis for the evaluation of edible mushroom germplasm resources and scientific breeding. To address the problems of traditional threshold segmentation method to extract mycelium regions which are easily disturbed by uneven light, irregular growth of mycelium and metabolites produced in the petri dishes, an image dataset of edible mycelium was made and a deep learning-based automatic measurement method for edible mycelium phenotype parameters was proposed. The U — Net network encoder was partially replaced with the first 13 convolutional layers of VGG16, and pre-training weights were introduced to constmct a VGG — UNet model applicable to mycelium segmentation. The average cross-merge ratio of this model reached 98. 18%, which was 0. 93 percentage points higher than that of the original U — Net model. After obtaining mycelium segmentation images by this model, the five phenotypic parameters of radius, perimeter, area, coverage, and roundness of mycelium were calculated by using OpenCV correlation functions. A linear regression analysis was performed between the manual measurement method, and the R2 of mycelium radius, perimeter, area and coverage were 0. 979 5, 0. 991 5, 0. 975 0 and 0. 975 0, respectively, and the RMSE were 2. 20 mm, 4. 73 mm, 176. 74 mm2 and 3. 16%, respectively. The method was tested to accurately accomplish the task of automatic* measurement of phenotypic parameters of edible mycelium, which provided a theoretical basis for the study of phenotypic analysis of edible mushrooms. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Mycelium

Controlled terms: Conservation? - ?Deep learning? - ?Metabolites? - ?Parameter estimation? - ?Semantic Segmentation? - ?Semantics

Uncontrolled terms: Automated measurement? - ?Deep learning? - ?Edible mushroom? - ?Edible mushroom mycelium? - ?Images processing? - ?Measurement methods? - ?Mushroom Mycelium? - ?Phenotypic parameter? - ?Semantic segmentation? - ?VGG — unet

Classification code: 461.4 Ergonomics and Human Factors Engineering? - ?461.8 Biotechnology? - ?723.4 Artificial Intelligence? - ?811.2 Wood and Wood Products

Numerical data indexing: Area 7.40E-05m2, Percentage 1.60E+01%, Percentage 1.80E+01%, Size 2.00E-02m, Size 7.30E-02m

DOI: 10.6041/j.issn.1000-1298.2024.01.022

Funding text: 广西科学研究与技术开发计划项目（桂科 AA20302002-3）、广西创新驱动发展专项资金项目（桂科 AA0302012-1）和财政部和农业农村部：国家现代农业产业技术体系建设项目（CARS-20）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

12. Vision Detection Method for Picking Robots Based on Improved Faster R-CNN

Accession number: 20240915630263

Title of translation: 基于改进 Faster R — CNN 的苹果采摘视觉定位与检测方法

Authors: Li, Cuiming (1); Yang, Ke (1); Shen, Tao (1); Shang, Zhengyu (1)

Author affiliation: (1) School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou; 730050, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 47-54

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To address the issue of poor detection and positioning capabilities of fruit picking robots in scenes with densely distributed targets and fruits occluding each other, a method to improve the fruit detection and positioning of Faster R — CNN was proposed by introducing an efficient channel attention mechanism (ECA) and a multiscale feature fusion pyramid (FPN). Firstly, the commonly used VGG16 network was replaced with a ResNet50 residual network with strong expression capability and eliminate network degradation problem, thus extracting more abstract and rich semantic information to enhance the model’s detection ability for multiscale and small targets. Secondly, the ECA module was introduced to enable the feature extraction network to focus on local and efficient information in the feature map, reduce the interference of invalid targets, and improve the model’s detection accuracy. Finally, a branch and leaf grafting data augmentation method was used to improve the apple dataset and solve the problem of insufficient image data. Based on the constructed dataset, genetic algorithms were used to optimize K-means + + clustering and generate adaptive anchor boxes. Experimental results showed that the improved model had average precision of 96.16% for graspable apples and 86.95% for non-graspable apples, and the mean average precision was 92.79%, which was 15.68 percentages higher than that of the traditional Faster R — CNN. The positioning accuracy for graspable and non-directly graspable apples were 97.14% and 88.93 %, respectively, which were 12.53 percentages and 40.49 percentages higher than that of traditional Faster R — CNN. The weight was reduced by 38.20%. The computation time was reduced by 40.7 %. The improved model was more suitable for application in fruit-picking robot visual systems. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 20

Main heading: Fruits

Controlled terms: Agricultural robots? - ?Feature extraction? - ?Genetic algorithms? - ?Image enhancement? - ?K-means clustering? - ?Semantics

Uncontrolled terms: Apple picking robot? - ?Attention mechanisms? - ?Detection methods? - ?Distributed target? - ?Efficient channels? - ?Fast R — CNN? - ?Feature pyramid? - ?Picking robot? - ?Target localization? - ?Targets detection

Classification code: 731.5 Robotics? - ?821.1 Agricultural Machinery and Equipment? - ?821.4 Agricultural Products? - ?903.1 Information Sources and Analysis

Numerical data indexing: Percentage 3.82E+01%, Percentage 4.07E+01%, Percentage 8.695E+01%, Percentage 8.893E+01%, Percentage 9.279E+01%, Percentage 9.616E+01%, Percentage 9.714E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.004

Funding text: 国家自然科学基金项目（52265065, 51765031）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

13. Design and Modeling of Novel Three Degree-of-freedom Parallel Robot for Narrow Space

Accession number: 20240915642693

Title of translation: 面向狭长空间的三自由度并联机器人设计与建模

Authors: Xu, Dongmei (1); Liu, Xianglong (1); Yu, Simiao (2); Xu, Chao (1); Yang, Fan (1); Cao, Chuqing (3)

Author affiliation: (1) College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an; 710054, China; (2) School of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an; 710055, China; (3) Wuhu HIT Robot Technology Research Institute Co., Ltd., Wuhu; 241000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 426-435

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Parallel robots are widely studied for the advantages of high stiffness, stable structure, large bearing capacity and small motion load, and have been widely used in agricultural and industrial fields. Due to the distribution of branch chains, most of the existing parallel robots cannot work in a long and narrow space while having a large working space. Therefore, for the narrow and long working environment, a three-degree of freedom parallel mechanism was proposed. The whole mechanism was arranged along a linear guide rail direction, reducing the width perpendicular to the guide rail direction, so that it was easy to fit into a narrow space, while having a large working space, and realizing translational motion on three degrees of freedom. The degree of freedom of the mechanism was calculated by G - K formula and the rationality of the design of parallel robot was verified. The kinematics and dynamics of the platform were analyzed. The singularity was analyzed by genetic algorithm. Finally, the kinematics and dynamics simulation were carried out in ADAMS software, by comparing with the mathematical model in Simulink software, the error of the two results was generally less than 0.05%, which showed that the mathematical model was correct. The working space of the mechanism was analyzed by analytical method. The research results can provide an idea and structure for 3-DOF parallel robot working in narrow and long space. It can also provide a theoretical basis for the mathematical modeling of the structure. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 22

Main heading: Kinematics

Controlled terms: Agricultural robots? - ?Agriculture? - ?Computer software? - ?Degrees of freedom (mechanics)? - ?Dynamics? - ?Genetic algorithms? - ?Machine design

Uncontrolled terms: Agricultural fields? - ?Design and modeling? - ?High stiffness? - ?Kinematics and dynamics? - ?Large bearings? - ?Narrow spaces? - ?Parallel robots? - ?Stable structures? - ?Three degree of freedoms? - ?Working space

Classification code: 601 Mechanical Design? - ?723 Computer Software, Data Handling and Applications? - ?731.5 Robotics? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.1 Agricultural Machinery and Equipment? - ?931.1 Mechanics

Numerical data indexing: Percentage 5.00E-02%

DOI: 10.6041/j.issn.1000-1298.2024.01.041

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

14. Robot Path Planning Based on Artificial Potential Field Method with Obstacle Avoidance Angles

Accession number: 20240915642689

Title of translation: 基于含避障角人工势场法的机器人路径规划

Authors: Wan, Jun (1, 2); Sun, Wei (2); Ge, Min (2); Wang, Kehong (1); Zhang, Xiaoyong (1)

Author affiliation: (1) School of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing; 210094, China; (2) School of Automobile and Traffic Engineering, Jiangsu University of Technology, Changzhou; 213001, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 409-418

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the local minima problem of the distance-based artificial potential field (APF) method, an obstacle avoidance path planning method with the artificial potential field method containing obstacle avoidance angle was proposed. In a planar environment, the slope was used to determine the positional relationship during the path planning process, and the magnitude of the repulsive force in the artificial potential field method was derived from the difference between the distance from the robot’s current point to the obstacle and the radius of influence of the obstacle, and the deflection angle of the repulsive force was adjusted, thus overcoming the shortcomings of local minima that existed in the traditional artificial potential field method. In addition, the circular arc interpolation theory was utilized to convert the robot planar obstacle avoidance problem into a spatial obstacle avoidance problem in a spatial environment. The improved artificial potential field method was further refined based on the robot configuration to meet the practical obstacle avoidance requirements. The effectiveness of the improved artificial potential field method was verified by simulation and experiment. The results of simulation and experimental studies showed that the artificial potential field method containing obstacle avoidance angles not only solved the problem of local minima when performing obstacle avoidance path planning in single or multiple obstacle environments, but also realized the smooth trajectory profile of the end of the 6-DOF robot with no oscillations during obstacle avoidance, thus verifying the feasibility of the proposed obstacle avoidance path planning method. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Interpolation

Controlled terms: Agricultural robots? - ?Collision avoidance? - ?Motion planning? - ?Robot programming

Uncontrolled terms: 6-DOF robot? - ?Artificial potential fields method? - ?Circular interpolation? - ?Deflection angle for obstacle avoidance? - ?Deflection angles? - ?Obstacle avoidance angle? - ?Obstacles avoidance? - ?Path planning method? - ?Repulsive forces

Classification code: 723.1 Computer Programming? - ?731.5 Robotics? - ?821.1 Agricultural Machinery and Equipment? - ?914.1 Accidents and Accident Prevention? - ?921.6 Numerical Methods

DOI: 10.6041/j.issn.1000-1298.2024.01.039

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

15. Analytical Method and Evaluation of Tomato Size and Posture Based on Visual and Tactile Perception

Accession number: 20240915637091

Title of translation: 基于视触觉感知的番茄尺寸和姿态解析方法

Authors: Ma, Zenghong (1, 2); Tan, Li (1); Zeng, Wei (1); He, Leiying (1, 2); Du, Xiaoqiang (1, 3)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Zhejiang Key Laboratory of Transplanting Equipment and Technology, Hangzhou; 310018, China; (3) Key laboratory of Agricultural Equipment for Hilly and Mountainous Areas in Southeastern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou; 310018, China

Corresponding author: Du, Xiaoqiang(xqiangdu@zstu.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 223-232

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to solve the problem that the branches and leaves were obscured in the visual recognition of tomato fruit she and posture during the grasping process of traditional agricultural robots, a method of tomato size and posture analy^is based on visual and tactile perception was proposed. In the process of fruit grasping, the local point cloud information of fruit contour contact was obtained by visual and tactile seniorst and then the point cloud information under different sensor coordinate sytems was transformed to the same base cooidinate system by camera parameter calibration and finger joint transformation matrix, and then the sue and posture information of fruit was analyzed by point cloud improved PCA algorithm and ICP algorithm. In order to evaluate the performance of the proposed analytical method, tomato sue and posture tests were performed in the laboratory environment. The real values of tomato fruit size and postunp were obtained by vernier caliper measurement and depth camera scanning and compared with the presented analytical results. The test insults showed that the average errors of transverse and longitudinal dimensions of toniato obtained by this method were 8.66% and 11.08%, and the average eirors of horizontal angle and vertical deflection angle of tomato fruit axis and projection plane were 10.03% and 14.02%. The size and posture information of tomato fruit analyzed by the proposed method can be applied to the posture regulation of tomato fruit grasping processt so as to improve the reliability of tomato fiuit grasping and picking. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Fruits

Controlled terms: Agricultural robots? - ?Cameras? - ?Linear transformations

Uncontrolled terms: Cloud libraries? - ?Evaluation of size and posture? - ?ICP algorithms? - ?Improved PCA algorithm? - ?PCA algorithms? - ?PCL point cloud library? - ?Point-clouds? - ?Tactile sensors? - ?Tomato picking? - ?Visual sensor

Classification code: 731.5 Robotics? - ?742.2 Photographic Equipment? - ?821.1 Agricultural Machinery and Equipment? - ?821.4 Agricultural Products? - ?921.3 Mathematical Transformations

Numerical data indexing: Percentage 1.003E+01%, Percentage 1.108E+01%, Percentage 1.402E+01%, Percentage 8.66E+00%

DOI: 10.6041/j.issn.1000-1298.2024.01.021

Funding text: 浙江省基础公益研究项目(LGN22C130006), 国家自然科学基金项目(31971798), 国家重点研发计划项目(2022YFD2202103), 浙江省”领雁”研发攻关计划项目(2023C02049. 2022C02057) 和浙江省”三农九方”科技协作计划项目(2022SNJF017)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

16. Hyperspectral and Multispectral Co-inversion of Chlorophyll Content in Maize Leaves Based on Two-branch Convolutional Network

Accession number: 20240915638360

Title of translation: 基于双分支卷积网络的玉米叶片叶绿素含量高光谱和多光谱协同反演

Authors: Wang, Yazhou (1); Xiao, Zhiyun (1)

Author affiliation: (1) College of Electric Power, Inner Mongolia University of Technology, Huhhot; 010080, China

Corresponding author: Xiao, Zhiyun(xiaozhiyun@imut.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 196-202 and 378

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem of accurate chlorophyll prediction in smart agriculture, a method of hyperspectral and inultispectral synergistic inversion of chlorophyll content in maize leaves was proposed based on two-branch network. The undercomplete self-encoder was used for data dimensionality reduction to capture the most significant features in the data, so that the dimensionality reduced data can be trained instead of the original data to accelerate the training efficiency, and the two-branch convolutional network was used to fill the hyperspectral data with inultispectral data to make full use of the spatial detail information of the hyperspectral data, and then combined with the 1 DCNN to establish a prediction model of chlorophyll content in maize leaves. The results showed that compared with the traditional dimensionality reduction algorithm, the undercomplete self-encoder processed the best prediction results, with a coefficient of determination R2 of 0.988 and a root mean square error (RMSE) of 0.273, indicating that dimensionality reduction using the undercomplete self-encoder was effective in improving the accuracy of data inversion. Compared with the single hyperspectral data inversion model and the inultispectral data inversion model, the two-branch convolutional network prediction models both achieved better prediction results, with R2 above 0.932 and RMSE below 1.765, indicating that the collaborative hyperspectral and inultispectral image inversion model based on the two-branch convolutional network can make effective use of the features of the data. For the other data combined with the mentioned two-branch convolutional network model for the inverse model, the R2 was above 0.905 and the RMSE was below 2.149, which indicated that the prediction model had a certain degree of universality. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Forecasting

Controlled terms: Chlorophyll? - ?Convolution? - ?Data reduction? - ?Mean square error? - ?Signal encoding

Uncontrolled terms: Auto encoders? - ?Chlorophyll contents? - ?Co-inversion? - ?Convolutional networks? - ?HyperSpectral? - ?Hyperspectral Data? - ?Maize leaf? - ?Prediction modelling? - ?Root mean square errors? - ?Two-branch convolutional network

Classification code: 716.1 Information Theory and Signal Processing? - ?723.2 Data Processing and Image Processing? - ?804.1 Organic Compounds? - ?922.2 Mathematical Statistics

DOI: 10.6041/j.issn.1000-1298.2024.01.018

Funding text: 内蒙古自治区科技计划项目 (2021GG0345) 和内蒙古自治区自然科学基金项目 (2021MS06020)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

17. Quadratic Identification Method of Kinematic Parameters of Industrial Robots Based on POE Model

Accession number: 20240915642664

Title of translation: 基于POE模型的工业机器人运动学参数二次辨识方法研究

Authors: Qiao, Guifang (1, 2); Du, Baoan (1); Zhang, Ying (1); Tian, Rongjia (1); Liu, Di (1); Liu, Hanzhong (1)

Author affiliation: (1) School of Automation, Nanjing Institute of Technology, Nanjing; 211167, China; (2) School of Instrument Science and Engineering, 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: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 419-425

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem of insufficient precision performance of industrial robots in the high-end manufacturing field, a quadratic identification method of kinematic parameters of industrial robots based on POE model was proposed. Firstly, the construction method of the POE kinematic error model was presented. The fitness function based on the POE kinematic error model was established for kinematics identification. Secondly, a quadratic identification method was proposed to realize the parameter identification with high precision. At first, the improved grey wolf optimizer algorithm was applied to realize the primary identification of kinematic errors. The average comprehensive position error and average comprehensive attitude error of the Staubli TX60 robot were reduced from (0. 648 mm,0. 212) to (0. 457 mm,0. 166) respectively. In order to further improve the accuracy performance of the robot, the accurate identification of kinematic errors was carried out through the LM (Levenberg - Marquard) algorithm. The average comprehensive position error and average comprehensive attitude error of the Staubli TX60 robot were reduced to (0.237 mm, 0.063). The average comprehensive position error and average comprehensive attitude error were reduced by 63. 4% and 70. 2%. Finally, in order to verify the stability of the above quadratic identification method, five different sets of identification datasets and validation datasets were randomly selected for the parameter error identification of the POE error model. The results showed that the proposed quadratic identification method was able to stably and accurately identify the kinematic parameter errors of industrial robots. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Industrial robots

Controlled terms: Agricultural robots? - ?Errors? - ?Kinematics? - ?Parameter estimation

Uncontrolled terms: Error modeling? - ?Exponentials? - ?Identification method? - ?Improved GWO algorithm? - ?Kinematic error? - ?Kinematics parameters? - ?Parameters identification? - ?Position errors? - ?Product of exponential? - ?Serial industrial robots

Classification code: 731.5 Robotics? - ?731.6 Robot Applications? - ?821.1 Agricultural Machinery and Equipment? - ?931.1 Mechanics

Numerical data indexing: Percentage 2.00E+00%, Percentage 4.00E+00%, Size 2.37E-04m, Size 4.57E-01m, Size 6.48E-01m

DOI: 10.6041/j.issn.1000-1298.2024.01.040

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

18. Design and Experiment of Hybrid Jamming Variable Stiffness Soft Finger

Accession number: 20240915642702

Title of translation: 混合阻塞变刚度软手指设计与实验

Authors: Li, Dongmin (1); Ma, Wenping (1); Wang, Yu (1); Fang, Jiaqi (1); Zhang, Guohui (1); Ding, Guowei (1)

Author affiliation: (1) College of Intelligent Equipment, Shandong University of Science and Technology, Taian; 271019, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 436-445 and 458

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to improve the grasping effect on complex shaped objects of the variable stiffness soft robotic arm with a single jamming medium, inspired by the structure of human fingers, a variable stiffness soft finger with hybrid jamming methods imitating the finger pulp structure was designed. It was a double-layer structure, where the outer layer was used for a pneumatic actuator, and the inner layer was used for a variable stiffness layer with hybrid jamming methods based on active layer jamming and passive particle jamming methods, which can facilitate the soft fingers to fit the profiles of objects grasped automatically, and achieve the effects of passive adaptation under active driving, and objects grasping reliably by stiffness adjustment. Based on the traditional sewing techniques, the soft fingers were manufactured with hyperelastic silicone material. A stiffness control model for multi-material soft fingers based on cantilever beam structure was established by using Euler - Bernoulli beam theory and virtual work principle, furthermore, a selection rule to increase the overall material stiffness was proposed based on the stiffness control model. Experimental results on bendability showed the excellent bendability of the soft fingers. Besides, the stiffness variation and objects grasping experimental results showed that the stiffness of the soft fingers with hybrid jamming method was increased by 4. 6 times, and the maximum relative error of the stiffness control model established was only 3. 4%. Despite of increasing the surface roughness of the objects grasped, the detachment force of the soft fingers was still increased by 17%, which reached 1.7 N. Therefore, compared with the soft fingers with single jamming medium, the grasp success rate and load capacity were improved significantly. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Jamming

Controlled terms: Silicones? - ?Stiffness? - ?Surface roughness

Uncontrolled terms: Control model? - ?Double layer structure? - ?Human fingers? - ?Hybrid jamming? - ?Layer jamming? - ?Object grasping? - ?Soft robotics? - ?Soft-finger? - ?Stiffness control? - ?Variable stiffness

Classification code: 711 Electromagnetic Waves? - ?815.1.1 Organic Polymers? - ?931.2 Physical Properties of Gases, Liquids and Solids? - ?951 Materials Science

Numerical data indexing: Force 1.70E+00N, Percentage 1.70E+01%, Percentage 4.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.01.042

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

19. Design and Experiment of Self-propelled Potato Collecting and Bagging Machine

Accession number: 20240915630228

Title of translation: 自走式马铃薯捡拾装袋机设计与试验

Authors: Yang, Deqiu (1, 2); Wang, Xin (1, 2); Liu, Mengmeng (1, 2); Li, Yang (1, 2); Chen, Xinyu (1, 2); Cheng, Ziwen (1, 2)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 86-95

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: A self-propelled potato collecting and bagging machine was designed to address the issues of high labor intensity, low efficiency, and high cost in manual picking during potato segmented harvesting. The self-propelled potato collecting and bagging machine can complete the tasks of potato picking, potato soil separation, seedling removal, and bagging in one go. Elaborating on the overall structure of the selfpropelled potato collecting and bagging machine, a detailed design of key components such as the picking device, lifting chain device, thrid conveyor chain device, sorting table, and unloading device was provided; the DEM — MBD coupling method was used to analyze the movement process and force situation of potatoes at the intersection of two conveying chains; the Box — Behnken test method was used to carry out four factors and three levels experimental research on the working parameters of the machine, with the potato leakage rate and the potato damage rate as the evaluation indicators, and the forward speed of the machine, the linear speed of the picking device conveyor chain, the lifting chain, and the third conveyor chain as the test factors. The quadratic polynomial regression model was established by using DesignExpert software. After optimizing the regression model, response surfaces were drawn and the optimal operating parameters of the machine were obtained. Finally, field experiments showed that when the forward speed of the machine was 0.70 m/s, the conveying chain speed of the picking device was 1.10 m/s, the lifting chain speed was 1.20 m/s, and the third conveying chain speed was 1.30 m/s, the potato leakage rate was 2.82% and the potato damage rate was 3.61%, which met the requirements of potato collecting operations. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Chain conveyors

Controlled terms: Conveying? - ?Machine components? - ?Regression analysis? - ?Unloading

Uncontrolled terms: Damage rate? - ?Discrete elements? - ?Forward speed? - ?Labour intensity? - ?Leakage rates? - ?Low-high? - ?Multibody dynamic (MBD)? - ?Potato? - ?Potato collecting and bagging machine? - ?Segmented harvesting

Classification code: 601.2 Machine Components? - ?691.2 Materials Handling Methods? - ?692.1 Conveyors? - ?922.2 Mathematical Statistics

Numerical data indexing: Percentage 2.82E+00%, Percentage 3.61E+00%, Velocity 1.10E+00m/s, Velocity 1.20E+00m/s, Velocity 1.30E+00m/s, Velocity 7.00E-01m/s

DOI: 10.6041/j.issn.1000-1298.2024.01.008

Funding text: 财政部和农业农村部：国家现代农业产业技术体系建设项目(CARS-09-P25)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

20. Soil Cd Content Retrieval from Hyperspectral Remote Sensing Data Based on Organic Matter Characteristic Spectral Bands

Accession number: 20240915637954

Title of translation: 基于有机质特征谱段的土壤 Cd 含量高光谱遥感反演

Authors: Zhang, Xia (1); Sun, Youxin (1, 2); Shang, Kun (3); Ding, Songtao (1, 2); Sun, Weichao (1)

Author affiliation: (1) Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing; 100101, China; (2) College of Resources and Environment, University of Chinese Academy of Sciences, Beijing; 100049, China; (3) Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing; 100048, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 186-195

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To address the mechanistic limitations and data redundancy issues in the quantitative retrieval of soil Cd using hyperspectral remote sensing, an inversion method was proposed based on organic matter characteristic spectral bands. The method involved the extraction of characteristic spectral bands of organic matter with adsorption effects on heavy metal Cd in soil spectra. Subsequently, competitive adaptive reweighted sampling (CARS) was employed to optimize the selected spectral bands, and a partial least squares regression (PLSR) model was developed for the inversion of heavy metal Cd. The proposed method was validated by using laboratory spectral data from the Chenzhou mine and field spectral data from the Hami Huangshan South mine. The results demonstrated that the extraction of organic matter characteristic spectral bands not only reduced data redundancy but also significantly improved the accuracy of Cd inversion. In comparison to the correlation coefficient (CC) and genetic algorithm (GA) methods, the CARS algorithm exhibited superior performance in feature selection and inversion accuracy. The validation accuracies, expressed as R2, were 0. 94 for the Chenzhou laboratory spectral data and 0. 80 for the Hami field spectral data, indicating the robustness of the CARS — PLSR algorithm for both laboratory and field spectra. The findings can provide valuable references for feature band selection and algorithm optimization in the hyperspectral estimation of soil heavy metal content. The proposed method effectively addressed the limitations of existing approaches by leveraging the unique spectral characteristics of organic matter in soil. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Soils

Controlled terms: Biogeochemistry? - ?Biological materials? - ?Crops? - ?Extraction? - ?Feature extraction? - ?Genetic algorithms? - ?Laboratories? - ?Least squares approximations? - ?Organic compounds? - ?Redundancy ? - ?Remote sensing

Uncontrolled terms: Active substance? - ?Content retrieval? - ?Data-redundancy? - ?Features selection? - ?Hyperspectral remote sensing? - ?Retrieval? - ?Soil heavy metals? - ?Soil spectrally active substance? - ?Spectral band? - ?Spectral data

Classification code: 461.2 Biological Materials and Tissue Engineering? - ?481.2 Geochemistry? - ?483.1 Soils and Soil Mechanics? - ?801.2 Biochemistry? - ?802.3 Chemical Operations? - ?804.1 Organic Compounds? - ?821.4 Agricultural Products? - ?921.6 Numerical Methods

DOI: 10.6041/j.issn.1000-1298.2024.01.017

Funding text: 国家自然科学基金项目 (42371360) 和中国科学院战略性先导科技专项 (XDA28080500)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

21. Design and Experimental Optimization of End Effector for Picking Famous Tea with Split-cutter

Accession number: 20240915630286

Title of translation: 分体刀具式名优茶采摘末端执行器设计与试验优化

Authors: Chen, Jianneng (1, 2); Li, Hang (1); Liu, Linmin (3); Jia, Jiangming (1, 2); Zhao, Runmao (1, 2); Wu, Chuanyu (1, 2)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province, Hangzhou; 310018, China; (3) Bureau of Agriculture and Rural Affairs of Songyang County, Zhejiang Province, Songyang, 323400, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 39-46 and 195

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the problem of side buds being unable to be picked during the mechanized picking process of famous tea, an end effector was designed based on the relevant parameters of top buds, side buds, and tea stems, combined with the tea garden environment, which used the bending deformation of the cutter teeth of the split cutter to adapt to the interference of tea stems to pick side buds. The influencing factors of picking success rate were obtained by finite element simulation of cutting lateral buds: cutter tooth width, cutter tooth length and cutter thickness; the central composite design with three factors and three levels and response surface analysis were used to study the interaction of various factors on the success rate of picking taking the picking success rate as the response value, a quadratic regression model was established to determine the significant primary and secondary order of the influence of each factor on the picking success rate as follows: cutter tooth length, cutter tooth width, and cutter thickness. Taking the picking success rate as the goal, the experimental factors were optimized, and the optimized parameters were obtained: the cutter tooth width, cutter thickness, and cutter tooth length were 2. 6 mm, 0. 90 mm, and 20. 0 mm, respectively. The optimized parameters were tested in tea garden picking, the results showed that the end effector could effectively pick tea leaves, and the success rate of picking top buds and side buds was 93% and 63%, the relative error between the experimental value and the predicted value was less than 5%, the optimized model was reliable. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 24

Main heading: End effectors

Controlled terms: Regression analysis? - ?Surface analysis

Uncontrolled terms: Cutter teeth? - ?Design optimization? - ?Experimental optimization? - ?Famous tea? - ?Lateral bud? - ?Optimized parameter? - ?Picking robot? - ?Split cutter? - ?Tea gardens? - ?Tea picking robot

Classification code: 731.5 Robotics? - ?922.2 Mathematical Statistics? - ?951 Materials Science

Numerical data indexing: Size 0.00E00m, Size 6.00E-03m, Size 9.00E-02m, Percentage 5.00E+00%, Percentage 6.30E+01%, Percentage 9.30E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.003

Funding Details: Number: 2022C02052,51975537,52105284,U23A20175, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 国家自然科学基金项目(51975537, 52105284, U23A20175)和浙江省”领雁”研发攻关计划项目(2022C02052)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

22. Yield Estimation of Winter Wheat Based on Multiple Remotely Sensed Parameters and VMD-GRU

Accession number: 20240915639439

Title of translation: 基于遥感多参数和 VMD – GRU 的冬小麦单产估测

Authors: Guo, Fengwei (1, 2); Wang, Pengxin (1, 2); Liu, Junming (3); Li, Hongmei (4)

Author affiliation: (1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China; (3) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China; (4) Shaanxi Provincial Meteorological Bureau, Xi’an; 710014, China

Corresponding author: Wang, Pengxin(wangpx@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 164-174 and 185

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to fully exploit the time-series information and trend information of time-series remotely sensed parameters and further improve the yield estimation accuracy of winter wheat, vegetation temperature condition index (VTCI), leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR), which were closely related to the growth and development of winter wheat, were selected as remotely sensed parameters, and a neural network was constructed based on variational mode decomposition (VMD) and gated recurrent unit (GRU). The VMD algorithm was applied to decompose each remotely sensed parameter series into multiple sets of intrinsic mode function (IMF) components, and the IMF components that were highly correlated with the original remotely sensed parameter series were selected for feature reconstruction, and the reconstructed features were used as the input of the GRU network to develop a combined model for yield estimation of winter wheat. The results showed that the VMD 一 GRU model for yield estimation had a coefficient of determination of 0.63, root mean squared error of 448.80 kg/hm2, and mean relative error of 8.14%, with a highly significant correlation level (P ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Variational mode decomposition

Controlled terms: Crops? - ?Mean square error? - ?Parameter estimation? - ?Recurrent neural networks? - ?Remote sensing? - ?Time series

Uncontrolled terms: Combined modeling? - ?Function components? - ?Gated recurrent unit? - ?Intrinsic Mode functions? - ?Remotely sensed parameter? - ?Time series informations? - ?Times series? - ?Vegetation temperature condition index? - ?Winter wheat? - ?Yield estimation

Classification code: 716.1 Information Theory and Signal Processing? - ?821.4 Agricultural Products? - ?922.2 Mathematical Statistics

Numerical data indexing: Mass 4.488E+02kg, Percentage 8.14E+00%

DOI: 10.6041/j.issn.1000-1298.2024.01.015

Funding Details: Number: 42171332, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 国家自然科学基金项目（42171332）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

23. Design and Experiment of Multi-disturbance Cleaning and Single-seed Sowing Device for Garlic

Accession number: 20240915630246

Title of translation: 多重扰动清种式大蒜单粒取种排种器设计与试验

Authors: Hou, Jialin (1, 2); Fang, Lizhi (1, 2); Zhang, Haikuo (1); Zhou, Kai (1, 2); Li, Tianhua (1, 2); Li, Yuhua (1, 2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian; 271018, China; (2) Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence, Taian; 271018, China

Corresponding author: Li, Yuhua(liyuhua@sdau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 65-75 and 163

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the common issues of seed leakage and reseeding during the seed-picking process of a spoon-chain garlic seeder, a novel multi-disturbance cleaning and single-seed sowing device was designed. The sowing device collected multiple garlic seeds during the seed-picking process and underwent multiple disturbances to ensure that only one seed remains in the sowing spoon. Focusing on Jinxiang garlic seeds and elucidating the working principle of the sowing device, the optimal parameters of the sowing device and the installation position of multi-disturbance device were determined. Through DEM – MBD coupled simulation experiments, the influence of tilt angle and scoop speed on the success rate of seed filling and the impact of groove shape on the single-seed extraction rate were analyzed. A three-factor three-level orthogonal experiment was performed by using the Box – Behnken central composite design method, with the slope of the second arc-shaped prominent part, inclination angle, and spoon linear speed as experimental factors, and the single-seed qualification rate and seed leakage rate as evaluation criteria. Design-Expert 8. 0. 6 data analysis software was employed to analyze the effects of each factor on the single-seed sowing rate and seed leakage rate and optimize the experimental factors to determine the optimal structural parameters of the multi-disturbance device. A validation experiment was conducted using a test rig to verify the simulation results. Under the conditions of an inclination angle of 15° and a spoon linear speed of 0. 07 m/s, the multi-disturbance device was adjusted to adapt to different levels of garlic seeds by adjusting the distance between the device and the top of the sowing spoon groove. The success rates of single-seed sowing were 92. 2%, 97.2%, and 95.6% for Grade I, Grade II, and Grade III garlic seeds, respectively, demonstrating excellent sowing performance. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Structural optimization

Controlled terms: Seed

Uncontrolled terms: DEM — MBD? - ?Disturbance device? - ?Garlic planter? - ?Inclination angles? - ?Linear speed? - ?Multiple disturbance? - ?Seed sowing? - ?Seede? - ?Single seeds? - ?Single-seed sowing

Classification code: 821.4 Agricultural Products? - ?921.5 Optimization Techniques

Numerical data indexing: Percentage 2.00E+00%, Percentage 9.56E+01%, Percentage 9.72E+01%, Velocity 7.00E+00m/s

DOI: 10.6041/j.issn.1000-1298.2024.01.006

Funding text: 财政部和农业农村部: 国家现代农业产业技术体系项目（CARS-24-D-01), 山东省现代农业产业技术体系蔬菜产业创新团队项目（SDALT-05-11）和中国博士后科学基金面上项目（2019M662410）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

24. Grape Disease Detection Method Based on StyleGAN2—ADA and Improved YOLO v7

Accession number: 20240915637090

Title of translation: 基于StyleGAN2 - ADA和改进YOLO v7的葡萄叶片早期病害检测方法

Authors: Zhang, Linxuan (1, 2); Ba, Yin Tana (1); Zeng, Qingsong (1)

Author affiliation: (1) School of Electrical Engineering, Xinjiang University, Urumqi; 830017, China; (2) National Computer Integrated Manufacturing System Engineering Research Center, Tsinghua University, Beijing; 100084, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 241-252

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Black rot and brown spot disease of grapes are diseases that seriously threaten grape yields, and identification of grape diseases early is of great significance for disease prevention and control and grape yield. However, current disease detection methods have a high leakage rate. The black rot and brown spot were taken as the research objects, a method for detecting grape black rot and brown spot based on adaptive discnininator enhanced style generation adversarial network combined with improved YOLO v7 was proposed. Firstly, the grape disease data were expanded by the adaptive discnininator enhanced style generation adversarial network + de blurring processing. Secondly, the MSRCP algorithm was used to enhance the image and improve the lighting environment to highlight the characteristics of disease spots. Finally, based on the YOLO v7 network framework, the BiFonner attention mechanism was embedded in the feature extraction network to strengthen the key features of the target area. BiFPN was used instead of PA — FPN to better realize multi-scale feature fusion and reduce computational complexity. SPD module was introduced in the detection head section of YOLO v7 to improve the detection performance of low-resolution images. The combination of CIoU and NWD loss function was used to redefine the loss function to achieve rapid and accurate identification of small targets. The experimental results showed that the accuracy of spot detection in this method reached 94. 1 %, which was 5. 7 percentage points higher than that of the original algorithm, and 3. 3 percentage points, 3. 8 percentage points, and 4. 4 percentage points higher than that of Faster R — CNN, YOLO v3 — SPP, and YOLO v5x models, respectively, which can realize the rapid and accurate identification of early grape diseases, which was of positive significance for ensuring the development of the grape industry. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 39

Main heading: Object detection

Controlled terms: Disease control? - ?Image enhancement

Uncontrolled terms: Attention mechanisms? - ?Black rot? - ?Brown spots? - ?Disease identification? - ?Grape? - ?Objects detection? - ?Percentage points? - ?Self-attention mechanism? - ?Stylegan2 — ADA? - ?YOLO v7

Classification code: 723.2 Data Processing and Image Processing

Numerical data indexing: Percentage 1.00E00%

DOI: 10.6041/j.issn.1000-1298.2024.01.023

Funding text: 新疆维吾尔族自治区自然科学基金项目?(2022D01C431)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

25. Co-simulation and Test of Electro - Hydraulic System of Novel Hybrid Track

Accession number: 20240915642663

Title of translation: 液电混动履带底盘电液系统联合仿真与试验

Authors: Han, Mingxing (1); Xu, Kun (1); Liao, Yitao (1); Li, Miao (1); Yu, Kai (1)

Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 396-408 and 418

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Traditional hydraulic or pure electric driven tracked agricultural machinery equipment has problems such as high-power consumption, response lag, short battery life, and insufficient power and torque output. A type of high-efficiency electro - hydraulic track chassis was proposed, which integrated two independent power systems of hydraulic drive and electric drive, four-wheel drive structure with two hydraulic motors and two servo motors. It can realize the use of small power engine to output large torque, which was conducive to the lightweight design. At the same time, the speed and torque closed-loop control of the servo motor can adapt to the changes of the external load of the matching chassis, which can significantly improve the dynamic output characteristics of the closed hydraulic drive system, improve the dynamic control performance of the whole machine and reduce the energy consumption. A co-simulation model of the electro - hydraulic system was established based on AMESim and Matlab. The simulation compared and analyzed the driving performance of the whole machine under different working conditions, such as straight driving on flat ground, mountain climbing and in-situ steering. The prototype test results showed that the maximum speed of the electro - hydraulic drive track chassis was 1. 1 m/s, the fastest turning time was 2. 4 s, and the minimum turning diameter was 150 cm, which can realize turning and turning around on the complex terrain of hills and mountains. The offset of track chassis in a straight line was less than or equal to 3. 3%. Compared with the hydraulic drive under the same working conditions, the electro - hydraulic mode can reduce the energy consumption of at least 9.3%, effectively reduce the energy consumption and improve the working efficiency of the whole machine. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Electric drives

Controlled terms: Agriculture? - ?Brushless DC motors? - ?Chassis? - ?Energy efficiency? - ?Energy utilization? - ?Hydraulic machinery? - ?Landforms? - ?MATLAB

Uncontrolled terms: Condition? - ?Cosimulation? - ?Driving performance? - ?Electro-hydraulics? - ?Electrohydraulic systems (EHSS)? - ?Energy-consumption? - ?Power? - ?Servo-motor? - ?Track chassi? - ?Whole machine

Classification code: 481.1 Geology? - ?525.2 Energy Conservation? - ?525.3 Energy Utilization? - ?632.2 Hydraulic Equipment and Machinery? - ?662.4 Automobile and Smaller Vehicle Components? - ?663.2 Heavy Duty Motor Vehicle Components? - ?705.3.2 DC Motors? - ?723.5 Computer Applications? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?921 Mathematics

Numerical data indexing: Percentage 3.00E+00%, Percentage 9.30E+00%, Size 1.50E+00m, Time 4.00E+00s, Velocity 1.00E00m/s

DOI: 10.6041/j.issn.1000-1298.2024.01.038

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

26. Kinematic Characteristic Analysis and Test of Tea in Tea Vibrating-sifting Machine Based on DEM

Accession number: 20240915630255

Title of translation: 基于离散元的茶叶抖筛机茶叶运动特性分析与试验

Authors: Wang, Xiaoyong (1, 2); Zhu, Junyu (1, 2); Zhang, De (1, 2); Yu, Zhi (1, 2); Ni, Dejiang (1, 2)

Author affiliation: (1) College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan; 430070, China; (2) National Key Laboratory for Germplasm Innovation and Utilization of Horticultural Crops, Wuhan; 430070, China

Corresponding author: Ni, Dejiang(nidj@mail.hzau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 109-121 and 133

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to reduce the error-sifting rate of the tea vibrating-sifting machine, the effects of inclination angle, vibration amplitude, and vibration frequency on the motion characteristics of tea particles on the sieve were studied from the perspective of particle dynamics. By combining the discrete element method to numerically simulate the movement of tea particles on the sieve surface, and analyzing the vibrating-sifting process of tea particles, the transport mechanism of tea particles on the sieve during the vibrating-sifting process was clarified. The results showed that tea particles were mainly concentrated in the middle of the sieve, and too high or too low frequency could cause horizontal segregation of tea particles on the sieve. The average velocity and rotational kinetic energy of tea particles on the sieve were gradually increased with the increase of amplitude and frequency. The inclination angle had little effect on the average velocity and rotational kinetic energy of tea particles on the sieve. The velocity of tea particles along the X-axis and Z-axis contributes the most to the average velocity of tea particles on the sieve. The variation amplitude of the migration coefficient was gradually increased with the increase of inclination angle, vibration amplitude, and vibration frequency. The order of influence of different parameters on the particle migration ability of tea vibrating-sifting process was as follows : amplitude, frequency, and inclination angle. When the vibration amplitude was 22.5 mm, the inclination angle was 3°, and the vibration frequency was 4.166 Hz, the error-sifting rate of the tea vibrating-sifting test was the smallest. The error between error-sifting rate results of the tea vibrating-sifting test and the simulation test results was within 5 percentages, indicating that the DEM simulation had high accuracy. The research result had important reference value for reducing the error-sifting rate of the tea vibrating-sifting machine. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Velocity distribution

Controlled terms: Errors? - ?Kinetic energy? - ?Kinetics? - ?Sieves

Uncontrolled terms: Amplitude-frequency? - ?Angle vibrations? - ?Average velocity? - ?DEM? - ?Inclination angles? - ?Motion characteristics? - ?Vibrating-sifting machine? - ?Vibration amplitude? - ?Vibration frequency? - ?Vibration vibrations

Classification code: 631.1 Fluid Flow, General? - ?922.2 Mathematical Statistics? - ?931 Classical Physics; Quantum Theory; Relativity

Numerical data indexing: Frequency 4.166E+00Hz, Size 2.25E-02m

DOI: 10.6041/j.issn.1000-1298.2024.01.010

Funding text: 国家重点研发计划项目(2021YFD1000401)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

27. Analysis and Model Construction of Factors Affecting Photosynthesis and Transpiration Rates in Facility Lettuce

Accession number: 20240915642656

Title of translation: 设施生菜光合和蒸腾速率影响因素分析与预测模型构建

Authors: Zhang, Zenglin (1); Yang, Jie (1); Guo, Changjiang (1); Han, Wenting (1); Yang, Zhenchao (2)

Author affiliation: (1) College of Mechanical and Electronic Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) College of Horticulture, Northwest A&F University, Shaanxi, Yangling; 112100, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 339-349

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Photosynthesis rate and transpiration rate are crucial physiological indicators in plants. In a controlled artificial environment, Italian lettuce was chosen as the research subject. A nested experiment was conducted to investigate the multivariate impact on the photosynthesis rate and transpiration rate of lettuce. The study unveiled patterns of environmental factors affecting these rates, leading to the construction of a neural network prediction model for photosynthesis rate and transpiration rate during the seedling phase of lettuce. For lettuce seedlings, four factors were selected; temperature, relative humidity, photosynthetic photon flux density (PPFD), and environmental CO2 concentration. Using the random forest method, a correlation analysis of the data was carried out. The results revealed that factors strongly correlated with the transpiration rate, in descending order, were CO2 concentration, temperature, relative humidity, and PPFD. Meanwhile, for the photosynthesis rate, the factors were CO2 concentration, PPFD, temperature, and relative humidity. A GA - BP neural network physiological indicator prediction model was developed, employing the enumeration method to determine the number of hidden layer nodes and training functions, and optimizing the initial weights and thresholds of the BP neural network through a genetic algorithm. Testing with actual data, the determination coefficients of predicted and actual values for photosynthesis rate and transpiration rate were 0. 962 12 and 0. 979 44, respectively, with root mean square errors (RMSE) of 2. 983 2 |xmol/(m *s) and 0.001 435 8 mol/(m “s). This demonstrated the significantly improved performance of the GA - BP neural network in terms of model accuracy and iteration times. In summary, the research result can provide a valuable basis for environmental regulation in facility lettuce production. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Lettuce

Controlled terms: Carbon dioxide? - ?Correlation methods? - ?Environmental regulations? - ?Forecasting? - ?Forestry? - ?Genetic algorithms? - ?Iterative methods? - ?Mean square error? - ?Physiological models? - ?Physiology ? - ?Transpiration

Uncontrolled terms: BP neural networks? - ?CO 2 concentration? - ?Correlation analysis? - ?Facility lettuce? - ?GA - BP neural network? - ?Photosynthesis rate? - ?Photosynthetic photon flux densities? - ?Photosynthetic rate? - ?Prediction modelling? - ?Transpiration rates

Classification code: 454.2 Environmental Impact and Protection? - ?461.9 Biology? - ?804.2 Inorganic Compounds? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.4 Agricultural Products? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics

Numerical data indexing: Amount of substance 8.00E+00mol

DOI: 10.6041/j.issn.1000-1298.2024.01.032

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

28. Soybean Seed Yield Estimation Model Based on Ground Hyperspectral Remote Sensing Technology

Accession number: 20240915634759

Title of translation: 基于地面高光谱遥感的大豆产量估算模型研究

Authors: Tang, Zijun (1, 2); Zhang, Wei (1, 2); Huang, Xiangyang (1, 2); Xiang, Youzhen (1, 2); Zhang, Fucang (1, 2); Chen, Junying (1, 2)

Author affiliation: (1) Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Shaanxi, Yangling; 712100, China

Corresponding author: Xiang, Youzhen(Youzhenxiang@nwsuaf.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 145-153 and 240

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To estimate crop yield in field management, hyperspectral data and yield data during the reproductive growth period of soybeans through two years of field experiments were collected. Seven spectral indices were calculated based on first-order spectral reflectance at various growth stages. These indices included the ratio index (RI), difference index (DI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), triangular vegetation index (TVI), modified normalized difference index (mNDI), and modified simple ratio (mSR). A correlation analysis between the spectral indices and soybean yield data were conducted by using the correlation matrix method. The best wavelength combinations to be used as the optimal spectral indices related to soybean yield were extracted. Finally, the five spectral indices with the highest correlation coefficients with soybean yield at different growth stages were selected as input variables for the model. Support vector machine (SVM), random forest (RF), and back propagation neural network (BPNN) were utilized to construct soybean yield estimation models and conducted validation. The results indicated that the spectral indices calculated at different growth stages (full flowering stage (R2), full pod stage (R4), and seed filling stage (R6)) all exhibited a correlation coefficient greater than 0. 6 with yield, showing a strong correlation. Among these, the spectral index FDmSR at the full pod stage had the highest correlation with soybean yield, reaching 0. 717. The optimal model for soybean yield estimation was built using first-order spectral indices from the full pod stage in combination with RF as input variables, achieving a validation set R2 of 0. 85, and RMSE and MRE values of 272. 80 kg/hm2 and 5.12%, respectively. The research outcome can provide a theoretical basis and practical reference for crop yield estimation based on hyperspectral remote sensing technology. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Support vector machines

Controlled terms: Backpropagation? - ?Crops? - ?Forestry? - ?Neural networks? - ?Remote sensing? - ?Vegetation mapping

Uncontrolled terms: Crop yield? - ?Estimate model? - ?Estimation models? - ?HyperSpectral? - ?Hyperspectral remote sensing technology? - ?Machine-learning? - ?Soybean? - ?Spectral indices? - ?Yield estimate model? - ?Yield estimation

Classification code: 405.3 Surveying? - ?723 Computer Software, Data Handling and Applications? - ?723.4 Artificial Intelligence? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.4 Agricultural Products

Numerical data indexing: Mass 8.00E+01kg, Percentage 2.00E+00%, Percentage 5.12E+00%

DOI: 10.6041/j.issn.1000-1298.2024.01.013

Funding Details: Number: 52179045, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 国家自然科学基金项目（52179045）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

29. Design and Validation of Pneumatic Vibration Walnut Picking Machine Carried by UAV

Accession number: 20240915630281

Title of translation: 基于无人机平台的气振式核桃采收机设计与试验

Authors: Guo, Guanzhu (1); Yang, Liyang (1); Luo, Ya’nan (1); Xu, Guangming (2)

Author affiliation: (1) College of Mechanical, Electrical Engineering, Yunnan Agricultural University, Kunming; 650201, China; (2) Yunnan Light Textile Industry Design Institute Co., Ltd., Kunming; 650041, China

Corresponding author: Luo, Ya’nan(1339706332@qq.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 55-64

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the Yunnan mountainous areas planted deep-striped walnut trees are tall and large, which makes the existing fruit picking machinery difficult to reach the planting to harvest the fruit, as well as manually climbing walnut trees with bamboo poles to hit the picking fruit was high cost and casualties. For the first time, the principle and method of pneumatic vibration picking walnut with UAV were proposed. Based on the test and analysis results of the connection strength of the stalk of deep?grained walnuts, the pneumatic vibration flow simulation analysis of walnuts dislodged by pneumatic vibration was carried out. A walnut pneumatic vibration fruit picking machinery installed on a six-rotor agricultural plant protection UAV was designed. The stability of the pneumatic walnut picking machinery was analyzed when the machine was subjected to the recoil of the airflow during the launch of the air?vibration flow. The pneumatic vibration fruit picking machinery for walnuts mounted on a UAV was tested and validated. According to the two harvesting modes of efficiency priority and harvesting rate priority, the fruit picking efficiency and net picking rate of the pneumatic vibration walnut picking machinery were predicted and analyzed. The results showed that the critical flow velocities at which pneumatic vibration caused walnut stalk breakage were 77. 5 m/s, 69. 0 m/s and 58. 5 m/s when the ripeness of walnuts was 80%, 90% and 100%, respectively. The optimal distance from the pneumatic nozzle of the pneumatic vibration walnut picking machinery to the fruiting position was 0.5 m for a pneumatic compartment with volume of 20 L and pneumatic pressure of 1 MPa. The simulated and experimental values for the maximum effective area of a single pneumatic vibration flow for fruit picking at this location were approximately 0. 09 m2 and 0. 10 m2, respectively. The maximum effective area for fruit picking in a single pass was decreased as the distance to the pneumatic nozzle increased. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Efficiency

Controlled terms: Fruits? - ?Harvesting? - ?Nozzles? - ?Pneumatics? - ?Unmanned aerial vehicles (UAV)? - ?Vibration analysis

Uncontrolled terms: Deep-grained walnut? - ?Effective area? - ?Harvesting efficiency? - ?Mountainous area? - ?Picking machineries? - ?Picking machines? - ?Pneumatic nozzles? - ?Pneumatic vibration flow? - ?Vibration flow? - ?Walnut trees

Classification code: 632.3 Pneumatics? - ?652.1 Aircraft, General? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?913.1 Production Engineering

Numerical data indexing: Percentage 1.00E+02%, Percentage 8.00E+01%, Percentage 9.00E+01%, Pressure 1.00E+06Pa, Size 1.00E+01m, Size 5.00E-01m, Size 9.00E+00m, Velocity 0.00E00m/s, Velocity 5.00E+00m/s, Volume 2.00E-02m3

DOI: 10.6041/j.issn.1000-1298.2024.01.005

Funding text: 云南省自然科学基金重点项目（202301AS070079), 兴滇英才支持计划产业创新人才专项（YNWR - CYJS - 2018 - 050）和云南省教育厅科研基金项目（2023J0397）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

30. Discrete Element Simulation Parameters Calibration for Xinjiang Cotton Straw

Accession number: 20240915630224

Title of translation: 新疆棉花秸秆离散元仿真参数标定研究

Authors: Zhang, Jiaxi (1); Zhang, Peng (2); Zhang, Hu (3); Tan, Chunlin (4); Wan, Wenyu (2); Wang, Yichao (1)

Author affiliation: (1) School of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Heilongjiang Agricultural Economics Vocational College, Mudanjiang; 154005, China; (3) Xinjiang Uygur Autonomous Region Agricultural Machinery Product Quality Supervision and Management Station, Urumqi; 830052, China; (4) School of Mechanical and Electrical Engineering, Xinjiang Changji Vocational and Technical College, Changji; 831110, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 76-84 and 108

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Due to the lack of accurate simulation model parameters in the process of mechanized harvesting and crushing of cotton straw, there is a great difference between the simulation effect and the actual operation in the design of machinery and tools, which limits the design and research of cotton straw harvesting and crushing device to a certain extent. Xinjiang cotton straw was used as experimental material to carry out simulation analysis. After the intrinsic parameters of cotton straw were determined by physical tests, the EDEM simulation software was used for test simulation and parameter calibration of cotton straw. The accumulation angle and the maximum destructive power of cotton straw were 28. 62° and 143. 21 N respectively by the method of accumulation angle test and bending test. The Hertz — Mindlin no slip model and Hertz - Mindlin with bonding model were used to simulate the stacking angle and bending of cotton straw. The collision recovery coefficient, static friction coefficient and rolling friction coefficient between cotton straw and the collision recovery coefficient, static friction coefficient and rolling friction coefficient between cotton straw and steel were respectively 0.5, 0.41, 0.06, 0.5, 0.37 and 0.08, and the normal contact stiffness, tangential contact stiffness, critical normal stress and critical tangential stress of cotton straw were respectively obtained, which were 4.15 × 1010 N/m, 5.60 × 1010 N/m, 40 MPa and 50 MPa, respectively. According to the above results, the pulverized cotton straw can be divided into powder type material, crushed type material and unbroken type material according to different lengths and widths. The deviation between the simulation test quality and the actual test quality was 6.84%, 8.29% and 7.37%, which proved the feasibility of the parameters and can be used for the parameter calibration of cotton straw. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Machine design

Controlled terms: Calibration? - ?Cotton? - ?Crushing? - ?Software testing? - ?Stiffness

Uncontrolled terms: Accumulation angle test? - ?Cotton straws? - ?EDEM? - ?Friction coefficients? - ?Mindlin? - ?Parameters calibrations? - ?Recovery coefficients? - ?Rolling friction? - ?Static friction coefficient? - ?Xinjiang

Classification code: 601 Mechanical Design? - ?723.5 Computer Applications? - ?821.4 Agricultural Products? - ?951 Materials Science

Numerical data indexing: Force 2.10E+01N, Percentage 6.84E+00%, Percentage 7.37E+00%, Percentage 8.29E+00%, Pressure 4.00E+07Pa, Pressure 5.00E+07Pa, Surface tension 1.01E+03N/m

DOI: 10.6041/j.issn.1000-1298.2024.01.007

Funding Details: Number: 2022B02022,51865058,52365038,YTH5D2022 - 09, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 国家自然科学基金项目(52365038, 51865058), 新疆维吾尔自治区农机研发制造推广应用一体化项目(YTH5D2022 - 09)和新疆维吾尔自治区重点研发计划项目(2022B02022 - 2)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

31. Blockchain Based Salmon Cold Chain Multi-chain Collaborative Supervision Model

Accession number: 20240915642690

Title of translation: 基于区块链的三文鱼冷链多链协同监管模型研究

Authors: Sun, Chuanheng (1, 2); Yang, Xiaohu (1, 2); Luo, Na (2, 3); Chen, Feng (2, 3); Xu, Darning (2, 3); Xing, Bin (2, 3)

Author affiliation: (1) College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin; 300384, China; (2) National Engineering Research Center for Information Technology in Agriculture, Beijing; 100097, China; (3) National Engineering Laboratory for Agri-product Quality Traceability, Beijing; 100097, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 360-370

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In the context of the cluster development in the cold chain industry, the challenge of cross-chain signature data transmission and slow verification efficiency caused by the continuity and fragmentation of regulatory data in the collaborative process of salmon cold chain management was addressed. To tackle this issue, a blockchain-based multi-chain collaborative regulatory model for salmon cold chain management was proposed. The model incorporated a data verification and cold chain pattern monitoring method based on the aggregate signature algorithm, which ensured both the authenticity and integrity of salmon cold chain management while enhancing the efficiency of cross-chain regulatory data verification. Furthermore, a prototype system of the multi-chain collaborative regulatory model for salmon cold chain management on the Ethereum platform was implemented. Performance testing of the system revealed that the multi-chain architecture showed an average improvement of 17. 98% in regulatory performance compared with the single-chain architecture, with the advantage becoming more pronounced as the number of blockchain transactions were increased. In terms of verification efficiency, the slope analysis of the verification time curve indicated that the aggregate signature algorithm had a significant advantage with a slope of 0. 553, as opposed to the traditional verification algorithm with a slope of 57.448. This demonstrated that the aggregate signature algorithm exhibited remarkable efficiency advantages as the number of signatures were increased. Regarding communication overhead, the traditional signature algorithm required a maximum signature communication of up to 4 875 B under theoretical limits, while the aggregate signature algorithm consistently maintained a signature communication of 96 B, even without compression. The test results showed that the aggregate signature and verification method exhibited significant efficiency advantages in the batch data transmission and verification of the salmon cold chain scenario, providing valuable insights and references for trustworthy cold chain management and the development of cluster-based cold chains. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Efficiency

Controlled terms: Aggregates? - ?Blockchain? - ?Cryptography? - ?Data transfer? - ?Information management

Uncontrolled terms: Aggregate signature? - ?Block-chain? - ?Chain management? - ?Cold chain? - ?Cold chain supervision? - ?Cross-chain? - ?Multi-chain? - ?Salmon cold chain? - ?Signature algorithms

Classification code: 406 Highway Engineering? - ?412.2 Concrete Reinforcements? - ?723.3 Database Systems? - ?913.1 Production Engineering

Numerical data indexing: Percentage 9.80E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.034

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

32. Microenvironment Simulation and Crop Transpiration Analysis of Solar Greenhouse with Different Ventilation Modes

Accession number: 20240915637719

Title of translation: 不同通风方式日光温室微环境模拟与作物蒸腾研究

Authors: Wan, Min (1); Yang, Wei (1); Liu, Zhuqing (1); Xu, Chenxi (1); Liu, Dong (1)

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

Corresponding author: Yang, Wei(wyang@cau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 328-338 and 349

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The heat storage of back wall of the solar greenhouse reduces efficiency of ventilation and cooling. High temperature will stimulate plant water transpiration and reduce the utilization rate of water resources. Taking Beijing Tongzhou solar greenhouse as the research object, on the basis of the original upper and lower vents, the rear wall vents were added. Based on DO radiation model, component transport model and porous medium model, a computational fluid dynamics (CFD) model of solar greenhouse was established. The microenvironment of greenhouse under different ventilation modes was explored, and the transpiration characteristics of crops were obtained by combining crop transpiration model analysis. The results showed that the change of temperature would directly affect the intensity of crop transpiration, and the spatial distribution characteristics of the two were consistent. The high temperature of the greenhouse at noon, the opening of the back wall and the lower vent, compared with the original opening of the upper and lower vent, the airflow trend was similar, due to the reduction of part of the heat storage wall, the cooling efficiency was increased by 5.7%, and the transpiration was decreased by 0.020mm/h, the opening of the back wall, the upper and lower vent, the transpiration was decreased by 0.005mm/h. After opening the back wall and the upper vent, because the two vents were close to one side and far away from the crop, only the north side can be partially cooled, the cooling efficiency was reduced by 10.3%, the dehumidification efficiency was increased by 5.7%, and the transpiration was increased by 0.035mm/h. In addition, in the combination of vents, the lower vent was set in the windward direction, which can reduce the energy and momentum loss of the external wind and improve the ventilation cooling efficiency. The results provided a reference for the regulation of microenvironment in solar greenhouse. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 36

Main heading: Computational fluid dynamics

Controlled terms: Crops? - ?Greenhouses? - ?Heat storage? - ?Humidity control? - ?Landforms? - ?Porous materials? - ?Transpiration? - ?Transport properties? - ?Vents

Uncontrolled terms: Cooling efficiency? - ?Crop transpirations? - ?Highest temperature? - ?Microenvironments? - ?Plant water? - ?Solar greenhouse? - ?Solar greenhouse microenvironment? - ?Ventilation mode? - ?Ventilation mode crop transpiration

Classification code: 461.9 Biology? - ?481.1 Geology? - ?723.5 Computer Applications? - ?821.4 Agricultural Products? - ?821.6 Farm Buildings and Other Structures? - ?931.1 Mechanics? - ?931.2 Physical Properties of Gases, Liquids and Solids? - ?951 Materials Science

Numerical data indexing: Percentage 5.70E+00%, Size 2.00E-05m, Size 3.50E-05m, Size 5.00E-06m, Percentage 1.03E+01%

DOI: 10.6041/j.issn.1000-1298.2024.01.031

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

33. Lightweight Method for Identifying Farmland Weeds Based on YOLO v5

Accession number: 20240915637710

Title of translation: 基于 YOLO v5的农田杂草识别轻量化方法研究

Authors: Ji, Wenli (1); Liu, Zhou (1); Xing, Haihua (2)

Author affiliation: (1) College of Communications and Information Engineering, Xi’an University of Science and Technology, Xi’an; 710600, China; (2) School of Information Science and Technology, Hainan Normal University, Haikou; 571158, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 212-222 and 293

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The disadvantage of the existing weed recognition models for a variety of small target weeds is that they are low recognition rate, large volume, many parameters and slow detection speed in complex farmland environment. In order to solve this problem, a lightweight weed recognition method was proposed based on YOLO v5 model. Firstly, the multi-scale retinex with color restoration (MSRCR) algorithm was used to preprocess part of the image data to improve the image definition with blurred edge details and reduce the shadow interference in the image. On this basis, the feature extraction network in the recognition model was reset by using the lightweight network PP — LCNet to reduce the amount of model parameters. Secondly, the Ghost convolution model lightweight feature fusion network was used to further reduce the amount of calculation. In order to make up for the loss of model performance caused by lightweight, a normalization-based attention module (NAM) was added at the end of the feature fusion network to enhance the feature extraction ability of the model for weeds and corn seedlings. Finally, the activation function of the attention mechanism of the backbone network was optimized to improve the nonlinear fitting al)ility of the model. Experiments were carried out on the self-built dataset. The experimental results showed that compared with the current mainstream target detection algorithm YOLO v5s and the mature lightweight target detection algorithms MobileNet v3 — YOLO v5s and ShuffleNet v2 — YOLO v5s, the volume of the lightweight weed recognition model was 6. 23 M B, which was reduced by 54. 5%, 12% and 18%, respectively. The mean average precision (n)AP) was 97. 8%, which was increased by 1. 3 percentage points, 5. 1 percentage points, and 4. 4 percentage points, respectively. The detection time of single image was 118. 1 ms, which achieved the requirement of lightweight. It could significantly reduce the complexity of the model while maintaining high model recognition accuracy. The proposed method could identify corn seedling and weed accurately and rapidly, which provided technical support for the use of mobile devices with limited resources for farmland weed recognition. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Feature extraction

Controlled terms: Complex networks? - ?Convolution? - ?Extraction? - ?Farms? - ?Image enhancement? - ?Signal detection

Uncontrolled terms: Attention mechanisms? - ?Features extraction? - ?Features fusions? - ?Ghost convolution module? - ?Lightweight feature extraction network? - ?Percentage points? - ?Recognition models? - ?Targets detection? - ?Weed recognition? - ?YOLO v5s

Classification code: 716.1 Information Theory and Signal Processing? - ?722 Computer Systems and Equipment? - ?802.3 Chemical Operations? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control

Numerical data indexing: Percentage 1.20E+01%, Percentage 1.80E+01%, Percentage 5.00E+00%, Percentage 8.00E+00%, Time 1.00E-03s

DOI: 10.6041/j.issn.1000-1298.2024.01.020

Funding Details: Number: 62066013, Acronym: NSFC, Sponsor: National Natural Science Foundation of China; Number: 20193054YF042NS042,622RC674, Acronym: -, Sponsor: -;

Funding text: 国家自然科学基金项目(62066013), 海南省自然科学基金项目(622RC674) 和西安市科技局农业科技创新工程项目 (20193054YF042NS042)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

34. Time-optimal Trajectory Planning Method for Cooperative Working of Agriculture Material Handling Robot

Accession number: 20240915630217

Title of translation: 农业物料移运机器人协同作业时间最优轨迹规划方法

Authors: Guo, Wanjin (1); Li, Ru (1); Hao, Qinlei (1); Cao, Chuqing (2, 3); Zhao, Lijun (3, 4)

Author affiliation: (1) Key Laboratory of Road Construction Technology and Equipment, Ministry of Education, Chang’an University, Xian; 710064, China; (2) Post-doctoral Research Center, Wuhu HIT Robot Technology Research Institute Co., Ltd., Wuhu; 241007, China; (3) Yangtze River Delta HIT Robot Technology Research Institute, Wuhu; 241007, China; (4) State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin; 150001, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 22-38

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To address the issues of high labor intensity andlow work efficiency for the transfer of agricultural products from harvesting place to warehouse or transportation vehicle in the agricultural field, a material handling robot was designed, which enabled the robot to perform tasks such as grabbing, transporting, and placing materials. Aiming at the problem that the moving track and the working track were relatively independent and time-consuming when the material handling robot moved and grabed simultaneously, a time-optimal trajectory planning methodology for the cooperative working of the designed material handling robot was proposed, which can obtain the time-optimal trajectory for the simultaneous performance of the robot driving and grasping operation. This methodology was used to conduct the time-optimal trajectory planning for the material handling robot, which allowed to take into account the robot’s kinematic and dynamic constraints of both the operation system and the driving system. Additionally, a control law was designed based on Lyapunov theory to reduce the error for the robot,s path tracking and improve the accuracy and stability of the robot’s trajectory tracking. Finally, the effectiveness of the time-optimal trajectory planning method for collaborative operation was verified through joint simulation by the co-simulation in Matlab/Simulink and ADAMS. The results showed that the proposed methodology can enable the robot to obtain a smooth and time-optimal motion trajectory during the material handling process, the displacement, velocity, acceleration, and force/torque of the operation system, and the tractive force curves of each joint of the robot changed gently, and the two-track tractive force met the requirements of the robot which can quickly and stably track the time-optimal path. The designed material handling robot and the proposed time-optimal trajectory planning methodology can provide an effective technical solution for the transfer of agricultural products in the agricultural field. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 38

Main heading: Trajectories

Controlled terms: Agricultural products? - ?Agricultural robots? - ?Materials handling? - ?MATLAB? - ?Robot programming

Uncontrolled terms: A* algorithm? - ?Agricultural fields? - ?Co-operative working? - ?Material handling robots? - ?Operation system? - ?Planning methodology? - ?Time optimization? - ?Time-optimal trajectory planning? - ?Trajectory Planning? - ?Trajectory planning method

Classification code: 723.1 Computer Programming? - ?723.5 Computer Applications? - ?731.5 Robotics? - ?821.1 Agricultural Machinery and Equipment? - ?821.4 Agricultural Products? - ?921 Mathematics

DOI: 10.6041/j.issn.1000-1298.2024.01.002

Funding Details: Number: 2022M722435,2023B675,2Q19YQQ021,300102253201,KJ2020A0364,U202354, Acronym: -, Sponsor: -;

Funding text: 基金项目：国家自然科学基金面上项目(52275005), 中央高校基本科研业务费C项资金项目(300102253201), 长安大学高笠教育教堂改革研究项目(U202354), 安徽省博士后研究人员科研活动经费项目(2023B675)年国博士后科学基金项目(2022M722435), 安徽省教育厅科堂研究重点项且(KJ2020A0364)和高校优秀置生人才支持计划项且(2Q19YQQ021)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

35. Parameter Optimization and Experiment of Air-screen Potato-stone Cleaning Device Based on Gas-Solid Coupling

Accession number: 20240915634754

Title of translation: 基于气固耦合的气筛式马铃薯清选装置参数优化与试验

Authors: Li, Xiaohui (1); Wei, Zhongcai (1, 2); Su, Guoliang (3, 4); Wang, Xinghuan (1); Zhang, Xiangcai (1); Wang, Xianliang (1); Cheng, Xiupei (1); Jin, Chengqian (1, 2)

Author affiliation: (1) School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo; 255091, China; (2) Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing; 210014, China; (3) Shandong Star Agricultural Equipment Co., Ltd., Dezhou; 253600, China; (4) Shandong Provincial Intelligent Engineering and Technology Research Center for Potato Production Equipment, Dezhou; 253600, China

Corresponding author: Wei, Zhongcai(weizc@sdut.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 96-108

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: At present, the rate of potato skin breaking after harvest was high and the content of impurities was high in China. In order to solve the problem that the rate of potato skin breaking was high, the content of impurities was high and the high cost of the above two points after the potato harvest, an airscreen type potato cleaning device was designed and optimized. By using the method of EDEM — Fluent coupling simulation, the air velocity at the inlet of the cleaning device, the swinging form of the shaking screen, the swinging frequency and the inclined angle were taken as the experimental factors, and the cleaning and separating rate and the cleanliness rate of the potatoes were taken as the evaluation indexes. Multiple sets of simulation analyses were conducted on the cleaning process, and validation and optimization were conducted on the basis of the simulation results. The simulation results showed that the wind speed at the inlet of the cleaning device played a decisive role in the feasibility of potato pneumatic separation. The order of significance of the impact was as following： the air velocity at the inlet of the cleaning device, the inclined angle of the shaking screen and the shaking frequency of the shaking screen, and the simple harmonic oscillation of the shaking screen was better than the up-down oscillation. The optimal working parameter combination was that the form of the simple harmonic swing of the screen was front and back, the angle of the screen was 250, the swing frequency was 10 Hz, the wind speed of the fan was 60 m/s. Under the optimal working parameter combination, the potato cleaning and separating rate was 93.1% and the cleanliness rate was 98.7%. The results showed that the application of EDEM — Fluent coupling simulation was helpful to the research of potato cleaning and separating, and the research results could provide a theoretical basis for the design and optimization of potato cleaning device. At the same time, it laid a foundation for the further research on the size and shape of the opening of the shaking sieve. There was little difference between the bench verification experiment and the simulation experiment. The results of the bench verification test and the simulation test were basically the same, which laid a foundation for the follow-up field test. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 39

Main heading: Wind

Controlled terms: Air? - ?Cleaning

Uncontrolled terms: Air velocities? - ?Breakings? - ?Cleaning devices? - ?Coupling simulation? - ?Fluents? - ?Gas-solid couplings? - ?Inclined Angle? - ?Potato； cleaning and separating device? - ?Separation of potato and stone? - ?Wind speed

Classification code: 443.1 Atmospheric Properties? - ?802.3 Chemical Operations? - ?804 Chemical Products Generally

Numerical data indexing: Frequency 1.00E+01Hz, Percentage 9.31E+01%, Percentage 9.87E+01%, Velocity 6.00E+01m/s

DOI: 10.6041/j.issn.1000-1298.2024.01.009

Funding Details: Number: 52I05266, Acronym: NSFC, Sponsor: National Natural Science Foundation of China; Number: 202IM70I801, Acronym: -, Sponsor: -; Number: 202ITSGCI332, Acronym: -, Sponsor: -;

Funding text: 国家自然科学基金项目（52I05266)、山东省科技型中小企业创新能力提升工程项目（202ITSGCI332)、中国博士后科学基金面上项目（202IM70I801）和南京市博士后科研项目

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

36. Construction of Solid Bridge Structured Biomass Pellets by Eucalyptus Sawdust and Its Combustion Characteristics

Accession number: 20240915642671

Title of translation: 桉木屑颗粒燃料固体桥结构构建与燃烧特性研究

Authors: Li, Weizhen (1, 2); Liu, Huacai (1, 3); Jiang, Yang (1, 2); Yin, Xiuli (1, 2); Xu, Xuenan (4); Hong, Hao (4)

Author affiliation: (1) Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou; 510640, China; (2) CAS Key Laboratory of Renewable Energy, Guangzhou; 510640, China; (3) Guangdong Provincial Key Laboratory of New and Renewable Energy Research and Development, Guangzhou; 510640, China; (4) Jilin Hongri New Energy Co., Ltd., Changchun; 130212, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 350-359

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: It is an effective way to improve the physical properties of biomass pellets by constructing “solid bridge” structures inside the pellets. A way of constructing “solid bridge” structured pellets was proposed by blending different particle sizes from one material. The construction scheme was set to add eucalyptus sawdust with (4 mm, 5 mm] particle size into eucalyptus sawdust with (0, 1 mm] particle size. The blending amount (referred to mass fraction of material with (4 mm, 5 mm] particle size in the total materials) was 0, 1%, 3%, 5%, 7%, 10%, 15%, 20%, 25%, 30%, 40% and 100%, respectively. The cross-sectional structures of the made pellets showed that with 5% ~ 10% blending amount, a proper amount of “solid bridge” structures can be constructed by long fiber particle mechanical interlocking. Under this condition, short fiber particles were filled among these mechanical interlocks sufficiently and thus the pellet possessed particle tightly arrangements. The appropriate blending amount was 5%, under which condition the relaxed density, Meyer hardness and specific energy consumption of the pellets reached the relatively higher, the highest and the lowest values of 1 074. 79 kg/m”, 23.93 MPa and 27.06 kj/kg, respectively. Meanwhile, the equilibrium moisture content and moisture absorption rate of the pellets was 11. 65% and 0. 015 3 min, respectively. Then, the heating value analysis given the information that the structured pellets maintained the same higher heating value as the eucalyptus sawdust, which was 18. 44 MJ/kg. At the heating rates of 10 ~40TVmin, the ignition temperature of pellet combustion (with 5% blending amount) was evaluated at 246.60 ~ 265. 00T1, the burnout temperature was measured at 504. 40 ~ 508. 40^, the maximum mass loss rate was assessed at - 6. 84 ~ - 29. 10%/min, and the mean mass loss rate was calculated at - 6. 84 ~ -29. 10%/min, the integrated combustion index was determined at 7. 26 X 10 ~ ~ 1. 09 X 10 min~ -K Besides, the slagging and fouling indices predicted a high or medium tendency for combustion. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 37

Main heading: Biomass

Controlled terms: Blending? - ?Calorific value? - ?Energy utilization? - ?Moisture? - ?Particle size? - ?Particle size analysis? - ?Pelletizing

Uncontrolled terms: “solid bridge” structure? - ?Biomass pellets? - ?Bridge structures? - ?Combustion characteristics? - ?Condition? - ?Different particle sizes? - ?Mass loss rate? - ?Particles sizes? - ?Pellet? - ?Solid bridges

Classification code: 525.3 Energy Utilization? - ?802.3 Chemical Operations? - ?951 Materials Science

Numerical data indexing: Linear density 7.90E+01kg/m, Percentage 1.00E+01%, Percentage 1.00E+02%, Percentage 1.00E00%, Percentage 1.50E+01%, Percentage 2.00E+01%, Percentage 2.50E+01%, Percentage 3.00E+00%, Percentage 3.00E+01%, Percentage 4.00E+01%, Percentage 5.00E+00%, Percentage 6.50E+01%, Percentage 7.00E+00%, Pressure 2.393E+07Pa, Size 1.00E-03m, Size 4.00E-03m, Size 5.00E-03m, Specific energy 2.706E+04J/kg, Specific energy 4.40E+07J/kg, Time 1.80E+02s, Time 6.00E+02s

DOI: 10.6041/j.issn.1000-1298.2024.01.033

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

37. Design and Experiment of Novel Sprayer for Protecting Middle and Lower Leaves of Cigar Tobacco Plants

Accession number: 20240915637619

Title of translation: 遥控自走式雪茄植株中下层烟叶植保喷雾机设计与试验

Authors: Zhang, Qingoong (1, 2); Chen, Zhiling (1); Du, Wenbin (1); Yang, Jinpeng (3); Liao, Qingxi (1, 2); Yang, Chunlei (3)

Author affiliation: (1) College of Engineering, Huazhong Agricultural University, Wuhan; 430070, China; (2) Key laboratory Agricultural Equipment in Mid-loner Yangtze River, Miniitry Agriculture and Rural Affairt, Wuhan; 430070, China; (3) Tobacco Rerearch Injtituie of Hubei Province, Wuhan; 430030, China

Corresponding author: Yang, Chunlei(ycll93737@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 122-133

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem that the space between ridges in cigar tobacco fields is small due to the tall plants and the growth of leaves, and the production of cigar tobacco leaves requires high color and integrity of tobacco leaves, and the field management requirements cannot damage tobacco leaves, which leads to the difficulty in plant protection of middle and lower tobacco leaves in cigar tobacco plants during production. Combined with the growth characteristics of tobacco leaves, a plant protection device for middle and lower layers of tobacco leaves in cigar plants was designed. The device mainly consisted of a spray system, a crawler chassis and a contml system and other functions. In order to obtain the growth characteristics of tobacco plants, a three-dimensional laser scanner was used to scan them and establish a spatial distribution model of plant leaves in the field. According to the distribution characteristics of tobacco leaves in the field, the overall structure and working mode of the device were determined; combined with the tobacco leaf shape characteristics and plant protection and agronomic requirements, the structure design and analysis of the spraying system were carried out, and the parameter range was determined. According to the requirements of field operations, the dynamic analysis of the crawler chassis and the design of the control system were carried out. The field experiments was carried out, and the parameters of the spray system were optimized by using Box — Behnken. When the spray pressure was 0.65 MPa, the nozzle angle was 20.4°, and the nozzle aperture was 0.4 nun, the vertical direction of the cigar leaf layer was simulated by the vertical droplet distribution measuring instrument. The liquid adhesion performance test showed that the vertical distribution of droplet deposition met the requirements of cigar tobacco leaf plant protection. The field experiments results showed that the coverage rate of the liquid medicine on the front side of the middle and lower layers of the cigar plant was 52% ~83%. and the coverage rate of the backside was 22% ~45%, which can realize the effective spraying of the liquid medicine on the middle and lower layers of the tobacco leaves of the cigar plant. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Remote control

Controlled terms: Chassis? - ?Drops? - ?Plants (botany)? - ?Pneumatics? - ?Spray nozzles? - ?Structural design? - ?Tobacco

Uncontrolled terms: Coverage rate? - ?Crawler chassi? - ?Field experiment? - ?Growth characteristic? - ?Plant protection? - ?Remote control self-propelled? - ?Spray systems? - ?Sprayer? - ?Tobacco leaf? - ?Tobacco plants

Classification code: 408.1 Structural Design, General? - ?631.1 Fluid Flow, General? - ?632.3 Pneumatics? - ?662.4 Automobile and Smaller Vehicle Components? - ?663.2 Heavy Duty Motor Vehicle Components? - ?731.1 Control Systems? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 2.20E+01%, Percentage 4.50E+01%, Percentage 5.20E+01%, Percentage 8.30E+01%, Pressure 6.50E+05Pa

DOI: 10.6041/j.issn.1000-1298.2024.01.011

Funding text: 中国烟草总公司重大专项(110202101059(XJ-08)) 和湖北省烟草公司科技项目(027Y2021 - 006)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

38. UAV Multispcctral Remote Sensing Inversion of Soil Moisture Content Based on Window Size Optimization of Spectral Information at Sampling Points

Accession number: 20240915637367

Title of translation: 基于采样点光谱信息窗口尺度优化的土壤含水率无人机多光谱遥感反演

Authors: Jin, Yahong (1, 2); Wu, Xinmiao (1, 2); Zhen, Wenchao (2, 3); Cui, Xiaotong (1, 2); Chen, Li (4); Qie, Zhihong (1, 2)

Author affiliation: (1) College of Urban and Rural Construction, Hebei Agricultural University, Baoding; 071001, China; (2) Key Laboratory of Water Saving Agriculture in North China, Ministry of Agriculture and Rural Affairs, Baoding; 071001, China; (3) College of Agronomy, Hebei Agricultural University, Baoding; 071001, China; (4) Baoding Irrigation Experimental Station, Baoding; 071000, China

Corresponding author: Qie, Zhihong(qiezhihong@163.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 316-327

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The primary factor in crop growth and one of the fundamental indicators used to monitor the wetness of fields is soil moisture. The relationship between the size of spectral information window of sampling points and soil moisture was mainly studied to solve the problem of soil moisture inversion error caused by spatial heterogeneity. UAV remote sensing tech oology was utilized to acquire inultispectral orthophoto images during the corn filling and wheat seedling stages, under both sprinkler irrigation and border irrigation. Initially, the sliding window method was employed to extract 34 groups of spectral characteristic variables, capturing the average spectral information across various spatial scales. Subsequently, the optimal window size of spectral information at the sampling points was determined by using three machine learning models: extreme gradient Boost (XGBoost), support vector machine regression (SVR), and partial least squares regression (PLSR). Next, the feature variables extracted the 34 groups of spectral features were screened by using the Pearson correlation coefficient feature variable screening method (R) in conjunction with the XGBoost and SVR machine learning models. Subsequently, the feature variables that demonstrated sensitivity to soil water were selected. Lastly, the estimation of soil moisture was conducted. The results indicated that the optimal spectral information window for sampling points under sprinkler irrigation was smaller compared with that under border inigation. Specifically, the optimal window size for sprinkler inigation was ranged from 11 × 1 1 to 21 × 21, while for border inigation, it was ranged from 15 × 15 to 29 × 29. The eigenvariable screening method, employing the Pearson correlation coefficient in combination with machine learning models, can significantly enhance the accuracy of soil moisture invei’sion. Among the five machine learning models (R_XGBoost, R_SVR, XGBoost, SVR, PLSR), the R_XGBoost model exhibited the highest accuracy in estimating soil moisture. The R_XGBoost model achieved R2 values of 0.80 and 0.83, and RMSE values of 1.27% and 0.98% under spray irrigation and border irrigation, respectively. Additionally, the R2 values were 0.76 and 0.79, and the RMSE values were 1.68% and 0.85%, respectively. The accuracy of the soil water inversion models was higher under border irrigation compared with that of sprinkler irrigation. The research result can serve as a valuable reference for information mining and soil moisture monitoring through the analysis of UAV multi-spectral images. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 54

Main heading: Unmanned aerial vehicles (UAV)

Controlled terms: Correlation methods? - ?Learning systems? - ?Least squares approximations? - ?Remote sensing? - ?Soil moisture? - ?Support vector machines

Uncontrolled terms: Feature variable? - ?Inversion? - ?Machine learning models? - ?Machine-learning? - ?Multi-spectral? - ?Remote-sensing? - ?Sampling points? - ?Spectral information? - ?UAV multi-spectral remote sensing? - ?Window Size

Classification code: 483.1 Soils and Soil Mechanics? - ?652.1 Aircraft, General? - ?723 Computer Software, Data Handling and Applications? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics

Numerical data indexing: Percentage 1.27E+00%, Percentage 1.68E+00%, Percentage 8.50E-01%, Percentage 9.80E-01%

DOI: 10.6041/j.issn.1000-1298.2024.01.030

Funding text: 河北省重点研发计划项目 (22327002D, 21327001D) 和国家重点研发计划项目 (2018YFD0300503-15)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

39. Yield Estimation of Winter Wheat Based on Remotely Sensed Multi-parameters and IPSO-WNN

Accession number: 20240915637086

Title of translation: 基于遥感多参数和 IPSO –WNN 的冬小麦单产估测

Authors: Wang, Pengxin (1, 2); Li, Mingqi (1, 2); Zhang, Yue (1, 2); Liu, Junming (3); Zhu, Jian (1, 2); Zhang, Shuyu (4)

Author affiliation: (1) College of Information and Electrical Engineering, China Agricultural University, Beijing; 100083, China; (2) Key Laboratory of Agricultural Machinery Monitoring and Big Data Application, Ministry of Agriculture and Rural Affairs, Beijing; 100083, China; (3) College of Land Science and Technology, China Agricultural University, Beijing; 100193, China; (4) Shaanxi Provincial Meteorological Bureau, Xi’an; 710014, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 154-163

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Wheat is one of the major food crops in China. To further estimate the yield of winter wheat accurately, Guanzhong Plain in Shaanxi Province was used as the study area, vegetation temperature condition index (VTCI), leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR), which were closely related to water stress and photosynthesis at the main growth stage were selected as remotely sensed characteristic parameters, and the improved particle swarm optimized wavelet neural network (IPSO — WNN) was used to improve the shortcomings of gradient descent method which tended to fall into local optimum and construct winter wheat yield estimation model. The results showed that the IPSO - WNN model had a coefficient of determination (R2) of 0. 66 and a mean absolute percentage error (MAPE) of 7. 59%. Compared with the BPNN (R2 = 0.46, MAPE was 11. 80%) and WNN (R2 =0.52, MAPE was 9.80%), the IPSO — WNN can further improve the accuracy of the yield estimation and enhance the robustness of the model. It was explored by sensitivity analysis that the input parameters had a strong influence on winter wheat yield, and it was found that FPAR at the heading – filling stage had the greatest effect on winter wheat yield, followed by VTCI at the jointing stage, LAI at the heading — filling and milk maturity stages and FPAR at the green-up and jointing stages. The I index of winter wheat was obtained from IPSO 一 WNN output, and a yield estimation model between I and statistical yield was constructed to estimate the yield of winter wheat in the Guanzhong Plain. The results showed that the R2 between estimated yield and statistical yield was 0. 63 and root mean square error (RMSE) was 505.50 kg/hm2, and the problem of “ low yield and high estimation” of the yield estimation model was solved. Therefore, the yield estimation model constructed based on IPSO – WNN can estimate the yield of winter wheat in the Guanzhong Plain more accurately. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Sensitivity analysis

Controlled terms: Crops? - ?Gradient methods? - ?Mean square error? - ?Parameter estimation? - ?Particle swarm optimization (PSO)? - ?Plants (botany)? - ?Remote sensing

Uncontrolled terms: Estimation models? - ?Multiparameters? - ?Neural-networks? - ?Particle swarm? - ?Particle swarm optimization? - ?Remotely sensed multi-parameter? - ?Swarm optimization? - ?Wavelet neural network? - ?Winter wheat? - ?Yield estimation

Classification code: 723 Computer Software, Data Handling and Applications? - ?821.4 Agricultural Products? - ?921 Mathematics? - ?921.5 Optimization Techniques? - ?921.6 Numerical Methods? - ?922.2 Mathematical Statistics

Numerical data indexing: Mass 5.055E+02kg, Percentage 5.90E+01%, Percentage 8.00E+01%, Percentage 9.80E+00%

DOI: 10.6041/j.issn.1000-1298.2024.01.014

Funding Details: Number: 42171332, Acronym: NSFC, Sponsor: National Natural Science Foundation of China;

Funding text: 国家自然科学基金项目（42171332）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

40. Inversion of Salt Content in Salinized Soil under Background of Water-saving Transformation Based on Landsat 8

Accession number: 20240915636919

Title of translation: 基于 Landsat?8?的节水改造背景下盐渍化土壤含盐量反演

Authors: Liu, Wei (1, 2); Shi, Haibin (1); Miao, Qingfeng (1); Liu, Xiaozhi (3); Duan, Jie (1); Wang, Yusen (1)

Author affiliation: (1) College of Water Conservation and Civil Engineering, Inner Mongolia Agricultural University, Huhhot; 010018, China; (2) Inner Mongolia Ecological Environment Big Data Company, Huhhot; 010010, China; (3) State Key Laboratory of Wateshed Water Cycle Simulation and Regulation, China Institute of Water Resources and Hydropower Research, Beijing; 100083, China

Corresponding author: Shi, Haibin(shi_haibin@sohu.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 294-304

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to explore the spatial-temporal distribution characteristics and variation rules of soil salt content caused by the reduction of channel lining and drainage water after water-saving transformation in Shenwu irrigated district, fixed-point monitoring of regional soil information was adopted, combined with classical statistics, spatial interpolation and machine learning modeling and inversion, and spectral data was obtained by Landsat 8 satellite. By processing the measured soil salt content, spectral index and band reflectance, using Adaboost regression, BP neural network regression, gradient lifting tree regression, KNN regression, decision tree regression and random forest regression, the spatial inversion model of soil salt content in Shenwu irrigated district was constructed. The optimal inversion model was used to invert the spatial distribution characteristics of soil salt content in Shenwu irrigated district. The results showed that the correlation coefficient was screened by the whole variable single regression method. With nine spectral factors of 0.55, six inversion models of machine learning were constructed using SPSS PRO software, and the accuracy of the six inversion models was compared. The verification set R2 from high to low was random forest regression, gradient lifting tree regression, Adaboost regression, KNN regression, decision tree regression, and BP neural network regression. The random forest regression model had the best fitting accuracy, and the R2 of training set and verification set were 0.834 and 0.86, respectively. It was showed that random forest regression model had better inversion effect. The inversion results showed that the non-salinization soil increased by 39 1.7 kin2, accounting for 21% of the total irrigation area, while the moderate salinization soil, severe salinization soil and saline soid reduced the square by 95.61 km2, 63.37 km2 and 45.7 km2, accounting for 5%, 3% and 2% of the total irrigation area, respectively. In summary, after the completion of the water-saving transformation project, the degree of soil salinization in Shenwu inigated district was reduced, and the area of crop growth security area was increased. However, due to the reduction of channel lining and drainage water, the effect of soil salt leaching was weakened, and soil salt migrated within the irrigation area, the overall soil environment was improved, and salt accumulation occurred in some areas. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 45

Main heading: Landsat

Controlled terms: Adaptive boosting? - ?Decision trees? - ?Irrigation? - ?Machine learning? - ?Metadata? - ?Neural networks? - ?Regression analysis? - ?Remote sensing? - ?Soil surveys? - ?Soils ? - ?Spatial distribution? - ?Water conservation? - ?Water resources

Uncontrolled terms: Inversion models? - ?LANDSAT? - ?Landsat 8? - ?Random forests? - ?Remote sensing inversion? - ?Remote-sensing? - ?Salinisation? - ?Soil salt content? - ?Water-saving? - ?Water-saving transformation

Classification code: 405.3 Surveying? - ?444 Water Resources? - ?483.1 Soils and Soil Mechanics? - ?655.2 Satellites? - ?723 Computer Software, Data Handling and Applications? - ?723.4 Artificial Intelligence? - ?821.3 Agricultural Methods? - ?902.1 Engineering Graphics? - ?921 Mathematics? - ?921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory? - ?922.2 Mathematical Statistics? - ?961 Systems Science

Numerical data indexing: Percentage 2.00E+00%, Percentage 2.10E+01%, Percentage 3.00E+00%, Percentage 5.00E+00%, Size 4.57E+04m, Size 6.337E+04m, Size 9.561E+04m

DOI: 10.6041/j.issn.1000-1298.2024.01.028

Funding Details: Number: 2021YFC3201202-05, Acronym: NKRDPC, Sponsor: National Key Research and Development Program of China; Number: 52269014, Acronym: -, Sponsor: -;

Funding text: 国家重点研发计划项目 (2021YFC3201202-05) 和国家自然科学基金项目 (52269014)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

41. Effects of Soil and Water Conservation Measures on Soil Physical and Chemical Properties in Slope Farmland in Black Soil Region

Accession number: 20240915636583

Title of translation: 黑土区坡耕地水土保持耕作措施对土壤理化性状的影响

Authors: Zhang, Zhongxue (1, 2); Yin, Zhihao (1, 2); Yu, Peizhe (1, 2); Qi, Zhijuan (1, 2); Wei, Yongxia (1, 2); Li, Ao (1, 2)

Author affiliation: (1) School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin; 150030, China; (2) Key Laboratory for Efficient Utilization of Agriculture Water Resources, Ministry of Agriculture and Rural Affairs, Northeast Agricultural University, Harbin; 150030, China

Corresponding author: Qi, Zhijuan(zhijuan.qi@neau.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 282-293

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to explore the effects of different soil and water conservation tillage measures on soil physical and chemical properties in sloping farmland, a field experiment was canied out. Setting transverse tillage (TP), ridge field (RF), deep loosening (SF), transverse tillage + ridge field (TP-R), transverse tillage + deep loosening (TP-S), and ridge field + deep loosening (RF-S) three soil and water conservation tillage measures and three combined tillage measures, and conventional down-slope tillage (CK) as a control. The soil porosity, soil mechanical composition, water stability, soil aggregate stability, soil nutrients and other indicators were analyzed, and the TOPSIS model was used to comprehensively evaluate different soil and water conservation farming measures, and the soil stability and water storage and fertilizer conservation were selected. The effective soil and water conservation practices in farming were investigated. The results showed that during the whole growth period of maize, deep loosening tillage, ridge field and transverse tillage could all increase the soil volume moisture content. The TP-S treatment had the highest volumetric moisture content, and the average volumetric moisture content of the 0 ?40 cm soil layer was increased by 29. 47% compared with that of the CK treatment. RF —S treatment had the largest average porosity, followed by TP — S treatment, and the average porosity was increased by 10. 68% and 9. 25% in turn compared with that of CK treatment. TP — S treatment could significantly improve soil stability, among which the mean mass diameter (MWD), geometric mean diameter (GMD) and macroaggregate content (R0.25) were increased by 12.30%, 19.57% and 13. 97% respectively compared with that of CK treatment. TP — S treatment could improve soil mechanical composition, the content of coarse sand, powder, and clay particles in TP — S treatment was 15. 40%, 26. 89% and 1.90% higher than that of CK treatment, the content of fine sand was 31. 56% lower than that of CK treatment ； the content of IN (inorganic nitrogen), AP (available phosphorus) and AK (available potassium) in TP — S treatment was the highest, compared with that of CK treatment, the content of IN, AP and AK was increased by 42.81% ? 55.32%, 39.69% ?40. 68% and 20.41% ? 25. 45%, respectively. According to the comprehensive evaluation results of the TOPSIS model, the TP — S treatment had the highest degree of fit, more stable soil structure, and better water storage and fertilizer conservation effects, which was a suitable soil and water conservation farming measure in this area. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 52

Main heading: Tillage

Controlled terms: Cultivation? - ?Farms? - ?Fertilizers? - ?Moisture? - ?Moisture determination? - ?Nitrogen? - ?Porosity? - ?Soil conservation? - ?Soils? - ?Stability ? - ?Water conservation

Uncontrolled terms: Black soil regions? - ?Cultivation measures? - ?Ridge fields? - ?Slope farmland? - ?Soil and water conservation? - ?Soil structure? - ?Soil-structure? - ?TOPSIS models? - ?Water storage? - ?Water storage and fertilizer conservation

Classification code: 444 Water Resources? - ?483.1 Soils and Soil Mechanics? - ?804 Chemical Products Generally? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.2 Agricultural Chemicals? - ?821.3 Agricultural Methods? - ?931.2 Physical Properties of Gases, Liquids and Solids? - ?944.2 Moisture Measurements

Numerical data indexing: Percentage 1.23E+01%, Percentage 1.90E+00%, Percentage 1.957E+01%, Percentage 2.041E+01%, Percentage 2.50E+01%, Percentage 3.969E+01%, Percentage 4.00E+01%, Percentage 4.281E+01% to 5.532E+01%, Percentage 4.50E+01%, Percentage 4.70E+01%, Percentage 5.60E+01%, Percentage 6.80E+01%, Percentage 8.90E+01%, Percentage 9.70E+01%, Size 0.00E00m to 4.00E-01m

DOI: 10.6041/j.issn.1000-1298.2024.01.027

Funding text: 国家重点研发计划项目（2021YFD1500802）和东农学者计划学术骨干项目（21XG18）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

42. Experiment on Weed Seed Germination Rate in Soil under Different Flame Temperature Conditions before Sowing of Direct-seeded Rice

Accession number: 20240915637831

Title of translation: 直播稻播前不同土壤火焰温度条件下杂草种子发芽率试验

Authors: Zhou, Zhiyan (1, 2); Li, Xin (1, 3); Huang, Junhao (1, 3); Yang, Deshuai (1, 4); Lin, Jianqin (1, 3); Jiang, Rui (1, 5)

Author affiliation: (1) College of Engineering, South China Agricultural University, Guangzhou; 510642, China; (2) Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou; 510642, China; (3) Guangdong Provincial Key Laboratory of Agricultural Artificial Intelligence, Guangzhou; 510642, China; (4) Guangdong Engineering Research Center for Agricultural Aviation Application, Guangzhou; 510642, China; (5) Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou; 510642, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 134-144

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Effective weed control is an important measure to reduce the risk of stable yields in direct seeded rice, and pre-sowing soil flame treatment is an effective means of suppressing weed seed germination prior to sowing by non-chemical methods. In order to clarify the law of the influence of the temperature field on the germination rate of weed seeds in soil flame treatment, the structural parameters of the header pipe in the fuel diversion component were investigated by using numerical simulation. The results of the numerical simulation and validation test showed that when the inner diameter of the header pipe d was 20 mm and the gas input flow rates were 1. 0 ~ 3.5 m3/h, the maximum flow deviation rates η were within 3.0%, more uniform gas flow distribution between outlet branches. Based on the numerical simulation results, a flame combustion device was designed to study the effects of six types of LPG fuels with input flow rates (1. 0 ~ 3.5 m3/h) on the flame height and the flame temperature distribution, and a full-factorial test was carried out by using the tractor traveling speed, fuel input flow rate, and soil depth as test factors, and the effect of temperature field on the germination pattern of weed seeds was studied using common weed seeds among rice fields. The test results showed that the flame height and the maximum value of flame temperature were both increased with the increase of fuel input flow rates under normal temperature and pressure operating environment； when the tractor traveled at a speed of 2. 36 km/h and the fuel input flow rates were 2.5 m3/h, 3.0 m3/h and 3.5 m3/h, the soil temperature could reach 92.83?C，116.58?C and 156.83?C，respectively; compared with the un-flamed treatment control group, when the soil temperature reached 92.83?C，the germination rate of seeds of Leptochloa chinensis (L.) Nees and Cyperus difformis were significantly reduced at the significance level of α =0.05, but the germination rate of seeds of Digitaria sanguinalis and Eclipta prostrata were not significantly affected, and the germination rate of seeds of the four weeds were significantly reduced when the soil temperature reached 116.58?C and 156.83?C. When the soil temperature reached 156.83?C， the germination of seeds of four weed species Digitaria sanguinalis, Eclipta prostrata, Leptochloa chinensis (L.) Nees and Cyperus difformis were decreased by 94.82%, 87.81%, 86.54% and 84.05%, respectively. The results of the field test showed that the soil flame treatments had significant germination inhibiting effects on Echinochloa crusgalli, Digitaria sanguinalis, Eclipta prostrata, and Cyperus difformis, and their relative weed control rates Y was greater than or equal to 80.00%. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Soil temperature

Controlled terms: Combustion? - ?Cultivation? - ?Flow of gases? - ?Flow rate? - ?Germination? - ?Numerical models? - ?Risk assessment? - ?Soils? - ?Tractors (agricultural)? - ?Tractors (truck) ? - ?Weed control

Uncontrolled terms: Combustion characteristics? - ?Direct-seeded rice? - ?Eclipta prostrata? - ?Flame treatment? - ?Germination rates? - ?Seed germination? - ?Seed germination rate? - ?Soil abatement? - ?Soil temperature? - ?Weed seed

Classification code: 483.1 Soils and Soil Mechanics? - ?631 Fluid Flow? - ?631.1.2 Gas Dynamics? - ?641.1 Thermodynamics? - ?663.1 Heavy Duty Motor Vehicles? - ?821.1 Agricultural Machinery and Equipment? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?914.1 Accidents and Accident Prevention? - ?921 Mathematics? - ?943.2 Mechanical Variables Measurements

Numerical data indexing: Percentage 3.00E+00%, Percentage 8.00E+01%, Percentage 8.405E+01%, Percentage 8.654E+01%, Percentage 8.781E+01%, Percentage 9.482E+01%, Size 0.00E00m to 3.50E+00m, Size 2.00E-02m, Size 3.60E+04m, Volume 2.50E+00m3, Volume 3.00E+00m3, Volume 3.50E+00m3

DOI: 10.6041/j.issn.1000-1298.2024.01.012

Funding text: 岭南现代农业实验室科研项目(NT2021009), 广州市重点研发计划项目(202206010149), 广东省科技计划项目(2021B1212040009) 和江西省井冈山农高区省级科技专项 (20222-051252-02)

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

43. Temporal and Spatial Evolution of Drought Disasters in Shanxi Province under Background of Climate Change

Accession number: 20240915636311

Title of translation: 气候变化背景下山西省气象干旱时空演变特征

Authors: Yao, Ning (1); Jiang, Kunhao (1); Xie, Wenxin (1); Zhang, Dongjran (2); Yang, Xiaojuan (3); Yu, Qiang (4)

Author affiliation: (1) College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi, 712100, China; (2) College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi, 712100, China; (3) Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing; 100081, China; (4) College of Soil and Water Conservation Science and Engineering, Northwest A&F University, Yangling, Shaanxi, 712100, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 1

Issue date: 2024

Publication year: 2024

Pages: 270-281

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Frequent droughts caused serious impacts on ecological resources and agricultural development. In order to reveal the spatial and temporal evolution characteristics of drought in Shanxi Province, based on the month-by-month meteorological data from 24 meteorological stations in Shanxi Province from 197 1 to 2020, the annual trends of each meteorological factor were examined by using the improved Mann — Kendall method, and the FAO56 Penman — Monteith formula was used to calculate the reference crop evapotranspiration (ET0) of reference crop emergence, analyze the characteristics of ET0 and its sensitivity to meteorological factors under the changes of individual meteorological factors, and compare the ability of different drought indices (percentage of precipitation anomaly (Pa), standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI)) in monitoring drought hazards in Shanxi Province at various time scales (monthly, seasonal, and annual scales). The results showed that ET0 was negatively correlated with relative humidity, and the sensitivity of meteorological factors to ET0 was in descending order of relative humidity, daily maximum temperature, wind speed at 2 in, daily minimum temperature, daily average temperature, with a fluctuating and decreasing trend of ET0.SPEI was able to reflect the drought condition of Shanxi Province effectively in multiple time scales, which was an effective tool for drought monitoring in this region. Comparing the three drought indices at monthly, seasonal and annual scales, Pa was less effective in detecting droughts, SPI and SPEI differed significantly in some geographic regions, and overall, SPEI performed better in detecting droughts in most regions； at the SPEI — 1 scale, the frequency of each drought class in descending order was light drought (14.8%), moderate drought (10.6%), severe drought (5.6%), extreme drought (1.9%), with the highest occurrence rate of drought in March (34%) and the lowest in December (31.8%), and more severe drought conditions in Liiliang City, Jinzhong City, and Datong City； under the SPEI — 3 scale, the frequency of seasonal drought, in descending order, was in the fall (33.5%), summer (32.5%), spring (31.9%), and winter (31.4%), and Datong City, Changzhi City had the highest frequency of special drought and the most serious drought, and Xinzhou City, Shuozhou City, and Liiliang City had the highest frequency of light, moderate, and severe drought, respectively; at the SPEI — 12 scale, the frequencies of light, moderate, severe, and special drought were 14.8%, 10.5%, 5.4%, and 2.3%, respectively, and SPEI — 12 recognized more sites with severe and special drought compared with SPEI — 1 and SPEI — 3, and based on the travel theory, it was concluded that the frequency of drought in southern Shanxi Province was higher than that of other provinces in China. It was concluded that the frequency of drought was more frequent in the southern part of Shanxi Province, the drought in the eastern part lasted longer and the severity of drought was greater, and the peak of drought mainly occurred in the northern and sou them parts of Shanxi Province. Due to the fluctuating decline of the mean annual precipitation and the overall increase of the mean annual temperature, the climate in Shanxi Province tended to be warm and dry, the drought in the southern and northern parts of Shanxi Province would be aggravated, the drought in the central part of Shanxi Province would be slowed down, and the whole-area drought was still very possible. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 43

Main heading: Drought

Controlled terms: Crops? - ?Evapotranspiration? - ?Stream flow? - ?Wind

Uncontrolled terms: Drought characteristics? - ?Drought conditions? - ?Drought index? - ?High frequency HF? - ?Meteorological factors? - ?Precipitation anomalies? - ?Reference crop evapotranspirations? - ?Shanxi province? - ?Standardized precipitation index? - ?Travel theory

Classification code: 407.2 Waterways? - ?443.1 Atmospheric Properties? - ?443.3 Precipitation? - ?444 Water Resources? - ?631.1 Fluid Flow, General? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 1.05E+01%, Percentage 1.06E+01%, Percentage 1.48E+01%, Percentage 1.90E+00%, Percentage 2.30E+00%, Percentage 3.14E+01%, Percentage 3.18E+01%, Percentage 3.19E+01%, Percentage 3.25E+01%, Percentage 3.35E+01%, Percentage 3.40E+01%, Percentage 5.40E+00%, Percentage 5.60E+00%, Size 5.08E-02m

DOI: 10.6041/j.issn.1000-1298.2024.01.026

Funding text: 国家自然科学基金项目（52209070）和国家外国专家项目（QN2022172005L）

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village