2024年第11期

2024年第11期

2024年第11期共收录48篇

1. Multi-task Visual Perception Method in Dragon Orchards Based on OrchardYOLOP

Accession number: 20244717414293

Title of translation: 基于 OrchardYOLOP 的火龙果园多任务视觉感知方法

Authors: Zhao, Wenfeng (1); Huang, Yuanjue (1); Zhong, Minyue (1); Li, Zhenyuan (1); Luo, Zitao (1); Huang, Jiajun (1)

Author affiliation: (1) College of Electronic Engineering, College of Artificial Intelligence, 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: 11

Issue date: November 2024

Publication year: 2024

Pages: 160-170

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In the face of challenges such as complex terrains, fluctuating lighting, and unstructured environments, modern orchard robots require the efficient processing of a vast array of environmental information. Traditional algorithms that sequentially execute multiple single tasks are limited by computational power which are unable to meet these demands. Aiming to address the requirements for real-time performance and accuracy in multi-tasking autonomous driving robots within dragon fruit orchard environments. Building upon the YOLOP, focus attention convolution module was introduced, C2F and SPPF modules were employed, and the loss function for segmentation tasks was optimized, culminating in the OrchardYOLOP. Experiments demonstrated that OrchardYOLOP achieved a precision of 84. 1 % in target detection tasks, an mloU of 89. 7% in drivable area segmentation tasks, and an mloU increased to 90. 8% in fruit tree region segmentation tasks, with an inference speed of 33. 33 frames per second and a parameter count of only 9. 67 X 10 . Compared with the YOLOP algorithm, not only did it meet the realtime requirements in terms of speed, but also it significantly improved accuracy, addressing key issues in multi-task visual perception in dragon fruit orchards and providing an effective solution for multi-task autonomous driving visual perception in unstructured environments. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Orchards

Controlled terms: Agricultural robots? - ?Gluing? - ?Image coding? - ?Semantic Segmentation? - ?Vision

Uncontrolled terms: Autonomous driving? - ?Complex terrains? - ?Dragon orchard? - ?Lighting environment? - ?Multi tasks? - ?Objects detection? - ?Semantic segmentation? - ?Unstructured environments? - ?Visual perception? - ?YOLOP

Classification code: 101.5 ? - ?1106.3.1 ? - ?1106.8 ? - ?210 ? - ?214 ? - ?731.6 Robot Applications? - ?741.2 Vision? - ?821.2 Agricultural Chemicals? - ?821.4 Agricultural Products

Numerical data indexing: Percentage 1.00E00%, Percentage 7.00E+00%, Percentage 8.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.018

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

2. Research on FDC YOLO v8 Underwater Biological Object Detection Method Improved by Deformable Convolution

Accession number: 20244717414311

Title of translation: 基于改进可变形卷积的FDC-YOLO v8水下生物目标检测方法研究

Authors: Yuan, Hongchun (1); Li, Chunqiao (1)

Author affiliation: (1) School of Information, Shanghai Ocean Vniversity, Shanghai; 201306, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 140-146

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Underwater biological target detection is a crucial technology for achieving automation in underwater robotic fishing. Aiming to address issues such as object overlap, occlusion, and false detections, missed detections caused by small object scales in underwater biological object detection tasks, an underwater biological object detection algorithm, FDC — YOLO v8 was proposed based on an improved YOLO v8n. Firstly, the FDC module was incorporated, which utilized deformable convolution networks in the backbone network to enhance the model’s feature extraction capability and enrich the diversity of extracted features. Secondly, the FrSAConv module, integrating fractional Fourier transform and spatial attention mechanism, was introduced to further separate diverse object features and enhance the model’s perceptual ability towards various features. Finally, the Wise — IoU loss function was introduced as the bounding box loss function to better address issues related to object imbalance and Scale differences. The experiments were conducted by using the RUIE dataset, which included four types of underwater organisms; echinus, starfish, holothurian, and scallops. Experimental results demonstrated that the improved FDC — YOLO v8 achieved an mAP of 85. 3%, a 2. 6 percentage points improvement over the baseline model. The inference speed can reach 769 frames per second, showcasing better Performance in underwater object detection of marine organisms with challenged such as object overlap, occlusion, and small-scale objects. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Convolution

Controlled terms: Fourier transforms? - ?Image segmentation? - ?Molluscs? - ?Shellfish

Uncontrolled terms: Biological objects? - ?Biological recognition? - ?Convolutional networks? - ?Deformable convolutional network? - ?Fractional Fourier transforms? - ?Loss functions? - ?Objects detection? - ?Underwater biological recognition? - ?Wise — IoU? - ?YOLO v8n

Classification code: 103 ? - ?1106.3.1 ? - ?1201.3 ? - ?471 Marine Science and Oceanography? - ?716.1 Information Theory and Signal Processing

Numerical data indexing: Percentage 3.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.015

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

3. Classification Model of Fish Feeding Intensity Based on MobileViT CBAM BiLSTM

Accession number: 20244717414301

Title of translation: 基于 MobileViT-CBAM-BiLSTM 的开放式养殖环境鱼群摄食强度分类模型

Authors: Xu, Lihong (1, 2); Huang, Zhizun (1); Long, Wei (1); Jiang, Linhua (1); Tong, Xin (1)

Author affiliation: (1) School of Information Engineering, Huzhou University, Huzhou; 313000, China; (2) College of Electronics and Information Engineeriing, Tongji University, Shanghai; 201804, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 147-153

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Precise feeding technology for fish ingestion is a key technology to achieve intelligent aquaculture. However, most of the precise feeding model is based on indoor aquaculture ponds with clear water quality, which are not suitable for outdoor open farming environments. In view of the actual situation, a set of detailed open pond dataset through water perspective acquisition was constructed, and the dataset was augmented to increase its diversity, and then the BiLSTM bidirectional recurrent neural network was embeded on the basis of the lightweight neural network MobileViT, so as to improve the memory ability of the model for video sequence data in a long period of time, and the CBAM attention module was combined with the MV2 module to design the CBAM — MV2 module, and then the CBAM — MV2 module was added to different layers of the model for experiments to obtain the most reasonable improvement scheme. Finally, an improved MobileViT — CBAM— BiLSTM fish feeding behavior classification model was proposed, which improved the prediction ability, robustness and generalization performance of the model, and realized the three classification of fish feeding behavior. The experimental results showed that the improved MobileViT was significantly better than previous in the collected video frame dataset, with an accuracy of 98. 61%, 98. 79% for Macro-Fl, which was 6. 33 percentage points for accuracy, 6.75 percentage points for Macro-Fl compared with the original MobileViT. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Fish

Controlled terms: Failure analysis? - ?Fish ponds? - ?Macroinvertebrates? - ?Recurrent neural networks

Uncontrolled terms: BiLSTM? - ?CBAM? - ?Classification model of fish feeding intensity? - ?Classification models? - ?Feeding behavior? - ?Feeding technology? - ?Key technologies? - ?Mobilevit? - ?Percentage points? - ?Precision feeding

Classification code: 103 ? - ?1101 ? - ?214.1 ? - ?821.4 Agricultural Products? - ?822.3 Food Products

Numerical data indexing: Percentage 6.10E+01%, Percentage 7.90E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.016

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

4. Automatic Extraction of Phenotypic Parameters from Anthurium andraeanum Linden Based on YOLO v8 and CycleGAN

Accession number: 20244717414346

Title of translation: 基于 YOLO v8 和 CycleGAN 的红掌植株表型参数自动提取方法

Authors: Lu, Peng (1); Sun, Tianwen (1); Chen, Ming (1); Wang, Zhenhua (1); Zheng, Zongsheng (1)

Author affiliation: (1) College of Information, Shanghai Ocean University, Shanghai; 201306, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 154-159 and 319

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Phenotypic parameters of plants are quantitatively indicated, describing the morphology, structure, and physiological characteristics of plants, unveiling the growth patterns and relationships with environmental factors. Issues such as significant data errors, plant damage, high costs, and extensive data volume were exhibited by existing manual measurement and laser scanning-based methods for extracting plant phenotypic parameters. Therefore, an automatic extraction method for phenotypic parameters of Anthurium andraeanum Linden plants based on YOLO v8 and CycleGAN was proposed. The method included the follows; YOLO v8 was enhanced with the convolutional block attention module to improve the model’s feature extraction capabilities for detecting and segmenting Anthurium andraeanum Linden leaves; the Grabcut algorithm was utilized to eliminate background features from segmented images, and the VGG model was employed for classification to distinguish intact and missing Anthurium andraeanum Linden leaves; the convolutional block attention module and feature pyramid network were introduced into the CycleGAN generator to enhance multi-scale feature extraction capabilities, incorporating the SmoothLl loss function to enhance model stability and repair missing Anthurium andraeanum Linden leaves; a phenotypic parameters extraction algorithm (PPEA) was proposed to automatically extract leaf length, leaf width, and leaf area of Anthurium andraeanum Linden plants. The proposed methods were compared and analyzed by using a dataset of 650 self-collected images. Experimental results demonstrated the effectiveness of the proposed approach in automatically extracting phenotypic parameters of Anthurium andraeanum Linden plants. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Image segmentation

Controlled terms: Physiological models

Uncontrolled terms: Anthurium andraeanum linden? - ?Automatic extraction? - ?Cyclegan? - ?Extraction capability? - ?Morphology structures? - ?Parameters extraction? - ?Phenotypic parameter extraction? - ?Structure characteristic? - ?Targets detection? - ?YOLO v8

Classification code: 101.1 ? - ?1106.3.1

DOI: 10.6041/j.issn.1000-1298.2024.11.017

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

5. Lightweight Dense Multi-scale Attention Network for Identification of Rust on Wheat Leaves

Accession number: 20244717414292

Title of translation: 基于轻量级密集多尺度注意力网络的小麦叶部锈病识别方法

Authors: Bao, Wenxia (1); Zhao, Shiyi (1); Huang, Linsheng (1); Liang, Dong (1); Hu, Gensheng (1)

Author affiliation: (1) National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University, Hefei; 230601, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 21-31

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Artificial identifieation of wheat rust is costly and inefficient, and can no longer meet the needs of modern agricultural production. A lightweight dense multi-scale attention network model called Mobile — DMSANet was presented for the automatic identifieation of rust on wheat leaves (stripe rust and leaf rust) from images of natural scenes taken in the field. In the input layer of the network, a fast subsampling block (FSB) was used to improve the feature expression ability of the network without adding computational cost. In the feature extraction layer, three lightweight blocks called dense multi-scale attention (DMSA) blocks were used to extract the features of rust on wheat leaves. In the DMSA block, a multi-scale three-way convolution (MSTC) layer was designed to get different scales for the receptive fields, in order to improve the expressive ability of the network and its ability to perceive the features of rust disease at different scales. Six MSTC layers were used to achieve feature reuse by dense connections in the DMSA block, an approach that not only greatly reduced the number of parameters of the network but also improved the feature extraction ability for similar diseases. A coordinated attention (CA) block was also introduced to the DMSA block to increase the sensitivity to positional Information and suppress background Information in the image. The Output layer of the network used a Softmax function to classify rust on wheat leaves. The results showed that the reeognition accuracy of Mobile — DMSANet model on the test dataset was 96. 4%, which was higher than that of other models. Mobile — DMSANet had only 454 000 parameters, less than for other lightweight models. The proposed model can be used for the automatic identification of rust on wheat leaves using mobile devices. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Convolution

Controlled terms: Convolutional neural networks? - ?Multilayer neural networks

Uncontrolled terms: Convolutional neural network? - ?Disease identification? - ?Leaf rust? - ?Lightweight convolutional neural network? - ?Molile - DMSANet? - ?Multi-scales? - ?Stripe rust? - ?Wheat leaf rust? - ?Wheat leaves? - ?Wheat stripe rust

Classification code: 1101 ? - ?1101.2.1 ? - ?716.1 Information Theory and Signal Processing

Numerical data indexing: Percentage 4.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.002

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

6. Spatial-temporal Divergence of Cultivated Land Use in Different Main Functional Areas from Perspective of Functional and Spatial Form

Accession number: 20244817420372

Title of translation: 功能与空间形态视角下不同主体功能区耕地利用时空分异特征

Authors: Zhu, Qingying (1, 2); He, Gengyi (1); Chen, Kun (3); Chen, Yinrong (4); Wang, Yulin (1)

Author affiliation: (1) School of Public Management, South China Agricultural University, Guangzhou; 510642, China; (2) Key Lahoratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources, Qingdao; 266101, China; (3) School of Economics and Management, Hubei Polytechnic University, Huangshi; 435003, China; (4) College of Public Administration, 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: 11

Issue date: November 2024

Publication year: 2024

Pages: 375-390

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Studying the spatial-temporal divergence eharacteristics of cultivated land use functions and spatial forms in different functional areas can provide scientific basis for sustainable management and utilization of cultivated land, as well as regional economic and social sustainable development. Taking all districts (counties) in Hubei Province as the research object, cultivated land use functions and spatial forms of different main functional areas were evaluated from 1995 to 2019 by using data from social economy, natural geography, agricultural production etc., and the spatiot-emporal evolution eharacteristics were analyzed. The results indicated that from 1995 to 2019, the production, social,eeological and Overall functional forms of cultivated land showed characteristics of inverted “N” shaped, “W” shaped, “V” shaped, and “V” shaped ehanges over time respeetively. In terms of spatial distribution characteristics, the production, eeological and overall funetions were stronger in western Hubei than that in eastern Hubei, while the spatial differentiation of social funetions was relatively small. On the main functional area, the production funetion was not significantly different between the key development areas and the main agricultural production areas, but it was significantly stronger than the eeological funetion areas; the social funetion was the strongest in eeological funetion areas and the weakest in the key development areas, while the eeological funetion and overall funetion were the strongest in the main agricultural production areas and the weakest in the eeological funetion areas. From 1995 to 2019, the number of cultivated land, landscape pattern, and spatial form exhibited characteristics of inverted “N” shaped, “V” shaped, and “N” shaped ehanges over time respeetively. In terms of spatial distribution characteristics, the quantity form showed that the central Hubei region were stronger than the western and eastern Hubei regions, while there was a little difference between the western and eastern Hubei regions. The landscape pattern and spatial form showed that the central Hubei region was the highest and the western Hubei region was the lowest. The quantity form values were relatively high in the key development areas and the main agricultural production areas, and the landscape pattern and spatial form were manifested as the largest agricultural produet production area, followed by key development areas, and the smallest eeological funetion area, and the phenomenon was very obvious. The overall form of cultivated land use showed a “V” shaped trend over time; in terms of spatial distribution characteristics, under the combined influence of cultivated land use funetion and spatial form, the overall form of cultivated land use showed a differentiation pattern with the highest in central Hubei and relatively lower in eastern and western Hubei. The main funetion were manifested as the largest agricultural produet production area, followed by key development areas, and the smallest eeological funetion area. It was recommended that different functional zones had significant heterogeneity in social and economic conditions, functional positioning and cultivated land resource endowment, so differentiated regulatory strategies should be adopted to optimize the functional and spatial forms of cultivated land use, serving the sustainable use of cultivated land and the sustainable development of Hubei Province’s economy and society. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Agricultural economics

Controlled terms: Sustainable agriculture

Uncontrolled terms: Analysis method? - ?Condition index? - ?Cultivated land use form? - ?Cultivated lands? - ?Functional zones? - ?Hubei Province? - ?Ill-condition index analyze method? - ?Ill-conditions? - ?Index analysis? - ?Main functional zone ? - ?Spatial temporals? - ?Spatial-temporal divergence

Classification code: 1501.1 ? - ?911.2 Industrial Economics

DOI: 10.6041/j.issn.1000-1298.2024.11.037

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

7. Food Waste Acidification Liquid as Carbon Source for Wastewater Denitrification

Accession number: 20244817420393

Title of translation: 不同产酸类型餐厨酸化液作为污水反硝化碳源的性能研究

Authors: Zheng, Yonghui (1); Ren, Yuying (2); Wang, Zhenbao (3); Lu, Yanjuan (3); Dong, Renjie (1); Guo, Jianbin (1)

Author affiliation: (1) College of Engineering, China Agricultural University, Beijing; 100083, China; (2) College of Resources and Environmental Sciences, China Agricultural University, Beijing; 100193, China; (3) Beijing Fairyland Environmental Technology Co., Ltd., Beijing; 100085, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 446-452

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The acidified liquid of food waste had a high concentration of organic acids, providing an additional carbon source for the denitrification process in wastewater treatment, potentially alleviating the common problem of carbon source scarcity in urban sewage treatment plants in China. Based on fully mixed anaerobic fermentation reactors, the effects of different pH values, organic loading rates (OLR), hydraulic retention times (HRT) on the anaerobic acidification characteristics of food waste under continuous operation were investigated. By regulating the types of anaerobic acid production, different types of acidification liquids were obtained to evaluate their performance as additional carbon sources for wastewater denitrification. The results indicated that controlling the pH value at 6. 0 and the OLR at 15. 0 g/(L-d) yielded the maximum production of TVFAs at 50. 05 g/L, with butyric acid fermentation being predominant. When the pH value was controlled at 5.0, acetate-type fermentation occurred, exhibiting the optimal denitrification rate of 7. 62 mg/(g.h), which was between that of glucose (5. 39 mg/(g-h)) and sodium acetate (9.47 mg/(g-h)). At equivalent COD levels, the denitrification capability of the acidified liquid of food waste (0. 21 g/g) was 84% of that of sodium acetate. Therefore, food waste acidification liquid represented a sustainable, low-energy and cost-effective renewable carbon source with significant market and application potential. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Denitrification

Controlled terms: Acidification? - ?Butyric acid? - ?Sewage treatment plants? - ?Wastewater treatment

Uncontrolled terms: Acidified liquids? - ?Acidogenic fermentation? - ?Additional carbon source? - ?Anaerobics? - ?Carbon source? - ?Food waste? - ?Organic loading rates? - ?Organics? - ?pH value? - ?Sodium acetate

Classification code: 451.2 Air Pollution Control? - ?451.4 ? - ?802.2 Chemical Reactions? - ?804.1 Organic Compounds? - ?822.2 Food Processing Operations

Numerical data indexing: Mass 0.00E00kg, Mass 2.10E-02kg, Mass 3.90E-05kg, Mass 6.20E-05kg, Mass 9.47E-06kg, Mass density 5.00E+00kg/m3, Percentage 8.40E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.042

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

8. Lightweight Salmon Detection Model Based on Improved YOLO v7

Accession number: 20244817420479

Title of translation: 基于改进YOLO v7的鲑鱼检测模型轻量化研究

Authors: Zheng, Rongcai (1); Tan, Dingwen (1, 2); Xu, Qing (2); Chen, Dayong (1); Yuan, Kexin (1)

Author affiliation: (1) Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang), Zhanjiang; 524013, China; (2) College of Mechanical Engineering, Guangdong Ocean University, Zhanjiang; 524088, China

Corresponding author: Xu, Qing(xuqing@gdou.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 132-139

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to achieve rapid and accurate identification of salmon in complex underwater environments, a lightweight salmon detection model, YOLO v7 - CSMRep, was proposed based on YOLO v7. Firstly, by adopting the Stem module, the first four convolutional operations in the backbone layer were merged into an efficient convolutional operation, reducing the computational load of the model. Secondly, the ELAN and ELAN - H modules of the YOLO v7 network were replaced with the multidirectional reparameterization (MRep) module, which enhanced the one-way feature extraction capability while greatly reducing parameters and calculations. Finally, at the end of the backbone layer, the convolutional block attention module (CBAM) was integrated to enhance the network’s spatial and channel feature extraction capabilities. The experimental results showed that the improved model’s volume, parameter count, and computational load were reduced by 4.28%, 5.29% and 31.30%, respectively. The F1 score and mAP0.5were increased by 0.5 and 0.7 percentage points, and reached 93. 1% and 97. 1%, respectively. Additionally, the frame rate was increased by 15. 41%, and reached 140. 8 f/s. Compared with that of YOLO v5s, YOLO v6s, YOLO v7, YOLO v7 - tiny, and YOLO v8s models, the mAP0.5was improved by 1.0, 2.0, 0.7, 0.8, and 1.2 percentage points, respectively. Therefore, the method proposed can rapidly and accurately identify salmon and provide technical support for biomass monitoring in deep-sea aquaculture. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 37

Controlled terms: Aquaculture? - ?Convolution

Uncontrolled terms: Computational loads? - ?Convolutional block attention module? - ?Deep sea? - ?Deep-sea aquaculture? - ?Detection models? - ?Multi-directional reparameterization? - ?Reparameterization? - ?Salmon detection? - ?Stem module? - ?YOLO v7

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

Numerical data indexing: Percentage 1.00E00%, Percentage 3.13E+01%, Percentage 4.10E+01%, Percentage 4.28E+00%, Percentage 5.29E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.014

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

9. Trade-off and Synergy Relationships and Regional Regulation of Multifunctional Cultivated Land in Henan Province

Accession number: 20244817420374

Title of translation: 河南省耕地多功能权衡-协同关系与分区管制研究

Authors: Zhao, Suxia (1); Li, Zhenzhen (1); Wang, Bing (2)

Author affiliation: (1) College of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo; 454000, China; (2) Henan Institute of Land and Resources Surveying and Planning, Zhengzhou; 450016, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 363-374

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The research on the trade-off synergy relationship of multifunctional cultivated land is of great significance for protecting cultivated land resources, ensuring food security, maintaining ecological security, and promoting rural revitalization. Taking 105 counties in Henan Province as the research object, and methods such as Spearman rank correlation analysis and K — means clustering analysis were used to study the multifunctional level of cultivated land in Henan Province from 2000 to 2020 and its trade-off and synergy relationship. The results showed that from 2000 to 2020, the multifunctional index of cultivated land in Henan Province showed an overall upward trend, showing a spatial pattern of “high in the east and low in the west”, and different spatiotemporal differentiation characteristics were observed among various functions. The grain production function in the eastern region was strong, while the ecological service function in the western region was excellent. The overall economic contribution function was declining, and although the social security function was weak, it was gradually improving. The spatiotemporal differences in the trade-off synergy relationship of multifunctional cultivated land were significant, and the interactions between multiple functions showed a characteristic of weakened synergy and intensified trade-offs, especially the significant trade-off between food production and economic contribution functions, as well as ecological service functions. Based on the dominant functional types of cultivated land and the characteristics of multifunctional coupling coordination, Henan Province was divided into four types of functional zones; modern agricultural demonstration zone, urban agricultural leisure zone, ecological agricultural construction zone, and modern agricultural construction zone, and differentiated control measures were proposed. The research result had certain theoretical and practical significance for guiding the rational allocation of cultivated land in major grain producing areas and improving the efficiency of diversified utilization of cultivated land. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 42

Main heading: Abiotic

Controlled terms: Agricultural economics? - ?Food security? - ?Rational functions

Uncontrolled terms: Cultivated lands? - ?Ecological services? - ?Henan Province? - ?Multi-functions? - ?Multifunction of cultivated land? - ?Multifunctionals? - ?Regional regulation? - ?Service functions? - ?Trade off? - ?Trade-off and synergy relationship

Classification code: 1201 ? - ?1502.2 ? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?822 Food Technology? - ?911.2 Industrial Economics

DOI: 10.6041/j.issn.1000-1298.2024.11.036

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

10. Lightweight Object Detection Method for Panax notoginseng Based on PN - YOLO v8s - Pruned

Accession number: 20244917476531

Title of translation: 基于PN-YOLO v8s-Pruned的轻量化三七收获目标检测方法

Authors: Wang, Faan (1, 2); He, Zhongping (1, 2); Zhang, Zhaoguo (1, 2); Xie, Kaiting (2, 3); Zeng, Yue (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 of Chinese Medicinal Materials, University of Yunnan Province, Kunming; 650500, China; (3) Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming; 650500, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 171-183

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order lo realize the adaptive grading conveyance and real-time monitoring of harvesting status in the process of Panax notoginseng combined harvesting operation, focusing on the characteristics of Panax notoginseng root-soil complex and the complex field harvesting conditions, a Panax notoginseng object detection method based on YOLO v8s and suitable for deployment on the Jetson Nano was proposed. Based on the accurate recognition of Panax notoginseng by YOLO v8s, the channel pruning algorithm was utilized to formulate a corresponding pruning strategies for its new model structural characteristics, which ensured the accuracy and improved the real-time detection performance at the same time. The improved model was deployed to Jetson Nano by using the TensorRT inference acceleration framework, which realized the flexible deployment of the Panax notoginseng object detection model. The experimental results showed that the mean average precision of the improved PN — YOLO v8s — Pruned model on the host side was 93. 71%, although it was decreased by 0. 94 percentage points compared with that of the original model, the number of parameters, computational complexity, and model size were 39.75%, 57.69%, and 40.25% of the original model, respectively, and the detection speed was increased by 44.26%. Compared with other models, the improved model demonstrated superior comprehensive detection performance in terms of computational complexity, detection accuracy, and realtime performance. After deployment at the Jetson Nano, the improved model had a detection speed of 18. 9 frames per second, which was 2. 7 times higher than before acceleration and 5. 8 frames per second higher than the original model, and the deployment detection effect was better than the original model. The results of the bench tests showed that the mean average precision of Panax notoginseng detection was more than 87% under four conveyor separation harvesting conditions. The average accuracy of the Panax notoginseng counting under different conveyor separation harvesting conditions and different flow levels reached 92. 61% and 91.76%, respectively. The field test results showed that the mean average precision of Panax notoginseng detection was more than 84%, and the average accuracy of the Panax notoginseng counting reached 88.11%, which could meet the detection requirements of Panax notoginseng under complex field harvesting conditions, and could provide technical support for the monitoring system of harvesting quality and the adaptive grading transportation system of combined harvesting operation based on edge computing equipments. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Conveyors

Controlled terms: Health risks? - ?Risk analysis? - ?Risk assessment? - ?Tensors

Uncontrolled terms: Channel pruning? - ?Complex harvesting condition? - ?Condition? - ?Harvesting operations? - ?Jetson nano? - ?Object detection method? - ?Objects detection? - ?Original model? - ?Panax notoginseng? - ?YOLO v8s

Classification code: 102.1.2.1 ? - ?1108 ? - ?1201.1 ? - ?1201.14 ? - ?1201.4 ? - ?1202 ? - ?692.1 Conveyors? - ?914.1 Accidents and Accident Prevention

Numerical data indexing: Percentage 3.975E+01%, Percentage 4.025E+01%, Percentage 4.426E+01%, Percentage 5.769E+01%, Percentage 6.10E+01%, Percentage 7.10E+01%, Percentage 8.40E+01%, Percentage 8.70E+01%, Percentage 8.811E+01%, Percentage 9.176E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.019

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

11. “Influences of Climate Change on Productivity of Winter Wheat and Summer Maize Rotation System in Huang-Huai-Hai Plain

Accession number: 20244817420399

Title of translation: 未来气候变化对黄淮海冬小麦-夏玉米轮作系统生产力影响

Authors: Dong, Wenbiao (1, 2); Feng, Wenzhe (1, 2); Qu, Mengyu (1, 2); Feng, Hao (2, 3); Yu, Qiang (3, 4); He, Jianqiang (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; (3) State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Water and Soil Conservation, Chinese Academy of Science, Ministry of Water Resource, Shaanxi, Yangling; 712100, China; (4) Key Laboratory of Eco- Environment and Meteorology for the Qinling Mountains and Loess Plateau, Shaanxi Provincial Meteorological Bureau, Xi’an; 710016, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 429-445

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: It is of great significance to explore the influences of climate change on crop phenology and yield of the rotation system of winter wheat and summer maize in the Huang-Huai-Hai Plain, a major grain production base in China, for guaranteeing the food security of China. The APSIM-Wheat and APSIM-Maize models (V 7. 6) were calibrated and verified based on experimental data of multiple years and multiple sites, which were obtained based on literature review. Then, future meteorological data predicted by ten different global climate models (GCMs) in the CMIP6 dataset were used to drive the verified APSIM models to simulate the changes of phenology and yield of winter wheat and summer maize in the time periods of 2021—2060 (2040s) and 2061—2100 (2080s) under two greenhouse gas emission scenarios of SSP2 —4. 5 and SSP5-8. 5. Based on the analyses with multiple linear regression and random forest model, the positive and negative effects of climatic factors and change of crop reproductive stage on crop yield were analyzed and their importance was clarified. The result showed that compared with the baseline period (1981—2020), the vegetative stage of winter wheat was shortened, the reproductive stage was prolonged, and wheat yield was increased. These changes were more obvious under the SSP5 —8. 5 than that under the SSP1-2. 6 scenario. The vegetative and reproductive stages of summer maize were both shortened, and maize yield was increased. However, compared with SSP2-4. 5, maize yield would be reduced under the SSP5 —8. 5 scenario. Compared with SSP2 —4. 5, the total growth period of winter wheat-summer maize rotation system was shortened, the annual yield was increased, and the proportion of winter wheat yield was increased under SSP5 —8.5 scenario. In the future, winter wheat yield was mainly positively correlated with solar radiation, daily mean temperature, and cumulative precipitation during the whole growing season. However, the increase of daily mean temperature and cumulative precipitation was unfavorable to yield increase in 2080s under the SSP5 —8. 5 scenario. Summer maize experienced the similar changes as winter wheat under future climate change, but daily mean temperature had a negative effect on maize yield. Based on the random forest model, the length of winter wheat reproductive stage and accumulated precipitation in the whole growing season had the greatest impacts on winter wheat yield. At the same time, C02 concentration, daily average temperature, and accumulated precipitation in the whole growing season had the greatest impacts on summer maize yield. Future climate change would prolong winter wheat reproductive stage and shorten summer maize reproductive stage, but increase winter wheat and summer maize yields in the Huang-Huai-Hai Plain. However, the positive effects of temperature and precipitation on crop yield would become negative over time, resulting in a reduction of summer maize yield in 2080s under the SSP5 —8. 5 scenario. In general, crop yield mainly would depend on the synergistic effect of climate change and the change of crop growing stage. The results would provide a scientific base and theoretical guidance for the management and the adaption to future climate change of the rotation system of winter wheat and summer maize in the Huang-Huai-Hai Plain of China. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 48

Main heading: Precipitation (meteorology)

Controlled terms: Crop rotation? - ?Regression analysis

Uncontrolled terms: Crop yield? - ?Huang-huai-hai plain? - ?Maize yield? - ?Mean temperature? - ?Phenology? - ?Reproductive stage? - ?Summer maize? - ?Winter wheat? - ?Winter wheat yields? - ?Yield

Classification code: 1202.2 ? - ?443.3 Precipitation? - ?821.4 Agricultural Products

DOI: 10.6041/j.issn.1000-1298.2024.11.041

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

12. Design and Test of Active Control System for Soil Compaction of High Speed No-tillage Maize Planter

Accession number: 20244817420373

Title of translation: 高速免耕玉米播种单体镇压力主动调控系统设计与试验

Authors: Fu, Zuoli (1); Gong, Zhichao (1); Chu, Qingxin (1); Li, Haiyu (1); Zhang, Molin (1); Huang, Yuxiang (1)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 273-284

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: It is difficult to guarantee the stability of soil compaction system under the condition of high speed no-tillage seeding. Therefore, a technical scheme of automatic soil compaction control was proposed, and the electro- hydraulic control system for soil compaction of maize planter was designed. The overall structure of the system was proposed, and the pressure control process was determined through the mechanical analysis of the movement of the seeding monomer and the interaction between suppression wheel and soil. The electro — hydraulic control system design and hardware selection were carried out. AMEsim simulation analysis and step response test were used respectively to design the hydraulic actuator and electronic control system. The results showed that compared with the traditional mechanical regulation, the adjustment accuracy and stability of the hydraulic actuator using PID control were improved. The mean adjustment time of the control system for soil compaction was 1.9 s, the mean steady-state error was 1. 9 N, and the mean overshoot was 2. 0% . It was obviously better than mechanical control. Sinusoidal surface soil trough verification test was adopted, and comparative experimental study was carried out on the influence of different adjustment methods and surface conditions on the stability of soil compaction. The results showed that when the target pressure was 300 N, the RMSE of the pressure using electro — hydraulic control was 30. 1% lower on average and the variation coefficient of soil compaction was 24. 46 percentage points lower than that by using traditional mechanical control. When the maximum surface displacement in the vertical direction of sine curve was 0 mm, 20 mm and 40 mm, respectively, the variation of RMSE was not significant with the increase of the target force, and the maximum difference was 39. 2 N. The automatic soil compaction control system of maize planter based on electro — hydraulic control can guarantee the compaction operation quality under different work conditions. It provided technical and equipment support for the construction of seed bed and maize sowing under the condition of high speed and no tillage in arid region. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 33

Main heading: Compaction

Controlled terms: Agricultural robots? - ?Control system analysis? - ?Control system stability? - ?Grain (agricultural product)? - ?Hydraulic control equipment? - ?Mechanical variables control? - ?Seed? - ?Soil testing? - ?Step response? - ?Three term control systems

Uncontrolled terms: Compaction control? - ?Compaction pressure? - ?Condition? - ?Electro-hydraulic control systems? - ?Electrohydraulic controls? - ?High Speed? - ?Maize planter? - ?Mechanical control? - ?No tillage? - ?Soil compaction

Classification code: 1106.3 ? - ?1401.2 ? - ?1502.1.1.4.3 ? - ?483.1 Soils and Soil Mechanics? - ?731.1 Control Systems? - ?731.3 Specific Variables Control? - ?731.4 Control System Stability? - ?731.6 Robot Applications? - ?732.1 Control Equipment? - ?821.2 Agricultural Chemicals? - ?821.5 Agricultural Wastes? - ?913.4 Manufacturing

Numerical data indexing: Force 2.00E+00N, Force 3.00E+02N, Force 9.00E+00N, Percentage 0.00E00%, Percentage 1.00E00%, Size 0.00E00m, Size 2.00E-02m, Size 4.00E-02m, Time 1.90E+00s

DOI: 10.6041/j.issn.1000-1298.2024.11.028

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

13. Humanoid Robot Gait Planning Method Based on Foot Placement Optimization

Accession number: 20244817425833

Title of translation: 基于落脚点优化的仿人机器人步态规划方法

Authors: Gan, Chunbiao (1); Li, Zijing (1); Neng, Yiming (1)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Vniversity, Hangzhou; 310058, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 486-491

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Humanoid robots, with their human-like form, can more easily integrate into human daily life and adapt to existing infrastructure environments. The study of their kinematics and dynamics theories, along with methods for disturbance rejection control, has been a focal point of research among numerous scientists and engineers around the world for nearly half a Century. Due to disturbances from external uncertainties, the motion State of humanoid robots may undergo significant changes in a short period, often leading to difficulties in maintaining continuous Walking and resulting in falls. Firstly, optimization adjustments were made to the relationship equation between the Walking parameters and the target foot placement in classieal gait planning methods based on the linear inverted pendulum, aiming to achieve a more coordinated Walking gait. Secondly, a gait planning method based on optimizing the deviation of foot placement within one and two steps was proposed by generating Walking patterns in two-step cycles and anticipating the subsequent two target foot placements. Substantial acceleration/deceleration Walking simulations and experiments were conducted on a small humanoid robot. The experimental results showed that the improved gait planning method can significantly reduce the maximum deviation of the landing points, reducing the deviation of two consecutive steps during motion State transitions from 1. 1 cm and 0.8 cm to 0.6 cm and 0.7 cm, respectively, compared with the classieal method. Moreover, the improved gait planning method also mitigated the impact of inertial forces on trunk stability, decreasing the maximum change in trunk pitch angle caused by the classieal method from 7. 8° to 6. 0°. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Anthropomorphic robots

Controlled terms: Disturbance rejection? - ?Gait analysis? - ?Intelligent robots? - ?Inverted pendulum? - ?Kinematics? - ?Motion planning? - ?Robot programming

Uncontrolled terms: Daily lives? - ?Foot placement optimization? - ?Foot placements? - ?Gait planning? - ?Human like? - ?Humanoid robot? - ?Motion state? - ?Placement optimization? - ?Planning method? - ?Robot gaits

Classification code: 101.4 ? - ?101.6.1 ? - ?1101 ? - ?1106.1 ? - ?1301.1.1 ? - ?731 Automatic Control Principles and Applications? - ?731.1 Control Systems? - ?731.5 Robotics? - ?731.6 Robot Applications

Numerical data indexing: Size 1.00E-02m, Size 7.00E-03m, Size 8.00E-03m to 6.00E-03m

DOI: 10.6041/j.issn.1000-1298.2024.11.046

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

14. Mechanism Modeling and Vibration Characteristics Analysis of 3 -(PRRPR)RC Orientation Adjustment and Vibration Isolation Platform

Accession number: 20244817420489

Title of translation: 3-(PRRPR)RC调姿隔振平台机构学建模与振动特性研究

Authors: Geng, Mingchao (1); Cui, Tiezheng (1); Zhou, Jingjun (1); Li, Erwei (2); Li, Runtao (3); Zhao, Tieshi (2)

Author affiliation: (1) School of Mechanical Engineering, Hebei University of Architecture, Zhangjiakou; 075000, China; (2) Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao; 066004, China; (3) China North Industries Croup Corporation Inner Mongolia First Machinery Croup Co., Ltd., Baotou; 014000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 492-503

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: A configuration of 3-(PRRPR) RC parallel platform was proposed to meet the dual requirements of orientation adjustment and vibration isolation. The mechanism consisted of three limbs, in which the large-stroke actuator and the passive vibration isolation unit existed in the form of closed-loop sub-chain. In the case of passive vibration isolation, it was assumed that the actuator was instantaneously locked, and the equivalent motion screw was used to describe the closed-loop sub-chain and the orientation adjustment and vibration isolation platform was instantaneously equivalent to a 3-RRC parallel mechanism. Based on the screw algebra and QR decomposition, the first and second order influence coefficients of the mobile platform and the limb links in the passive vibration isolation mode of the orientation adjustment and vibration isolation platform were derived. Based on the dynamic model, the vibration differential equation of the platform was derived when the foundation was excited by simple harmonic motion. The vibration response was solved by the superposition method of vibration mode, and the corresponding numerical examples were given. The prototype of the orientation adjustment and vibration isolation platform was designed, the experimental system was built, and the passive vibration isolation experiments in x, y and z directions were carried out. Numerical examples and experimental results showed that the vibration transmissibility of the prototype in three directions was less than 55%, that was, more than 45% of the vibration was isolated, which verified the effectiveness of the passive vibration isolation of the designed parallel platform. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Differential equations

Controlled terms: Machine vibrations? - ?Vibration analysis

Uncontrolled terms: Closed-loop? - ?Mechanism modeling? - ?Orientation adjustment and vibration isolation platform? - ?Parallel mechanisms? - ?Parallel platforms? - ?Passive vibration isolations? - ?Subchains? - ?Vibration characteristics? - ?Vibration characteristics analysis? - ?Vibration isolation platforms

Classification code: 1201.2 ? - ?601.3 Mechanisms? - ?941.5

Numerical data indexing: Percentage 4.50E+01%, Percentage 5.50E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.047

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

15. Design and Experiment of Variable Rate Fertilization Combined Soil Preparation Machine

Accession number: 20244817420382

Title of translation: 棉田变量施肥整地联合作业机设计与试验

Authors: Han, Changjie (1, 2); Liu, Zhao (1); Mao, Hanping (1); Ma, Xu (1); Wang, Su (3)

Author affiliation: (1) Mechanical and Electronic Engineering Institute, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Xinjiang Intelligent Agricultural Machinery Equipment Engineering Technology Research Center, Urumqi; 830052, China; (3) Cuangda Agricultural Machinery Co., Ltd., Shihezi; 832000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 250-261 and 284

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In view of the lack of cotton field fertilization combined soil preparation machinery and the low control precision of fertilizer application in Xinjiang, a variable fertilization combined soil preparation machine was designed, which could complete the operations of harrowing, variable fertilization, soil leveling, soil crushing and suppression at one time. The key components such as fertilizer discharge device, double disc trenching mechanism, notch rake group, soil crushing and pressing components were designed. The key factors affecting its working performance were obtained through static analysis, and the structural parameters of key components were determined. Based on the Beidou automatic navigation driving system, the driving speed was obtained, and the variable fertilization control was realized with STM32F405 as the core processor. The field experiment was carried out with the consistency of fertilizer amount in each row, the control accuracy of fertilizer amount at different driving speeds and the qualified rate of fertilization depth as the evaluation indexes of fertilization performance, and the stability of rake depth, standard deviation of surface flatness and rate of broken soil as the evaluation indexes of soil preparation performance. The test results showed that when the rotation speed of the fertilizer shaft was 10~60r/min, the maximum coefficient of variation of the consistency of each row of fertilizer was 4. 27% . When the driving speed was 4 km/h, 7 km/h and 10 km/h, the minimum control precision of fertilizer discharge was 96. 70%, 95. 35% and 94. 14%, respectively. The qualified rate of fertilization depth was 87. 04% . The maximum coefficient of variation of rake depth stability was 5. 34% . The maximum standard deviation of surface roughness was 4. 69 mm. The broken soil rate was 96. 16% . All indexes met the requirements of fertilization machinery and soil preparation machinery standards. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Shafts (machine components)

Uncontrolled terms: Combined machine? - ?Control precision? - ?Cotton fields? - ?Driving speed? - ?Evaluation index? - ?Fertilisation? - ?Land preparation? - ?Soil crushing? - ?Soil preparation? - ?Variable fertilizations

Classification code: 601.2 Machine Components

Numerical data indexing: Angular velocity 1.67E-01rad/s to 1.002E+00rad/s, Percentage 1.40E+01%, Percentage 1.60E+01%, Percentage 2.70E+01%, Percentage 3.40E+01%, Percentage 3.50E+01%, Percentage 4.00E+00%, Percentage 7.00E+01%, Size 1.00E+04m, Size 4.00E+03m, Size 6.90E-02m, Size 7.00E+03m

DOI: 10.6041/j.issn.1000-1298.2024.11.026

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

16. Mechanical Modeling of Foot-terrain Interactions in Agricultural Walking Wheels on Wet and Soft Terrain

Accession number: 20244817425836

Title of translation: 湿软地面农用步行轮足壤互作力学模型研究

Authors: Han, Dianlei (1); Liu, Hairui (1); Ren, Lizhi (1); Hu, Jinrui (1); Li, Bo (2); Chen, Xuegeng (1, 3)

Author affiliation: (1) School of Agriculture Engineering, Jiangsu University, Zhenjiang; 212013, China; (2) Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun; 130022, China; (3) College of Mechanical and Electrical Engineering, Shihezi University, Shihezi; 832003, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 461-474

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the challenges posed by the sinking of agricultural Walking wheels on wet and soft terrain, as well as the absence of a eomprehensive interaction meehanics theory, the typical foot-terrain interaction models for pressure and shear meehanics were modified. Numerous foot-terrain interaction tests were conducted by using a universal testing machine to study the pressure and shear resistance — displacement of various foot designs on different types of wet and soft ground, including sand and soil with varying humidity levels. At the same time, the particle velocity field and motion trend of different types of foots on different wet and soft ground were investigated by means of EDEM discrete dement Simulation, which was used to observe the fine-scale behavior of wet and soft terrain. In the pressure test, the cylindrical foot was easier to sink compared with the rectangular foot. Combined with the Simulation, the cylindrical foot was more likely to damage the soil structure under the foot, and the anti-subsidence Performance of the rectangular foot was better than that of the cylindrical foot. The difference in intrusion resistance between rigid and rigid-flexible foots was not significant. The bearing capacity of sand was gradually increased with the increase of humidity, while the bearing capacity of soil was gradually decreased. In the shear test, the foot shear resistance of rigid cylindrical and rectangular foots under sand and soil with different humidity was related to the normal load, and both of them were increased with the increase of normal load. The foot shear resistance had little relationship with the medium humidity. Combined with the Simulation, there was more soil accumulation in front of the foot in the process of foot shear, and the foot continuously pushed the soil above the slant, which needed the influence brought by the pushing effect to be further eonsidered. Based on the pressure test data, the typieal pressure-bearing model was modified, the subsidence — depth relationship of sand and soil with different humidity was supplemented. Based on the shear test data, the typieal shear model was modified, and the shear resistance — displacement relationship was obtained by eonsidering the influence of pushing soil. It can provide a design reference and theoretical basis for the development of a Walking wheel foot on wet and soft terrain. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 23

Main heading: Soil testing

Controlled terms: Agricultural robots? - ?Bearings (machine parts)? - ?Materials testing apparatus? - ?Shear flow? - ?Shear stress? - ?Wheels

Uncontrolled terms: Discrete elements method? - ?Foot-terrain interaction? - ?Pressure tests? - ?Sand and soil? - ?Shear resistances? - ?Shear tests? - ?Soft ground? - ?Terrain mechanic? - ?Walking wheel foot? - ?Wet and soft terrain

Classification code: 1502.1.1.4.3 ? - ?214.1.1 ? - ?215.1.1 ? - ?301.1.5 ? - ?483.1 Soils and Soil Mechanics? - ?601.2 Machine Components? - ?731.6 Robot Applications? - ?821.2 Agricultural Chemicals

DOI: 10.6041/j.issn.1000-1298.2024.11.044

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

17. Design and Experiment of Cutting Device of Multi-degree-of-freedom Sandy Willow Harvester

Accession number: 20244817425840

Title of translation: 多自由度沙柳平茬收割机切割装置设计与试验

Authors: He, Changbin (1, 2); Jing, Hongwei (1); Zhao, Chencheng (1); Te, Binguribu (3); Shi, Lei (3); Tu, Nala (3)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Inner Mongolin Agricultural University, Hohhot; 010018, China; (2) Inner Mongolia Engineering Research Center of Intelligent Equipment for the Entire Process of Forage and Feed Production, Hohhot; 010018, China; (3) Hangjinqi Agricultural and Animal Husbandry Technology Extension Center, Ordos; 017400, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 320-328

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, low efficiency, and lack of mechanical equipment in the harvesting of sandy willow growing in complex sandy terrains and dispersed distributions, the theoretical analysis, orthogonal experiments, response surface analysis, and field test methods were used, a sandy willow cutting harvester with seven degrees of freedom and a counter-rotating dual saw blade cutting device were designed. Subsquently, the prototype was fabricated and subjected to field Performance tests. The harvester was driven by a hydraulic System, and it mainly comprised a frame, a Walking meohanism, a cutting device, a telescopic device, and a rotating device, etc. The orthogonal experiments results and response surface analysis indicated that the saw blade rotate speed, feed rate, and number of saw blade teeth were key factors affecting the cutting force and power. The number of saw blade teeth and saw blade rotate speed significantly influenced the cutting force and power, as well as the notable interactions between the saw blade teeth and rotate speed, saw blade teeth and feed rate. The field test results showed that, when the cutting device operating parameters were saw blade tooth number of 120, feeding speed of 10 mm/s, and sawing speed of 1 400 r/min the average stubble breakage rate, missed cut rate, re-cut rate, and stubble height qualification rate of the sandy willow harvester were 4.02%, 4. 19%, 0, and 94.33%, respectively, meeting the technical requirements for mechanized sandy willow cutting Operations. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Sawing

Controlled terms: Hydraulic motors? - ?Metal working saws

Uncontrolled terms: Cutting device? - ?Cutting forces? - ?Cutting power? - ?Feedrate? - ?Multi degree-of-freedom? - ?Orthogonal experiment? - ?Response surface analysis? - ?Rotate speed? - ?Sandy willow? - ?Sawblade

Classification code: 1401.2 ? - ?216 ? - ?604.1 Metal Cutting

Numerical data indexing: Angular velocity 6.68E+00rad/s, Percentage 1.90E+01%, Percentage 4.02E+00%, Percentage 9.433E+01%, Velocity 1.00E-02m/s

DOI: 10.6041/j.issn.1000-1298.2024.11.032

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

18. Cow Face Keypoint Detection and Pose Recognition Based on Improved YOLO v7 - Pose

Accession number: 20244817420395

Title of translation: 基于改进YOLO v7-Pose的牛脸关键点检测与姿态识别方法

Authors: Huang, Xiaoping (1, 2); Hou, Xiankun (1); Guo, Yangyang (1, 2); Zheng, Huanyu (1); Dou, Zihao (1); Liu, Mengyi (1); Zhao, Jinling (1, 2)

Author affiliation: (1) School of Internet, Anhui University, Hefei; 230039, China; (2) National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Hefei; 230039, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 84-92 and 102

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Facial keypoint detection in dairy cows plays a crucial role in the automation of cow farms. It aids in cow face recognition, face alignment, head movement detection, and behavior recognition. In view of the problems of cow face occlusion and weak light in the current dairy farming environment, an improved algorithm of YOLO v7 — Pose network model was proposed, which can be used for keypoint detection and head pose recognition of cow face. Firstly, dairy cow facial images were collected from cow farms by using network cameras and a dataset was constructed. Secondly, the SPPFCSPCL structure was integrated into the YOLO v7 — Pose network model to enhance its feature extraction capabilities for cow facial keypoints. The WingLoss loss function replaced the OKS loss function for keypoint detection, thereby improving the accuracy of cow facial keypoint detection. Finally, LI regularization was applied to prune the improved model, reducing the number of network parameters. The experimental results showed that the cow face keypoint detection of improved model YOLO v7 — SCLWL — Pose was improved by 5 percentage points and AP0. 5 was improved by 2. 7 percentage points compared with the original model AP, and the memory occupation of the improved model was only 106.7 MB, which was reduced by 33. 6%. The keypoint detection was applied to pose recognition, and the experimental results showed that the recognition accuracy of the motions of looking up and looking down reached 95. 5% and 86. 5%. This research can provide support technology for behavior recognition in dairy cows on farms. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Face recognition

Controlled terms: Fertilizers? - ?Image enhancement

Uncontrolled terms: Behaviour recognition? - ?Cow face detection? - ?Dairy cow? - ?Faces detection? - ?Keypoint detection? - ?Loss functions? - ?Network models? - ?Percentage points? - ?Pose recognition? - ?YOLO v7 — pose

Classification code: 1106.3.1 ? - ?1106.8 ? - ?1502.1.1.3 ? - ?821.3 Agricultural Methods

Numerical data indexing: Percentage 5.00E+00%, Percentage 6.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.009

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

19. Design and Test of Radius Adjustable Fruit Vibration Harvesting Exciter Based on TRIZ Theory

Accession number: 20244817420405

Title of translation: 基于TRIZ理论的半径可调式林果振动采收激振器设计与试验

Authors: Jiao, Haobo (1); Luo, Juming (1); Tang, Aifei (1); Ma, Chen (1); Wang, Lihong (1, 2); Li, Yaping (3); Li, Chengsong (1, 2)

Author affiliation: (1) College of Engineering and Technology, Southwest University, Chongqing; 400715, China; (2) Key Laboratory of Agricultural Equipment in Hilly and Mountainous Areas, Chongqing; 400715, China; (3) College of Mechanical and Electrical Engineering, Shihezi Vniversity, Shihezi; 832003, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 231-239

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 magnitude and frequency of excitation force Output by existing exciter cannot be adjusted independently, the amplitude and frequency of excitation force cannot meet the demand of fruit Vibration harvesting at the same time, TRIZ theory was used to construct the model of exciter and fruit tree matter — field. According to the matter — field model and the physical conflict solving method, the eccentric block layout of the excitation force amplitude and frequency of the eccentric block exciter was obtained, and the schemes of the four eccentric block exciter and the radius adjustable exciter were proposed. By comparing the dynamic Performance of the two designs, it was found that the moment of inertia of the radius adjustable exciter was lower than that of the four eccentric blocks. The smaller the moment of inertia of the shaker was, the smaller the torque and power required during the rotation of the shaker was. When the four eccentric blocks were rotating, the phase angle size of each eccentric block was changed with time, so it was very difficult to adjust the size of the phase angle ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Controlled terms: Electric exciters? - ?Rotating machinery? - ?Safety factor? - ?Signal to noise ratio

Uncontrolled terms: Adjustable radius exciter? - ?Amplitude-frequency? - ?Amplitude-frequency regulation? - ?Detachment rate? - ?Excitation force? - ?Exciting forces? - ?Frequency regulations? - ?Fruit harvesting? - ?Fruit trees? - ?TRIZ theories

Classification code: 1106.3 ? - ?601.1 Mechanical Devices? - ?704.2 Electric Equipment? - ?716.1 Information Theory and Signal Processing? - ?914 Safety Engineering? - ?914.1 Accidents and Accident Prevention

Numerical data indexing: Frequency 1.90E+01Hz, Percentage 3.00E+00%, Size 7.00E-02m

DOI: 10.6041/j.issn.1000-1298.2024.11.024

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

20. Mixing Performance in Continuous Salt and Freshwater Mixing and Stirring Reactor

Accession number: 20244817420412

Title of translation: 连续式咸淡水混合搅拌反应器混合性能研究

Authors: Li, Jie (1); Chen, Dianyu (1); Hu, Xiaotao (1); He, Mingsong (1)

Author affiliation: (1) Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&E 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: 11

Issue date: November 2024

Publication year: 2024

Pages: 417-428

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to rationally develop and utilize brackish water resources, the structure and operating parameters of a continuous first-but-mix stirring reactor at the front end of an agricultural irrigation system were optimized. The effects of mixing speed and paddle width on the mixing performance were investigated by using a double-layer paddle mixer with a diameter of 290 mm. Realizable k — s model and Eulerian multiphase flow model were used for numerical simulations and validated by experimental data. The analysis of turbulent kinetic energy, velocity flow field, brackish water volume fraction distribution, mixing time and power consumption of the agitator showed that the increase in mixing speed and paddle enhanced the turbulence and flow velocity for both the three-bladed open type and the combined anchor type. It was found that the rotational speed had a greater effect on the studied parameters than the paddle width. Overall, the effect of rotational speed on the studied parameter was significantly more than paddle width, in addition to the significant difference in the effect of these two factors on the two types of agitators. Compared with the three-bladed open agitator, the combined anchor agitator reduced the agitation time by 6. 8%, but increased the agitation power consumption by about 10% . Taking into account of crop irrigation requirements, mixing efficiency and equipment energy consumption, it was recommended to use a three-blade open agitator with a lower speed (90 r/min) and a wide paddle (50 mm). This configuration can effectively balance the mixing efficiency and energy consumption of a continuous salt and freshwater mixing and stirring system. The results can provide a reference for the design optimization of continuous brackish freshwater mixing and stirring reactors. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 34

Main heading: Kinetic energy

Controlled terms: Flow fields? - ?Irrigation? - ?Mixers (machinery)? - ?Multiphase flow? - ?Reactor refueling? - ?Rotational flow? - ?Turbulent flow

Uncontrolled terms: Brackish water? - ?Brackish water irrigation? - ?Continuous stirring reactor? - ?Continuous stirrings? - ?Fresh Water? - ?Mixing efficiency? - ?Mixing performance? - ?Mixing speed? - ?Rotational speed? - ?Stirrer

Classification code: 1001.2 ? - ?1301.1.1 ? - ?301.1 ? - ?301.2 ? - ?601.1 Mechanical Devices? - ?802.1 Chemical Plants and Equipment? - ?821.4 Agricultural Products

Numerical data indexing: Angular velocity 1.503E+00rad/s, Percentage 1.00E+01%, Percentage 8.00E+00%, Size 2.90E-01m, Size 5.00E-02m

DOI: 10.6041/j.issn.1000-1298.2024.11.040

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

21. Maize Tassel Detection Algorithm after Artificial Emasculation Based on Lightweight MLCE RTMDet

Accession number: 20244817420394

Title of translation: 基于轻量化MLCE-RTMDet的人工去雄后玉米雄穗检测算法

Authors: Li, Jinrui (1, 2); Du, Jianjun (2, 3); Zhang, Hongming (1); Guo, Xinyu (2, 3); Zhao, Chunjiang (1, 3)

Author affiliation: (1) College of Information Engineering, Northwest A&F University, Shaanxi, Yangling; 712100, China; (2) Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing; 100097, China; (3) National Engineering Research Center for Information Technology in Agriculture, 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: 11

Issue date: November 2024

Publication year: 2024

Pages: 184-192 and 503

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Detecting missed tassels is crucial for assessing the quality of aritificial emasculation in maize seed production fields. Aiming at the problems of large parameter quantity, low detection efficiency and poor accuracy of the existing maize tassel detection models, a lightweight tassel detection model based on RTMDet — tiny, named MLCE — RTMDet, was proposed. The model used the lightweight MobileNetv3 as the feature extraction network to effectively reduce the model parameters. The CBAM attention module in the neck network was integrated to enhance multi-scale feature extraction capability for tassel objects, overcoming potential Performance losses caused by the lightweight networks. Simultaneously, the EIOU L?ss was adopted, replacing the GIOU L?ss, which further improved the accuracy of tassel detection. Experiments on the self-built dataset showed that the improved MLCE — RTMDet model reduced model parameters to 3. 9 X 10, while the number of floating point Operations was lowered to 5. 3 X 10, resulting in a 20. 4% reduction in parameters and a 34. 6% decrease in computational complexity compared with that of the original model. When evaluated on the test set, the model’s mean average precision (mAP) reached 92. 2%, reflecting a 1. 2 percentage points improvement over the original model. The inference speed was increased to 41. 9 frames per second (FPS), representing a 12. 6% enhancement. Compared with current mainstream detection models such as YOLO v6, YOLO v8, and YOLO X, MLCE — RTMDet demonstrated superior Overall detection Performance. The improved high-accuracy lightweight model offered technical support for tassel re-inspection and emasculation quality assessment in maize seed production fields following artificial emasculation. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Grain (agricultural product)

Controlled terms: Oilseeds? - ?Quality control

Uncontrolled terms: Artificial emasculation? - ?Detection models? - ?Features extraction? - ?Lightweight network? - ?Maize seeds? - ?Maize tassel? - ?Objects detection? - ?Production fields? - ?RTMDet? - ?Seed production

Classification code: 821.5 Agricultural Wastes? - ?913.3 Quality Assurance and Control

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

DOI: 10.6041/j.issn.1000-1298.2024.11.020

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

22. Dynamic Path Planning for Picking Robot Arm Based on Improved Algorithm Fusion and Switching

Accession number: 20244817420380

Title of translation: 基于改进算法融合与切换的采摘机械臂路径动态规划

Authors: Li, Na (1, 2); Gao, Xiao (1); Yang, Lei (1, 2); Jiang, Haiyong (1, 2); Zhang, Lijie (1, 2); Chen, Guangyi (1)

Author affiliation: (1) School of Mechanical and Electrical Engineering, Hebel Agricultural Unlverslty, Baoding; 071001, China; (2) Hebei Province Smart Agrieulture Equipment Technology Innovation Center, Baoding; 071001, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 221-230 and 270

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Ainring at the issues such as prolonged path planning time, low efficiency and poor success rate of the picking manipulator in the apple picking task as a consequence of the complex natural picking environment, an improved fusion and switching path dynamic planning algorithm was proposed. The algorithm introduced a dynamic threshold goal bias sampling strategy and artificial potential field to alter the generation position of new nodes, increasing the purposiveness of sampling and improving convergence speed. A relative distance was incorporated into the repulsive potential field coefficient to overcome the problem of unreachable targets by considering the distance to the goal. To enhance the algorithm’s robustness, a threshold was set to partition the spatial region, dynamically switching to the failure-guided adaptive sampling region RRT algorithm (FGA — RRT) based on the current node expansion State to address narrow passage issues and increase planning success rates. The greedy algorithm was utilized to optimize the resulting path tree, removing redundant nodes, further shortening the path length, and optimizing path smoothness to ensure the stable movement of the picking robot arm. Simulation experiments were conducted for the RRT algorithm, RRT * algorithm, GB — RRT algorithm, common fusion algorithm and the improved fusion and switching algorithm respectively in simple obstacles, narrow Channels, complex obstacles and simple three-dimensional Spaces. The results showed that the improved fusion and switching algorithm had good adaptability in different environments, with high planning efficiency, few iterations and high path quality. Based on the established 6 — DOF robot arm motion planning Simulation environment and laboratory environment, obstacle avoidance pieking tests were conducted. The improved hybrid switching algorithm’s pieking efficiency was increased by 74. 74%, path length was decreased by 32. 03%, and pieking success rate was improved by 8 percentage points compared with that of the RRT algorithm. The experimental results demonstrated that the proposed algorithm had stronger search capabilities in apple-picking scenarios, providing a reference for improving the operational efficiency of pieking robot arms. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 26

Main heading: Robotic arms

Controlled terms: Dynamic programming? - ?Industrial robots? - ?Intelligent robots? - ?Motion planning? - ?Redundant manipulators? - ?Robot programming

Uncontrolled terms: Algorithm fusion? - ?Fusion algorithms? - ?Improved artifieial potential field method? - ?Improved RRT? - ?Improved RRT algorithm? - ?Picking robot? - ?Pieking robot arm? - ?Potential field methods? - ?Robot arms? - ?Switching algorithms

Classification code: 101.6.1 ? - ?1101 ? - ?1106.1 ? - ?1201.7 ? - ?691.1 Materials Handling Equipment? - ?731.5 Robotics? - ?731.6 Robot Applications

Numerical data indexing: Percentage 3.00E+00%, Percentage 7.40E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.023

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

23. Denoising Method for Seed Feeder Field Vibration Signal Based on Combination of DA - VMD and Wavelet Thresholding

Accession number: 20244817420387

Title of translation: 基于 DA-VMD 联合小波阈值的排种器田间振动信号去噪方法

Authors: Liu, Zhengdao (1); Ma, Zhuanghong (1); Zhang, Junchang (1); Yan, Xiaoli (1); Huang, Yuxiang (1); Zhang, Zhiqiang (1)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 262-272

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: During the operation of the seeder, the discharge device will experience non-stationary random vibration, which significantly affects seed discharge performance and holds great importance for acquiring and analyzing vibration signals. A denoising method was proposed that combined dragonfly algorithm (DA), variational mode decomposition (VMD), and wavelet threshold to continuously update the location and speed of dragonfly individuals through iterative processes. The optimal parameter combination for VMD decomposition effect was determined. A simulated random road signal in the time domain served as the initial signal and underwent denoising by using DA-VMD combined wavelet threshold, wavelet threshold denoising, empirical mode decomposition (EMD), VMD, and wavelet combined EMD methods respectively. The results demonstrated that the proposed method achieved superior denoising effects on non-stationary random vibration signals with post-denoising signal-to-noise ratio, root-mean-square value, and correlation number measuring 21.570, 0.094, and 0.833, respectively. Furthermore, vibration signals from seeders under different surface conditions and operating speeds during field seeding were collected and subjected to denoising by using the DA-VMD combined wavelet threshold denoising method. The effectiveness of denoising was evaluated based on smoothness index, signal energy ratio, and noise mode indices. The results indicated smoother signals with higher signal energy ratios after denoising across various working conditions. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Wavelet decomposition

Controlled terms: Empirical mode decomposition? - ?Image coding? - ?Image segmentation? - ?Iterative methods? - ?Signal denoising? - ?Signal to noise ratio? - ?Time domain analysis? - ?Variational mode decomposition? - ?Variational techniques? - ?Wavelet analysis

Uncontrolled terms: De-noising? - ?Denoising methods? - ?Dragonfly algorithm-variational mode decomposition? - ?Mode decomposition? - ?Non-stationary random vibration? - ?Seeding device? - ?Vibration? - ?Vibration signal? - ?Wavelet threshold? - ?Wavelet threshold de-noising

Classification code: 1106.3 ? - ?1106.3.1 ? - ?1201 ? - ?1201.2 ? - ?1201.3 ? - ?1201.9 ? - ?716.1 Information Theory and Signal Processing

DOI: 10.6041/j.issn.1000-1298.2024.11.027

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

24. Lightweight Rice Blast Spores Detection Method Based on Improved YOLO v8

Accession number: 20244817420404

Title of translation: 基于改进YOLO v8的轻量化稻瘟病孢子检测方法

Authors: Luo, Bin (1, 2); Li, Jiachao (1, 2); Zhou, Ya’nan (2); Pan, Dayu (2); Huang, Shuo (2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, 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: 11

Issue date: November 2024

Publication year: 2024

Pages: 32-38

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Rice blast is one of the most serious diseases of riee. It is caused by blast fungus and occurs in different growth stages of riee. The spores of blast ean be transmitted through air, whieh seriously affects food production security. Therefore, the identification of blast spores plays an important role in the early diagnosis and control of riee blast. Based on the YOLO v8 model, an RBS — YOLO method for the detection of riee blast spores was proposed. Firstly, the algorithm introduced the PP — LCNet lightweight network in the backbone network, which used DepthSepConv as the basic block and reduced the computational effort of the model and the size of the model weight file, but hardly increased the inference time. Secondly, the efficient multi-scale attention module was introduced into the neck network, which reshaped some Channels into batch dimensions and grouped the Channel dimensions into multiple sub-features, so that the spatial semantic features were evenly distributed in each feature group. The Information of each Channel can be effectively preserved and the computational overhead ean be reduced. Finally, the loss funetion of YOLO v8n was changed to WIOU loss funetion, which can reduce the impact of low-quality samples on the model during training. WIOU used dynamic non-monootone focusing mechanism to evaluate the quality of the anchor frame, and used gradient gain, which ensured the high-quality effect of the anchor frame and reduced the influence of harmful gradients. The aecuraey and mean aecuraey of model identification of riee blast spores were improved. The aecuraey and average aecuraey of the improved RBS — YOLO model were 97. 3% and 98. 7%, respectively, meeting the demand for the detection of riee blast spores. The weight file size and computation amount were 3. 46 MB and 5. 2 X 10, respectively, which were 41.8% and 35.8% lower than that of YOLO v8n. In order to verify the detection Performance of RBS — YOLO, under the same training environment and parameter configuration, the improved model was oompared with the YOLO v5s, YOLO v7 and the original YOLO v8n model, and the computational load was reduced by 67. 3%, 95. 1% and 35. 8%, respectively. Model weight file sizes were reduced by 10.14 MB, 67.84 MB, and 2.49 MB, respectively. The results showed that RBS — YOLO can meet the demand of real-time detection of rice blast spores,which was conducive to deployment to mobile terminals. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Risk management

Controlled terms: Agricultural robots? - ?Distribution functions? - ?Health risks? - ?Precision balances? - ?Risk analysis? - ?Risk assessment? - ?Risk perception? - ?Thermal spraying

Uncontrolled terms: Attention mechanisms? - ?Detection methods? - ?File sizes? - ?Lightweight? - ?Model weights? - ?Rice blast spore? - ?Rice blasts? - ?Spore detection? - ?Targets detection? - ?YOLO v8

Classification code: 102.1.2.1 ? - ?1108 ? - ?1202 ? - ?1202.1 ? - ?208.1 ? - ?731.6 Robot Applications? - ?821.2 Agricultural Chemicals? - ?914.1 Accidents and Accident Prevention? - ?942.1.7

Numerical data indexing: Percentage 1.00E00%, Percentage 3.00E+00%, Percentage 3.58E+01%, Percentage 4.18E+01%, Percentage 7.00E+00%, Percentage 8.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.003

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

25. Maize Disease Classification and Recognition Method Based on Super-resolution Generative Adversarial Networks

Accession number: 20244817420381

Title of translation: 基于超分辨率生成对抗网络的玉米病害分类识别方法

Authors: Ma, Tiemin (1); Qu, Hao (1); Gao, Ya (1); Wang, Xue (1)

Author affiliation: (1) College of Information Technology, Heilongjiang Baji Agricultural University, Daqing; 163319, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 49-56 and 67

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Maize is one of the most important food crops in China. Leaf diseases of maize can seriously damage its yield, so the correct identification of disease is of great significance. However, the efficiency of traditional manual identification of leaf diseases is low. The resolution of disease images collected from agricultural fixed points or drone monitoring is low, and the key features are not significant, which cannot meet the image resolution requirements of Classification and recognition models. The training effect is poor, making it difficult to accurately identify leaf diseases. To this end, a maize disease Classification and recognition model based on an improved super-resolution generative adversarial network (SRGR) was designed. The images of maize leaf disease were divided into four types; large spot, rust, gray spot, and healthy leaves. The data set was divided into low resolution (LR) and high resolution (HR) images that corresponded one-to-one. In order to realize the restoration of low-resolution maize spot images to high-resolution images, this model proposed an improved strategy for the enhanced super-resolution generative adversarial networks (ESRGAN) model based on dual attention meohanism. LR images were input into the high-frequency feature reconstruction network, and Channel attention (CA) mechanism after each residual dense block (RRDB) was added to extract deep detailed features of the image, making the model highly targeted in reconstructing high-frequency details and reducing the possibility of pseudo texture phenomenon. The generation network was divided into encoding and decoding parts, and the spatial attention mechanism was introduced into U-shaped dense block with skip layers to maximize the retention of maize disease effective features in the middle and low levels of the LR image of maize lesions. The probability value of high-frequency features in the input feature map was calculated to determine the position of reconstructed lesion features in the image. The WGAN — GP loss function was used to train the network to solve the problem of vanishing generator gradients, enhancing the stability of the network. The regenerated lesion images were input into the discriminant network, and images that met HR image Standards were input into the ResNet34 Classification model to achieve accurate Classification and identification of maize leaf lesions, and images that did not meet the Standards were returned to the generation network for retraining. The experimental results showed that the addition of the dual attention mechanism and the change of the loss function increased the model’s ability to recover high-frequency features and robustness. Compared with other super-resolution image reconstruction algorithms, the high-resolution reconstructed images generated based on the SRGR model improved peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values, with an average increase of 2. 1 dB and 0. 049, which was a significant improvement. Four different Classification networks were selected for image Classification and recognition, and the recognition accuracy of reconstructed images was improved by an average of 28. 1 percentage points compared with that of LR images. Among them, the ResNet34 Classification model had the highest accuracy compared with AlexNet, VggNet, and GoogleNet models. In the attention module ablation experiment, compared with the other three models, SRGR accuracy in identifying maize lesions exceeded other models by an average of 1. 3 percentage points, with an accuracy rate of 97. 8%. In the visualization of the recognition results, the heat map of the lesions identified by the SRGR model had the darkest color and the highest recognition degree. In summary, the research result can serve as a reference for accurate identification of low-resolution leaf disease images in crop leaf spot monitoring or drone field monitoring. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 32

Main heading: Image reconstruction

Controlled terms: Conformal mapping? - ?Grain (agricultural product)? - ?Image enhancement? - ?Image texture? - ?Photointerpretation? - ?Photomapping

Uncontrolled terms: Adversarial networks? - ?Classification and recognition? - ?Classification models? - ?Disease identification? - ?High frequency HF? - ?Leaf disease? - ?Maize disease? - ?Maize leaf? - ?Super-resolution image reconstruction? - ?Superresolution

Classification code: 1106.3.1 ? - ?1201.14 ? - ?1201.2 ? - ?405.3 Surveying? - ?742.1 Photography? - ?821.5 Agricultural Wastes

Numerical data indexing: Decibel 1.00E00dB, Percentage 8.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.005

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

26. Feature Mask-based Local Occlusion Cattle Face Recognition Method

Accession number: 20244817420487

Title of translation: 基于特征掩膜的局部遮挡牛脸识别方法

Authors: Qi, Yongsheng (1); Zhang, Xinze (1); Zhang, Jiaying (1, 2); Liu, Liqiang (1, 2); Li, Yongting (1, 2)

Author affiliation: (1) College of Electric Power, Inner Mongolia University of Technology, Hohhot; 010080, China; (2) Intelligent Ener. Technol. and Equip. Eng. Res. Ctr. of Colleges and Universities in the Inner Mongolia Autonomous Reg., Hohhot; 010080, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 93-102

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: With the rapid development of intelligent animal husbandry, bovine face recognition has become the key to intelligent cattle breeding, but the problem of bovine face occlusion in practical application scenarios is more serious, which brings challenges to the performance of the recognition system. To solve this problem, a two-branch network structure based on occluder-assisted bovine face recognition was proposed. Firstly, an improved lightweight U - Net occlusion segmentation model was designed. By adding deep separable convolution and multi-scale mixing pool module, the occlusion segmentation performance of the segmentation network was effectively improved. Secondly, in order to better attenuate the influence of occlusions on bovine face recognition performance, a multilevel mask generation unit was introduced, and masks corresponding to different stages of the recognition network were constructed with different levels of occlusions as input. The damaged feature information caused by occlusions was effectively eliminated in each stage of feature extraction through mask operation. Finally, for the validity and real-time performance of the detection algorithm, the algorithm was verified on the self-made data set, and compared with a variety of recent typical recognition algorithms. The experimental results showed that the proposed algorithm had an average accuracy of 86. 34% on the blocked cow face data set, and the recognition speed was 54 f/s. Compared with the single-scale mask, the average accuracy of multistage mask was improved by 2.02 percentage points, and the recognition effect was better than that of the comparison network under different degrees of occlusion. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Mammals

Controlled terms: Face recognition? - ?Image segmentation? - ?Livestock

Uncontrolled terms: Branch structure? - ?Cattles? - ?Data set? - ?Dual- branch structure? - ?Face recognition methods? - ?Images segmentations? - ?Multi-level mask learning? - ?Multilevels? - ?Occluded cattle face recognition? - ?Occlusion segmentation

Classification code: 103 ? - ?1106.3.1 ? - ?1106.8 ? - ?821 Agricultural Equipment and Methods; Vegetation and Pest Control? - ?821.5 Agricultural Wastes

Numerical data indexing: Percentage 3.40E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.010

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

27. Soil Drought Monitoring with TVDI and ARIMA in Henan Province

Accession number: 20244817420390

Title of translation: 基于 TVDI 结合 ARIMA 的河南省土壤旱情监测方法

Authors: Su, Yingying (1); Lu, Xiaoping (1); Xiao, Feng (2); Zhang, Xiangjun (3); Li, Guoqing (3); Yu, Haikun (3); Wang, Xiaoxuan (1)

Author affiliation: (1) Key Laboratory of Spatiotemporal Information and Ecological Restoration of Mines, MNR, Henan Polytechnic University, Jiaozuo; 454003, China; (2) Henan Serveying and Mapping Geographic Information Technology Center, Zhengzhou; 450003, China; (3) Henan Institute of Remote Sensing, Zhengzhou; 450003, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 391-401 and 522

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aim at the frequent soil drought disasters and the limited monitoring area of ground soil moisture monitoring stations in Henan Province, the meteorological drought index and remote sensing monitoring model were combined to predict soil drought. It was based on the standardized precipitation evapotranspiration index calculated by meteorological data from 2012 to 2021, and the drought monitoring effects of four indices of commonly used remote sensing models, namely crop water scarcity index, vegetation supply water index, temperature vegetation drought index and vegetation temperature condition index were evaluated. Taking 2019 as a typical drought year, the differences among the four indices were compared, and the spatial distribution and change trend of TVDI in Henan Province from 2012 to 2021 were analyzed. Finally, ARIMA model was used to predict soil drought in 2022. The results showed that the research results of CWSI, VSWI and VTCI were different from the actual results. Only the TVDI value was consistent with the change trend of soil moisture recorded in the field, and showed an increasing trend with time in the northwest, central and northern parts of Henan Province. The spatial evolution results showed that the coverage pixels of arid areas in 2019 accounted for 76%, which accounted for the largest proportion in this decade, and the soil moisture predicted by the ARIMA model in 2022 was consistent with the reality. On the basis of soil drought prediction, it can provide reference for the precise management of agricultural production in Henan Province. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Soil moisture

Uncontrolled terms: %moisture? - ?Autoregressive moving average model? - ?Autoregressive Moving Average modeling? - ?Change trends? - ?Drought monitoring? - ?Henan Province? - ?Soil drought? - ?Standardized precipitation evapotranspiration index? - ?Temperature vegetation drought index? - ?Vegetation drought indices

Classification code: 483.1 Soils and Soil Mechanics

Numerical data indexing: Percentage 7.60E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.038

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

28. Research Status and Prospect of Key Technologies of Agricultural Track Chassis

Accession number: 20244817420375

Title of translation: 农业履带底盘关键技术研究现状与展望

Authors: Sun, Jingbin (1); Zeng, Lingkun (1); Ying, Jing (2, 3); Zheng, Hang (4, 5); Sun, Qun (1); Meng, Xianzhe (1)

Author affiliation: (1) College of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng; 252000, China; (2) Key Laboratory of Agricultural Equipment Technology for Hilly and Mountainious Areas, Ministry of Agriculture and Rural Affairs, Chengdu; 610066, China; (3) Sichuan Academy of Agricultural Machinery Sciences, Chengdu; 610066, China; (4) 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; 310021, China; (5) Institute of Agricultural Equipment, Zhejiang Academy of Agricultural Sciences, Hangzhou; 310021, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 202-220

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In view of its advantages such as small ground pressure, good climbing Performance and flexible turning, agricultural track chassis is currently a mobile agricultural power machinery widely recognized by farmers, which has been widely used in various aspects of agricultural production such as farming, planting, field management, harvesting, transportation, and gradually developing in the direction of automation and intelligence. The development Status at home and abroad was mainly expounded from the application of agricultural track chassis, stability theory and control technology, drive System and steering technology, autonomous navigation and intelligent control technology, and agricultural track chassis — soil interaction theory. The application progress of stable leveling, efficient transmission, smooth steering and autonomous driving in agricultural track chassis was summarized. Combined with different agricultural Operations, the application characteristics of agricultural track chassis in related fields were illustrated. At last, according to the current and future needs of agricultural track chassis in China, the future development direction of agricultural track chassis was prospected from the aspects of strengthening the optimization of high-stability Walking System, creating efficient transmission and flexible steering System, overcoming the teehnology of autonomous driving and intelligent control, and researehing the basie theory of track — soil System. The research result can provide a good reference for the future technical research of agricultural track chassis. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 90

Main heading: Steering

Controlled terms: Agricultural robots

Uncontrolled terms: Agricultural track chassi? - ?Autonomous driving? - ?Autonomous navigation? - ?Climbing performance? - ?Control technologies? - ?Drive steering? - ?Ground pressure? - ?Key technologies? - ?Research status? - ?Status and prospect

Classification code: 731.6 Robot Applications? - ?821.2 Agricultural Chemicals

DOI: 10.6041/j.issn.1000-1298.2024.11.022

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

29. Experiment on Anisotropy of Soil-Root Composite Based on Microstructure Quantification

Accession number: 20244817420400

Title of translation: 基于微结构量化的枣园根土复合体各向异性试验

Authors: Wang, Dewei (1, 2); Wang, Xufeng (2); You, Yong (1); Wang, Tianyi (1); Hui, Yunting (1); Wang, Decheng (1)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 402-416

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To determine the operation technology of root cutting and nurturing in jujube orchards in southern Xinjiang, physical parameters such as soil moisture content, solidity, porosity, bulk density, and particle size distribution were measured. The root aggregation depth and soil root content of the jujube orchard’s root cutting area were also calculated. The agricultural technical requirements were determined that the root cutting area should be located 750 mm away from the tree trunk and the depth of the root cutting operation should be adjustable within the range of 0 ~ 200 mm. The research results indicated that the root soil composite had anisotropy. When the sampling angles 9 were 0°, 45° and 90°, the shear strength T relationship of the root soil composite showed trend of T0? ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 36

Main heading: Fractal dimension

Controlled terms: Agricultural robots? - ?Cutting tools? - ?Fertilizers? - ?Orchards? - ?Shear strength? - ?Size distribution

Uncontrolled terms: Cutting area? - ?Jujube garden? - ?Microstructural parameters? - ?Probability entropy? - ?Research results? - ?Ring knife sampling? - ?Root cuttings? - ?Shears strength? - ?Soil-root composite? - ?Structural parameter

Classification code: 1201.13 ? - ?1202.2 ? - ?1502.1.1.3 ? - ?214 ? - ?603.1 Machine Tools, General? - ?731.6 Robot Applications? - ?821.2 Agricultural Chemicals? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products

Numerical data indexing: Size 0.00E00m to 2.00E-01m, Size 7.50E-01m

DOI: 10.6041/j.issn.1000-1298.2024.11.039

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

30. Calibration of Discrete Element Simulation Parameters for Cultivated Soil Layer in Coastal Saline Alkali Soil

Accession number: 20244817420409

Title of translation: 滨海盐碱地耕作层土壤离散元仿真参数标定方法

Authors: Wang, Dongwei (1, 2); Lu, Tong (1); Zhao, Zhuang (3); Shang, Shuqi (1, 2); Zheng, Shuai (1); Liu, Jie (1)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao; 266109, China; (2) Yellow River Delta Intelligent Agricultural Machinery Equipment Industry Acadcmy, Dongying; 257345, China; (3) College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian; 271018, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 240-249

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to obtain the discrete element Simulation parameters of coastal saline soils, the soil discrete element parameters were calibrated by combining the experiment and discrete element Simulation using the soil of the Yellow River Deltd Agricultural Highland Area as an example, and Hertz — Mindlin with JKR in EDEM was selected as the Simulation contact model. The significance analysis was carried out through the Plackett — Burman test to explore the factors that had a significant effect on the soil stacking angle, the steepest climb method was used to further determine the r?nge of factor values, the Box — Behnken test was applied to establish a quadratic polynomial regression model of the three significance factors and the simulated stacking angle of the soil, and the regression model was performed with the measured soil stacking angle of 33. 6° as the target. The optimal combination of soil - soil static friction factor of 0. 546, soil — soil recovery coefficient of 0. 358, and soil surface energy of 3. 207 J/m in the JKR model was obtained. Under the conditions of the optimal parameter combination, the Simulation results of the outer diameter of the top of the hole and the longitudinal depth of the hole had an error of 4.04% and 3.47% from the test, respectively, which verified the accuracy of the soil parameter calibration. The discrete element parameter calibration method and parameter values proposed for saline alkali soil can provide theoretical basis and Support for the discrete element Simulation of the interaction between soil contact components and soil under saline alkali working conditions, as well as the research and design of specialized agricultural machinery for saline alkali soil. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 35

Main heading: Polynomial regression

Controlled terms: Agricultural robots? - ?Polynomial approximation? - ?Soil testing

Uncontrolled terms: Condition? - ?Cultivated soils? - ?Discrete elements? - ?Discrete-element simulations? - ?Parameters calibrations? - ?Saline-alkali soils? - ?Simulation parameters? - ?Soil layer? - ?Soil-soil? - ?Stacking angle

Classification code: 1201.9 ? - ?1202.2 ? - ?1502.1.1.4.3 ? - ?483.1 Soils and Soil Mechanics? - ?731.6 Robot Applications? - ?821.2 Agricultural Chemicals

Numerical data indexing: Energy 2.07E+02J, Percentage 3.47E+00%, Percentage 4.04E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.025

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

31. Optimization Design and Test of Air Delivery System for Tower Sprayer

Accession number: 20244817420408

Title of translation: 塔形喷雾机风送系统优化设计与试验

Authors: Wang, Pengfei (1); Xu, Shuo (1); Yang, Xin (1); Li, Shike (2)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding; 071001, China; (2) Hebei Nongyao Technology Co., Ltd., Shijiazhuang; 050051, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 342-351 and 390

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of unreasonable distribution of wind field and large loss of liquid, an air delivery system of tower sprayer was designed and its structural parameters were optimized. ANSYS software was used to simulate the air delivery system of sprayer, and the optimal parameters of the rectifier plate structure, deflector taper and deflector on both sides were determined by comparing the wind speed difference of the two sides outlet and the wind speed of the upper outlet under different structural parameters. The experimental results showed that the influence of the structure parameters of the rectifier on the symmetry of wind field on both sides of the sprayer from large to small was as follows; guide vane angle, guide vane number and guide vane length. The diversion table greatly improved the symmetry of wind field. The length and angle of the baffle had great influence on the wind speed of the upper outlet. When the number of guide blades of the rectifier plate was 12, the length was 200 mm, the angle was 0°, and the taper of the guide table was 60°, when the contraction angle of air duct 1 was 2°, the symmetry of wind field and vertical distribution uniformity on both sides of the sprayer were optimized. According to the optimal parameters, the sprayer air delivery system was set up and the wind speed test was carried out. The results showed that the relative error between the simulated wind speed and the test value was less than 10%, and the simulation results were reliable. Field experiments showed that the difference of droplet deposition density on both sides of the sprayer was less than 9%, that was, the droplet deposition on both sides was uniform. The average density of droplets deposited in the canopy of fruit trees was 75. 69 particles/cm, which indicated that the optimized tower sprayer had good droplet penetration. The vertical distribution of fog droplets in the lower layer was the largest, followed by the middle layer and the smallest in the upper layer, which was consistent with the distribution of high spindle tree canopy. The symmetry of the wind field and droplet deposition characteristics on both sides of the optimized tower sprayer was high, and the research results can provide reference for the optimization of the air delivery system of tower sprayer. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 28

Main heading: Ducts

Controlled terms: Aerodynamics? - ?Axial flow turbomachinery? - ?Drop formation? - ?Dynamic programming? - ?Electric rectifiers? - ?Electrodeposition? - ?Enameling? - ?Hard facing? - ?Vortex flow? - ?Wind stress

Uncontrolled terms: Air conveyor? - ?Air delivery systems? - ?Axial fans? - ?Diversion table? - ?Droplet deposition? - ?Duct guide vane? - ?Guide-vane? - ?Tower sprayer? - ?Wind field? - ?Wind speed

Classification code: 1007 ? - ?1201.7 ? - ?1301.1.2 ? - ?201.1.1 ? - ?201.9.3.1 ? - ?208.1 ? - ?214.1.1 ? - ?301.1 ? - ?301.1.3 ? - ?304.4 ? - ?443.1 Atmospheric Properties? - ?651 Aerodynamics? - ?704.2 Electric Equipment

Numerical data indexing: Percentage 1.00E+01%, Percentage 9.00E+00%, Size 2.00E-01m

DOI: 10.6041/j.issn.1000-1298.2024.11.034

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

32. Rice Pest Identification Based on Improved YOLO v5s

Accession number: 20244817420386

Title of translation: 基于改进 YOLO v5s 的水稻害虫识别研究

Authors: Wang, Taihua (1, 2); Guo, Yazhou (1); Zhang, Jiale (1); Zhang, Chenyang (1)

Author affiliation: (1) School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo; 454003, China; (2) Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Jiaozuo; 454003, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 39-48

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: When identifying rice pests, issues such as targets being obscured, similarity to the background color, and proximity of multiple targets due to the rice field environment can lead to reduced identification accuracy. To address this, a rice pest identification method was proposed based on an improved YOLO v5s. The method enhanced the model’s ability to capture target location information by replacing ordinary convolution in the backbone network with CoordConv. It introduced the CBAM attention mechanism to increase the model’s focus on the target area. The Slim — neck architecture was adopted to enhance feature processing capabilities and reduce computational load. The introduction of the Soft — NMS algorithm optimized the selection of adjacent target bounding boxes, reducing missed detections. Experimental results showed that the improved YOLO v5s model achieved an mAP of 94. 3% on the rice pest dataset, which was an increase of 3. 8 percentage points over the original model and 1.5, 12. 7, 13. 6 and 1. 9 percentage points higher than that of the other mainstream models such as YOLO v3, YOLO R —CSP, YOLO v7, and YOLO v8s, respectively. Ablation experiments further validated the effectiveness of each component in the improved model. Heat map analysis also demonstrated that the improved model can better learn pest features. In summary, the improved YOLO v5s model proposed achieved significant results in improving the accuracy of rice pest detection, providing a more precise identification method for the prevention and control of rice pests. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 22

Uncontrolled terms: CBAM? - ?Identification method? - ?Multiple targets? - ?Percentage points? - ?Pest identification? - ?Rice? - ?Rice fields? - ?Rice pests? - ?Slim-neck? - ?YOLO v5s

Numerical data indexing: Percentage 3.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.004

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

33. Field Test Analysis of Start-stop Process of Turbine Operating Condition of Pumped Storage Power Unit

Accession number: 20244817420377

Title of translation: 蓄能机组水轮机工况开停机过程现场测试分析

Authors: Wang, Wei (1); Xia, Ming (2); Wang, Zhengwei (2)

Author affiliation: (1) School of Water Resources and Hydropower Engineering, North China Electric Power University, Beijing; 102206, China; (2) Department of Energy and Power Engineering, 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: 11

Issue date: November 2024

Publication year: 2024

Pages: 352-362

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: As an important energy storage technology, pumped storage power plants have both pump and turbine operating modes. In order to meet the requirements of energy collection and grid scheduling, the pump turbine operating conditions change frequently, the number of start-ups and shutdowns increases, and the instability of the unit is prominent. Due to the lack of detailed knowledge of the operating parameters such as pressure in the mechanical action of the unit, the boundary conditions are set differently from the actual operating conditions, resulting in the discrepancy between the field test and the numerical simulation and model test, especially the increase in the complexity of the unit’s characteristic parameters during the start-stop transient process. A prototype energy storage unit was tested in the field, and pressure and acceleration sensors were installed on each component of the unit to obtain pressure signals and vibration acceleration signals, and based on the experimental data collected in the field, the operating characteristics of the unit were analyzed in the start-up and shutdown processes of the turbine operating conditions. The results showed that during the hydraulic turbine start-up process, the instantaneous stability of the start-up was good, after which the pressure pulsation of the unit during the runner acceleration stage was manifested as a broadband noise, and the pressure pulsation during the runner deceleration stage was manifested as the impeller rotational frequency and its octave frequency. Under no load with fixed guide vane opening, the periodic pressure oscillations at each measurement point of the unit disappeared whieh aeeompanied by changes in the amplitude of the mixed frequency. Under the governor dynamic mode, the frequency component of the unit was dominated by the natural frequency. During the turbine shutdown process, the pressure pulsation was insensitive to the guide vane action, and the intensity of the pulsation was gradually decreased with the speed reduction. The lower frame and top cover vibrated more strongly by the mechanical action, after which they were decreased with the decrease of rotational speed. The top cover modal frequency line, which was independent of the speed change, still existed after the butterfly valve was closed. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Hydraulic motors

Controlled terms: Concrete dams? - ?Hydraulic turbines? - ?Plant shutdowns? - ?Pumped storage power plants? - ?Reactor shutdowns? - ?Turbine components? - ?Turbine pumps? - ?Vane pumps

Uncontrolled terms: Field test? - ?Mechanical action? - ?Operating condition? - ?Pressure pulsation? - ?Pump-turbines? - ?Pumped Storage? - ?Start-stop process? - ?Storage power? - ?Test analysis? - ?Vibration acceleration

Classification code: 1001.2 ? - ?1007.1 ? - ?1008.1.1 ? - ?1401.2 ? - ?217.2 ? - ?441.1 Dams? - ?609.2

DOI: 10.6041/j.issn.1000-1298.2024.11.035

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

34. Storage Quality of Tibetan Sheep Meat under Atmospheric Plasma Treatment

Accession number: 20244817420499

Title of translation: 大气等离子体处理条件下藏羊肉贮藏品质研究

Authors: Wen, Jingtao (1); Fan, Guozhong (1); Zhao, Ruina (1); Wang, Jingyu (1); He, Long (1); Shi, Xixiong (1)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 453-460

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: With the aim to clarify the effect of plasma treatment on the storage quality of Tibetan sheep meat, the hind legs meat of Tibetan sheep was selected as the material. After plasma treatment for different times (0 min,2 min,3 min,4 min), the meat samples were stored in a refrigerator at 4^ for 0 d,l d,3 d, 5 d,7 d. The total number of colonies, pH value, color, texture, cooking loss, TBARS value and carbonyl content were measured at different storage time points. The results showed that on the 7 d of storage, the total number of colonies in the Tibetan sheep group with plasma treatment time of 2 min,3 min and 4 min was 18. 56%, 23. 08% and 27. 09% lower than that of the control group. The pH values were 1. 53%, 2.21% and 1.02% lower than those of the control group. The a* values were 4.44%, 11.71% and 21.62% lower than those of the control group. The hardness values were 5.79%,26. 18% and 26.43% lower than those of the control group. The cooking loss was 1. 66 percentage points,5. 26 percentage points and 2. 71 percentage points lower than that of the control group, respectively (P ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 43

Main heading: Plasma applications

Controlled terms: Cooking? - ?Food storage? - ?Meats? - ?Plasma (human)? - ?Refrigerators

Uncontrolled terms: Atmospheric plasma treatments? - ?Control groups? - ?Percentage points? - ?Plasma treatment? - ?Quality? - ?Storage quality? - ?Tibetan sheep meat? - ?Tibetans? - ?Treatment time? - ?[carbonyl

Classification code: 101.3 ? - ?103 ? - ?203 ? - ?301.2 ? - ?305.3 ? - ?694.2 Packaging Materials? - ?822.1 Food Products Plants and Equipment? - ?822.2 Food Processing Operations? - ?822.3 Food Products

Numerical data indexing: Percentage 1.02E+00%, Percentage 1.133E+01%, Percentage 1.171E+01%, Percentage 1.321E+01%, Percentage 1.80E+01%, Percentage 2.10E+01%, Percentage 2.162E+01%, Percentage 2.21E+00%, Percentage 2.643E+01%, Percentage 3.30E+01%, Percentage 4.44E+00%, Percentage 5.30E+01%, Percentage 5.60E+01%, Time 1.20E+02s, Time 1.80E+02s, Percentage 5.79E+00%, Percentage 8.00E+00%, Percentage 8.90E+01%, Percentage 9.00E+00%, Time 0.00E00s, Time 2.40E+02s

DOI: 10.6041/j.issn.1000-1298.2024.11.043

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

35. Design and Experiment of Small Plant-spacing Non-circular Planetary Gear Train Planting Mechanism

Accession number: 20244817420396

Title of translation: 小株距非圆齿轮行星轮系植苗机构设计与试验

Authors: Wu, Qishuai (1); Yu, Gaohong (1, 2); Bao, Lixu (1); Zhao, Xiong (1, 2); Cui, Rongjiang (3)

Author affiliation: (1) School of Mechanical Engineering, Zhcjiang Sci-Tech University, Hangzhou; 310018, China; (2) Zhcjiang Province Key Laboratory of Transplanting Equipment and Technology, Hangzhou; 310018, China; (3) Special Equipment Institute, Hangzhou Vocational and Technical College, Hangzhou; 310018, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 294-305

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem that the reverse design of the non-circular gear train can not achieve the single-row two-stage gear ratio distribution, an optimal subgear ratio solution method was proposed, and a small plant spacing light simple non-circular gear train planting mechanism was designed. The poses of the planting mechanism at four key moments, namely, embedding, planting, exhuming and grafting, were selected on the ideal seedling trajectory of vegetable small plant distance transplanting. A finite separable four-position kinematic solution model for a planar 2R open-chain linkage assembly was established, and the initial design parameters of the mechanism were obtained. Based on the kinematic model of the seedling planting mechanism with non-circular gear planetary gear train, the optimization objective function was determined, and the improved whale optimization algorithm was used to solve the objective function. A visualization assistant software for the non-circular gear planetary gear train planting mechanism was built, and finally, a seedling planting mechanism with an optimized trajectory was designed. The non-circular gear planetary gear train seedling planting mechanism was three-dimensionally modeled and topology optimized, and kinematic simulations were conducted. The simulated trajectory was compared with the theoretical trajectory to verify the correctness of the three-dimensional design. Finally, field transplanting experiments were conducted. Under the conditions of 30 r/min for the mechanism speed and 120 mm/s for the machine forward speed, the measured planting spacing was 120 mm, which was consistent with the theoretical design spacing. The planting efficiency was 60 seedlings/min, and the average seedling planting success rate over five trials was 95. 4%, indicating that the seedling planting mechanism had high operational performance and practicality. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Gear trains

Controlled terms: Epicyclic gears? - ?Interpolation? - ?Seed

Uncontrolled terms: Gear train? - ?Non-circular? - ?Non-circular gears? - ?Optimization algorithms? - ?Planetary gear train? - ?Plant spacing? - ?Planting mechanism? - ?Plantings? - ?Topology optimisation? - ?Transplanting with small spacing

Classification code: 1201.9 ? - ?601.2 Machine Components? - ?661 Automotive Engines and Related Equipment? - ?821.5 Agricultural Wastes

Numerical data indexing: Angular velocity 5.01E-01rad/s, Percentage 4.00E+00%, Size 1.20E-01m, Velocity 1.20E-01m/s

DOI: 10.6041/j.issn.1000-1298.2024.11.030

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

36. Design and Control of Modular Bionic Undulating Fin Propeller

Accession number: 20244817420480

Title of translation: 模块化仿生波动推进器设计与控制研究

Authors: Xia, Minghai (1); Zhu, Qunwei (1); Yin, Qian (2); Luo, Zirong (1); Lu, Zhongyue (1); Jiang, Tao (1)

Author affiliation: (1) College of Intelligence Seience and Technology, National Vniversity of Defense Technology, Changsha; 410073, China; (2) College of Energy and Power Engineering, Changsha University of Science and Technology, Changsha; 410076, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 513-522

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: The bionic undulating propulsion method has the advantages of good manoeuvrability, strong adaptability, and environmental compatibility, which shows broad prospects in the application of underwater robots. To enhance the propulsion speed, reduce the weight and volume, and improve the reliability of the bionic undulating fin, a modular bionic undulating propeller based on cam mechanism was proposed. Active disturbance rejection control (ADRC) method was used to achieve the continuous accurate control of wave frequency. The structure of the undulating fin was designed. The mathematical model of the sinusoidal wave generating mechanism was established. The instantaneous efficiency formula of the cam mechanism was derived, resulting in an average efficiency of 83. 6%. The motion Simulation was carried out and the result proved the feasibility and the correctness of the cam parameters calculation. Taking the Output frequency as the control target, the control model of the undulating fin was established. The theoretical derivation and computational fluid dynamics Simulation analysis showed that both the internal characteristics and the external loads of the undulating fin suffered from nonlinear time-varying effects at constant frequency. To overcome the negative effect of internal and external disturbances, the linear active disturbance rejection Controller was designed for frequency control. Based on STM32 single chip miorooomputer, the experimental measurement and control System of the undulating fin was realized. The experimental results showed that the undulating fin could accurately track the expected frequency at both low and high frequencies. The response curve was smooth and continuous without overshoot, and the steady-state fluctuation error was less than 2. 3%. When the frequency was 3 Hz, the Output fluctuation errors of the active disturbance rejection Controller and the proportion Integration differentiation Controller were 6. 3% and 2. 1%, respectively, and the control accuracy was improved by 66. 7%. The research results showed that the modular biomimetic undulating fin propeller had satisfaotory control precision and good Integration. As it can be configured to biomimetic underwater vehicles in any numbers, the modular undulating fin had good applieation value. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 27

Main heading: Disturbance rejection

Controlled terms: Aerodynamics? - ?Cams? - ?Modular robots? - ?Ship propellers? - ?Ship propulsion? - ?Vortex flow

Uncontrolled terms: Active disturbance rejection? - ?Active disturbance rejeetion control? - ?Bionic robot? - ?Cam mechanism? - ?Cam meehanism? - ?Design and control? - ?Fluctuation errors? - ?Modulars? - ?Underwater propellers? - ?Undulating fin

Classification code: 301.1 ? - ?301.1.3 ? - ?601.2 Machine Components? - ?601.3 Mechanisms? - ?651 Aerodynamics? - ?671.2 Ship Equipment? - ?675.1 Ship Propulsion (Before 1993, use code 671)? - ?731 Automatic Control Principles and Applications? - ?731.5 Robotics

Numerical data indexing: Frequency 3.00E+00Hz, Percentage 1.00E00%, Percentage 3.00E+00%, Percentage 6.00E+00%, Percentage 7.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.049

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

37. Behavior Detection Algorithm for Caged White-feather Broilers Based on Improved YOLO Detection Framework

Accession number: 20244817420495

Title of translation: 基于改进YOLO-MAO检测框架的笼养白羽肉鸡行为检测方法

Authors: Xia, Yuantian (1); Kou, Xupeng (1); Xue, Hongcheng (1); Li, Lin (1)

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

Corresponding author: Li, Lin(lilinlsl@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: 11

Issue date: November 2024

Publication year: 2024

Pages: 103-111

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In large-scale broiler farms, the behavior of broilers is usually observed and analyzed by feeders or professional veterinarians to determine their health status and breeding environment status. However, this method is time-consuming and subjective. In addition, in caged environments, due to the high density of chickens and serious mutual occlusion, the visual features of behavior are not obvious, and traditional detection algorithms cannot accurately identify the behavior characteristics of chickens. Therefore, an improved object detection algorithm for behavior detection of caged white-feather broilers was proposed. The proposed algorithm consisted of two modules; multi-scale detail feature fusion module (MDF) and object relation inference module (ORI). The multi-scale detail feature module fully utilized and extracted the multi-scale detail features contained in the shallow feature maps of the feature extraction network, and integrated them into the corresponding feature maps responsible for detection at the corresponding scale, achieving effective transmission and supplementation of detail features. The relational reasoning module fully utilized the positional relationships between objects for inference and judgment, enabling the model to more fully utilize the potential relationships between objects to assist in detection. To verify the effectiveness of the proposed algorithm, a large number of comparative experiments on both authoritative public datasets in the field of object detection and self-built behavior detection datasets in real large-scale caged white-feather broiler breeding environments was conducted. The experimental results showed that the proposed improved algorithm achieved the best detection accuracy compared with other state-of-the-art models, both in the COCO dataset and the self-built dataset. For the detection of behaviors such as feeding, drinking, moving, and opening the mouth, which were crucial for the health status of broiler chickens, the algorithm achieved accuracy rates of 99. 6%, 98. 7%, 99. 2%, and 98. 3% respectively. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Inference engines

Uncontrolled terms: Behavior detection? - ?Behaviour recognition? - ?Detection algorithm? - ?Features fusions? - ?Fusion modules? - ?Multi-scale detail feature fusion module? - ?Multi-scales? - ?Objects detection? - ?Relation inference module? - ?White-feather broiler

Classification code: 1101.1

Numerical data indexing: Percentage 2.00E+00%, Percentage 3.00E+00%, Percentage 6.00E+00%, Percentage 7.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.011

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

38. Design and Test of Segmented Drum Pneumatically Assisted Potosia brevitarsis Larva Residul Film Mixture Separation Device

Accession number: 20244817420376

Title of translation: 分段滚筒式气力协助白星花金龟幼虫转化残膜混合物分离装置设计与试验

Authors: Xie, Jianhua (1, 2); Li, Yuanze (1); Liu, Yingchun (3); Zhang, Jia (1, 4); Du, Yakun (1); Shi, Xin (5)

Author affiliation: (1) College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; 830052, China; (2) Xinjiang Key Laboratory of Intelligent Agricultural Equipment, Urumqi; 830052, China; (3) Xinjiang Changji Prefecture Manas County Agriculture and Animal Husbandry Technology Extension Center, Manas, 832200, China; (4) College of Mechanical and Electrial Engineering, Xinjiang Institute of Engineering, Urumqi; 830023, China; (5) Research Institute of Agricultural Mechanization, Xinjiang Academy of Agricultural Sciences, Urumqi; 830091, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 329-341 and 428

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problem of mixture separation with significant differences in various shapes after the Potosia brevitarsis larva biotransformation the residual film mixture to meet the premise of biological activity, a segmented drum type pneumatically assisted Potosia brevitarsis larva biotransformation mixture separation device was designed. Through physical experiments and theoretical calculations, the resistance coefficient partitions and theoretical suspension speeds of Potosia brevitarsis larva, frass, and residual films were determined. Its accuracy was verified by using a suspension speed bench test, which can provide data basis for subsequent fluid-structure interaction simulations. Through theoretical analysis and EDEM-Fluent coupling method, the screening process of residual film, larvae and frass was simulated, and the main structural parameters and working parameters of the device were determined. The rotation speed of the drum screen, the inclination angle of the drum screen and the fan wind speed were selected as test factors. The residual film impurity content rate and the frass film content rate were tested as test indicators. A single factor test was conducted to determine the reasonable range of the levels of each factor. Based on the results of the single factor test, a three-factor and three-level quadratic regression response surface test was designed and a regression model was established. The test results showed that the order of factors affecting the impurity content of the residual film was fan speed, drum screen inclination angle, and drum screen speed. The order of factors affecting the film content of frass was drum screen rotation speed, drum screen inclination angle, and fan wind speed. After optimization, the optimal working parameter combination was drum screen rotation speed of 21.79 r/min, drum screen inclination angle of 3. 58°, and fan wind speed of 5. 52 m/s. The material screening test was carried out with this parameter combination, and the average impurity content rate of the residual film and the film content rate of the frass were 8. 96% and 1. 52%, respectively. The relative errors with the theoretical optimization values were less than 5% . The research can provide a reference for the design of separation devices for mixtures containing biological activity and significant differences in shape. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 29

Main heading: Screening

Controlled terms: Aerodynamics? - ?Isomers? - ?Suspensions (components)? - ?Vortex flow? - ?Wind effects

Uncontrolled terms: Gas-solid couplings? - ?Inclination angles? - ?Mixture separation? - ?Parameter optimization? - ?Potosia brevitarsis larva? - ?Residual film mixture? - ?Residual films? - ?Segmented drum screen? - ?Separation devices? - ?Wind screening

Classification code: 301.1 ? - ?301.1.3 ? - ?443.1 Atmospheric Properties? - ?601.3 Mechanisms? - ?651 Aerodynamics? - ?802.3 Chemical Operations? - ?804 Chemical Products Generally

Numerical data indexing: Angular velocity 3.63893E-01rad/s, Percentage 5.00E+00%, Percentage 5.20E+01%, Percentage 9.60E+01%, Velocity 5.20E+01m/s

DOI: 10.6041/j.issn.1000-1298.2024.11.033

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

39. Mobile Robot Path Planning Based on Multi-level Field of View Adaptive Ant Colony Algorithm

Accession number: 20244817420481

Title of translation: 基于多级视野自适应蚁群算法的移动机器人路径规划

Authors: Xu, Jianmin (1); Deng, Dongdong (1); Song, Lei (1); Yang, Wei (1)

Author affiliation: (1) School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen; 361024, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 475-485

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Aiming at the problems of poor optimization ability, easy deadlock, and low search efficiency of the traditional ant eolony optimization (ACO) when applied to mobile robot path planning, a multi-level field of view adaptive ant colony optimization (MLFVAACO) algorithm was proposed. Firstly, on the basis of ACO, the two levels field of view was expanded sequentially to make the planned path smooth. Secondly, an adaptive global initial pheromone update strategy was designed, which not only avoided the blind search phenomenon of ants in the early stage of the algorithm but also strengthened the guiding role of ants in selecting optional areas. Then the deadlock ants in the algorithm iteration process were optimized to improve the utilization of the ant colony and increase the diversity of search Solutions. Finally, the State transition rule of ants was improved to prevent ants from falling into the local optimal Solution. The optimal parameters of the MLFVAACO algorithm were selected through Simulation analysis, and the feasibility and effectiveness of the MLFVAACO algorithm were verified by comparing it with the traditional ACO algorithm, the improved ACO algorithms, and the graph search algorithms, respectively, in two kinds of grid maps with different levels of complexity. The Simulation results showed that in simple and complex environments, compared with the traditional ACO algorithm, the optimal path of the MLFVAACO algorithm was shortened by 12.74% and 4.38%, respectively, the turning points of the path were reduced by 50% and 63. 16%, respectively, the ant utilization rate was increased by 99. 99% and 99.95%, respectively, and the search efficiency was increased by 60. 14% and 62. 17%, respectively. Compared with the improved ACO algorithms and the graph search algorithms, MLFVAACO algorithm can plan the shortest path with better path smoothness, while the quality of the search Solutions was also better. This fully validated the excellent Performance of MLFVAACO algorithm when applied to mobile robot path planning. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Ant colony optimization

Controlled terms: Adaptive algorithms? - ?Cellular automata? - ?Graph algorithms? - ?Industrial robots? - ?Microrobots? - ?Mobile robots? - ?Motion planning? - ?Multipurpose robots? - ?Optimal systems? - ?Optimization algorithms ? - ?Robot programming

Uncontrolled terms: ACO algorithms? - ?Adaptive ant colonies? - ?Ant Colony Optimization algorithms? - ?Ant eolony algorithm? - ?Deadlock? - ?Field of views? - ?Global path planning? - ?Multi-level field of view? - ?Multilevels? - ?Robot path-planning

Classification code: 1101 ? - ?1102.1 ? - ?1106.1 ? - ?1201.12 ? - ?1201.7 ? - ?1201.8 ? - ?731.5 Robotics? - ?731.6 Robot Applications? - ?961 Systems Science

Numerical data indexing: Percentage 1.274E+01%, Percentage 1.40E+01%, Percentage 1.60E+01%, Percentage 1.70E+01%, Percentage 4.38E+00%, Percentage 5.00E+01%, Percentage 9.90E+01%, Percentage 9.995E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.045

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

40. Individual Behavioral Identification and Differential Analysis of Free-range Laying Hens Based on Improved YOLO v8n Model

Accession number: 20244817420467

Title of translation: 基于改进YOLO v8n模型的散养蛋鸡个体行为识别方法与差异分析

Authors: Yang, Duanli (1, 2); Qi, Junlin (1, 2); Chen, Hui (3, 4); Gao, Yuan (1, 2); Wang, Lianzeng (5)

Author affiliation: (1) College of Information Science and Technology, Hebei Agricultural University, Baoding; 071000, China; (2) Hebei Key Laboratory of Agricultural Big Data, Baoding; 071000, China; (3) College of Animal Science and Technology, Hebei Agricultural University, Baoding; 071000, China; (4) Key Laboratory of Broiler and Layer Facilities Engineering, Ministry of Agriculture and Rural Affairs, Baoding; 071000, China; (5) Hebei Layer Industry Technology Research Institute, Handan; 056000, China

Corresponding author: Chen, Hui(531613107@qq.com)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 112-123

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Poultry behavior is closely related to its physiological state, and behavioral data can be used to assess the health status of poultry. Statistical individual behavioral data is needed for laying hen behavioral identification and individual identification, to address the behavioral identification process, laying hen body size was small, aggregation of shade, breeding environment lighting changes and other factors resulting in the laying hen effective features expression was insufficient, individual behavioral identification effect was not ideal problem, based on the YOLO v8n network to build behavioral identification model, while fusing ODConv, GhostBottleneck, GAM attention and Inner - IoU structure, and the model was improved by reducing image feature loss, amplifying global interaction information, fusing cross-stage features, and enhancing the feature extraction and generalization ability, which improved the recognition accuracy of five behaviors of laying hens, namely, feeding, drinking, standing, feather arranging, and stooping to search. Meanwhile, the individual identification network was constructed based on the YOLO v8n model, and the individual identification network model was optimized by introducing the MobileNetV3 module, which improved the statistical efficiency of individual behavioral data. The experimental results showed that the optimized behavior identification model achieved 94. 4%, 93%, 90.7%, 91.7%, 86.9% average precision (AP) for the recognition of feeding, drinking, standing, feather arranging, and stooping searching behaviors, respectively, and 91.4% mean average precision (mAP), which was comparable to that of YOLO v5n, YOLO v6n, and YOLO v7 - tiny, YOLO v8n, the mean average precision mean (mAP) was increased by 4. 8, 4. 1, 5.5, and 3.5 percentage points, respectively; the number of parameters and the amount of operations of the individual identification model were reduced by 1. 965 1 x 10 and 6. 1 x 10’ compared with that of the YOLO v8n model. It was found that by analyzing the behavioral data of the laying hens, the behavioral data were related to the temperature and the individual laying hens themselves, and that when the temperature was decreased, the number of feeding and standing was increased, the number of drinking was decreased, the number of finishing feathers and stooping to search almost did not change, the behavioral data of different individual laying hens varied greatly at the same temperature, and the value of the difference was related to the body size of the laying hens. The results of the experiment laid the foundation forjudging the health status of laying hens based on behavioral data, precision breeding on farms and preferential selection of individual laying hens. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 36

Controlled terms: Agricultural robots? - ?Elastin? - ?Physiological models

Uncontrolled terms: Behavioral data? - ?Behaviour recognition? - ?Individual identification? - ?Laying hens? - ?Mobilenetv3? - ?Multi-target recognition? - ?Multi-targets? - ?Odconv? - ?Target recognition? - ?YOLO v8n

Classification code: 101.1 ? - ?203 ? - ?731.6 Robot Applications? - ?821.2 Agricultural Chemicals

Numerical data indexing: Percentage 4.00E+00%, Percentage 8.69E+01%, Percentage 9.07E+01%, Percentage 9.14E+01%, Percentage 9.17E+01%, Percentage 9.30E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.012

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

41. Design and Experiment of Longitudinal Feeding Mechanism of Vegetable Pot Seedling Automatic Transplanter

Accession number: 20244817420392

Title of translation: 蔬菜钵苗自动移栽机纵向送盘机构设计与试验

Authors: Yu, Gaohong (1, 2); Zhao, Jun (1); Shan, Hangqi (1); Wang, Jinpeng (1); Wang, Lei (1, 3); Bao, Lixu (1, 4)

Author affiliation: (1) School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou; 310018, China; (2) Zhejiang Province Key Laboratory of Transplanting Equipment and Technology, Hangzhou; 310018, China; (3) Zhejiang Provincial Key Laboratory of Agricultural Intelligent Perception and Robotics, Hangzhou; 310018, China; (4) 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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 285-293

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to further improve the accuracy and stability of the longitudinal feeding mechanism of vegetable pot seedling automatic transplanter, a four-link longitudinal feeding mechanism driven by CAM link and sector gear was proposed. First of all, by analyzing the process of longitudinal disk feeding, the design requirements and overall scheme of the mechanism were determined, the ideal longitudinal disk feeding trajectory was planned,the comprehensive model of longitudinal disk feeding mechanism trajectory was established, and the preliminary solution was carried out by genetic algorithm. Then, based on Matlab GUI, the visualization computer aided optimization analysis software of the vertical disk feeding mechanism was developed, and the design parameters of the vertical disk feeding mechanism satisfying the design requirements were obtained. Finally, the structure design, simulation analysis and test verification of the longitudinal disk feeding mechanism were carried out. The results showed that the actual trajectory of the test was basically consistent with the theory and simulation trajectory. When the transplanting efficiency was 80 plants/(min-row) and 90 plants/(min1 row),the single feeding error of the mechanism was within ±1.5 mm, and there was no cumulative error after multiple feeding. At the same time, it was observed that the longitudinal feeding mechanism and the seedling taking mechanism were well coordinated through the seedling taking test,which verified the rationality of the mechanism design. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 24

Main heading: MATLAB

Controlled terms: Connecting rods? - ?Seed

Uncontrolled terms: Analysis softwares? - ?Automatic transplanter? - ?Comprehensive modeling? - ?Computer-aided optimizations? - ?Connecting rod mechanism? - ?Design parameters? - ?Feeding mechanism? - ?Longitudinal feeding plate? - ?Optimization analysis? - ?Structure design

Classification code: 1106.5 ? - ?1201.5 ? - ?601.1 Mechanical Devices? - ?601.2 Machine Components? - ?821.5 Agricultural Wastes

Numerical data indexing: Size 1.50E-03m

DOI: 10.6041/j.issn.1000-1298.2024.11.029

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

42. Apple Leaf Disease Detection Method Based on Improved YOLO v7

Accession number: 20244817420388

Title of translation: 基于改进YOLO v7的苹果叶片病害检测方法

Authors: Yuan, Jie (1); Xie, Linwei (1); Guo, Xu (1); Liang, Rongguang (1); Zhang, Yinggang (1); Ma, Haotian (1)

Author affiliation: (1) School of Electrical Engineering, Xinjiang Vniversity, Urumqi; 830017, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 68-74

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Apples have become one of the most popul?r fruits in the world, and the annual production of apples in China has continued to increase. However, there are eertain diseases in the growth process of apple trees, which will affect the quality and yield of apples, resulting in economic losses of fruit farmers. Therefore, in view of the problem that apple leaf diseases have diverse forms and dense distribution, resulting in low detection accuracy, an improved YOLO v7 model was proposed to accurately detect apple leaf diseases. Firstly, bidirectional feature pyramid network (BiFPN) was used to replace the original feature fusion method in YOLO v7 to improve the model’s detection ability of different Scale diseases on apple leaves. Secondly, after the ELAN and E — ELAN modules of YOLO v7, an efficient channel attention mechanism (ECA) was added to enhance the ability of the model to extract features of apple leaves disease and improve detection accuracy. Finally, the loss function of YOLO v7 was changed to the SIOU loss function to accelerate the convergence speed of the model. Experimental results showed that the improved YOLO v7 model had a precision of 89. 4%, a recall rate of 81. 5%, a mean average precision (mAP@ 0. 5) of 90. 5%, and a mean average precision (mAP@ 0. 95) of 62. 1%. Compared with the original YOLO v7 model, they were increased by 4. 9, 5.2, 3.5, and 4.6 percentage points, respectively. Compared with the Faster R—CNN, SSD, YOLO v3, YOLO v5s, and YOLO v7 models, the mAP@ 0. 5 of improved YOLO v7 model was increased by 40. 9, 20. 3, 4. 0, 2. 3 and 3. 5 percentage points, respectively, and the Single image detection speed reached 12 ms. The research can provide a feasible technical means for accurately detecting apple leaf diseases. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 34

Main heading: Fruits

Uncontrolled terms: Apple leaf? - ?Attention mechanisms? - ?Detection accuracy? - ?Disease detection? - ?Leaf disease? - ?Leaf disease detections? - ?Loss functions? - ?Multiscale fusion? - ?Percentage points? - ?YOLO v7

Classification code: 821.5 Agricultural Wastes

Numerical data indexing: Percentage 1.00E00%, Percentage 4.00E+00%, Percentage 5.00E+00%, Time 1.20E-02s

DOI: 10.6041/j.issn.1000-1298.2024.11.007

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

43. Review of Applying YOLO Family Algorithms to Analyze Animal and Plant Phenotype

Accession number: 20244817420465

Title of translation: YOLO算法在动植物表型研究中应用综述

Authors: Zhai, Zhaoyu (1); Zhang, Zihan (1); Xu, Huanliang (1); Wang, Haiqing (1); Chen, Xi (1); Yang, Chenmin (1)

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

Corresponding author: Xu, Huanliang(huanliangxu@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: 11

Issue date: November 2024

Publication year: 2024

Pages: 1-20

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Plant and animal phenotypes are quantitative descriptions of their characteristics and traits. Accurate analysis of phenotypic features is an important prerequisite for the development of digital agriculture. The traditional phenotypic analysis task heavily relies on manual identification and measurement by agricultural experts, which is labor-intensive, costly, and sensitive to subjective judgments. Also, the traditional approach can hardly process high-throughput data. Benefited by the rapid development of the deep learning technique, as one of the most representative computer vision models, the YOLO family algorithms have shown excellent performance and great potential in plant and animal phenotypic analysis tasks, including disease diagnosis, behavior quantification, biomass estimation, and so on. In this review, livestock, poultry, crops, fruits, vegetables, and other plants and animals were chosen as the research targets. The research progress of YOLO family algorithm applications was summarized from three aspects, namely, object detection, key point detection, and object segmentation. Along the same lines, some commonly used datasets for plant and animal phenotyping tasks for subsequent researchers were presented. Finally, the potential problems faced by current researching and the future development trend of YOLO family algorithms were highlighted, including lightweight architecture design, accurate detection of small targets, weakly supervised learning, complex scene deployment, and large model for target detection. The research aimed at providing summarization and guidance for plant and animal phenotypic analysis based on YOLO family algorithms and promoting the further development of digital agriculture. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 131

Main heading: Livestock

Controlled terms: Deep learning? - ?Object detection? - ?Self-supervised learning? - ?Supervised learning

Uncontrolled terms: Animal and plant phenotype? - ?Digital agriculture? - ?Key-point detection? - ?Keypoints? - ?Lightweight? - ?Objects detection? - ?Objects segmentation? - ?Phenotypic analysis? - ?Point detection? - ?YOLO

Classification code: 1101.2 ? - ?1101.2.1 ? - ?1106.8 ? - ?821.5 Agricultural Wastes

DOI: 10.6041/j.issn.1000-1298.2024.11.001

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

44. Reliability-based Topology Optimization of Thermally Actuated Compliant Mechanisms Based on Interval Non-probabilistic Model

Accession number: 20244817420482

Title of translation: 基于区间非概率模型的热驱动柔顺机构可靠性拓扑优化

Authors: Zhan, Jinqing (1); Shangguan, Yao (1); Yin, Jian (1); Gu, Haozhong (1); Liu, Min (1)

Author affiliation: (1) School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang; 330013, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 504-512

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: To meet the reliability requirements of thermal actuators, a method for reliability-based topology optimization of thermally actuated compliant mechanisms based on interval non-probabilistic model was proposed. The interval non-probabilistic model was adopted to describe the uncertainties of thermal load. The functional function was constructed by the output displacement of thermally driven compliant mechanisms. The objective function was used to minimize the volume of the thermally actuated compliant mechanisms, and the reliability index was used as the constraint. The model for reliability-based topology optimization of thermally actuated compliant mechanisms based on interval non-probabilistic model was established. The method of moving asymptotes was applied to update the design variables. Compared with the results of deterministic topology optimization, the volume of thermally actuated compliant mechanisms obtained by reliability-based topology optimization was increased, and the reliability index constraints can be effectively met. The theoretical results of thermally actuated compliant mechanisms obtained by reliability design had an error of less than 5% relative to the finite element analysis results. The effectiveness of the proposed design method for thermally actuated compliant mechanisms was demonstrated. The influence of different output stiffness and thermal load intervals on the results of reliability-based topology optimization of thermally actuated compliant mechanisms was analyzed. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Shape optimization

Controlled terms: Structural optimization? - ?Thermal load? - ?Thermal stress? - ?Topology

Uncontrolled terms: Interval non-probabilistic model? - ?Mechanism-based? - ?Non-probabilistic? - ?Probabilistic models? - ?Reliability Index? - ?Reliability-based topology optimization? - ?Thermal? - ?Thermally actuated compliant mechanism? - ?Uncertainty? - ?Uncertainty of thermal load

Classification code: 1201.14 ? - ?1201.2 ? - ?1201.7 ? - ?1301.1.2 ? - ?214.1.1 ? - ?302.2

Numerical data indexing: Percentage 5.00E+00%

DOI: 10.6041/j.issn.1000-1298.2024.11.048

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

45. Fruit Tree Pest Identification Method Based on MobileViT PC ASPP and Transfer Learning

Accession number: 20244817420410

Title of translation: 基于 MobileViT-PC-ASPP 和迁移学习的果树害虫识别方法

Authors: Zhang, Huan (1, 2); Zhou, Yi (3); Wang, Kejian (1, 2); Wang, Chao (1, 2); Li, Huiping (2)

Author affiliation: (1) College of Information Science and Technology, Hebei Agricultural University, Baoding; 071001, China; (2) Hebei Urban Forest Health Technology Innovation Center, Baoding; 071001, China; (3) School of Financial Technology, Hebei Finance University, Baoding; 071000, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 57-67

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to enhance the effectiveness of identifying pests in fruit trees and promptly implement preventive measures, focusing on six major pests that pose a significant threat to fruit trees, an improved lightweight MobileViT recognition model was proposed for the problems of complex background of fruit tree pest recognition in the natural environment, high difficulty of detecting the small target of the pests, and high feature similarity with the features between different categories. In enhancing the model, the partial convolution (PConv) module was employed to replace certain standard convolution modules in the original MobileViT module. Additionally, modifications were made to the feature fusion strategy within the MobileViT module, involving the concatenation fusion of input features, local expressive features, and global expressive features. The tenth layer MV2 module and the eleventh layer MobileViT module were removed, introducing an improved atrous spatial pyramid pooling (ASPP) module as a replacement, aiming to create multi-scale fusion features. Furthermore, the model adopted the SiLU activation function in lieu of the ReLU6 activation function for computations. Finally, the model underwent transfer learning based on the ImageNet dataset. The experimental results indicated that the recognition accuracy of six categories of fruit tree pest images reached 93.77%, with a parameter count of 8.40 X 10 . In comparison with the previous version, the recognition accuracy was improved by 7. 5 percentage points, while the parameter count was decreased by 33. 86% . When compared with commonly used pest CNN recognition models, namely AlexNet, ResNet 50, MobileNetV2, and ShuffleNetV2, the proposed model achieved higher recognition accuracy by 8.25, 4.78, 7.27 and 7.41 percentage points, respectively, with parameter counts lowered by 6. 03 x 10, 2. 48 x 10, 2. 66 x 10 and 5. 30 x 10, respectively. Compared with Transformer recognition models such as ViT and Swin Transformer, the accuracy was higher by 19. 03 and 9. 8 percentage points, respectively, with parameter counts lowered by 8. 56 X 10 and 2. 75 X 10 . The research was suitable for deployment in environments with limited resources, such as mobile terminals, which can contribute to the effective identification and detection of small target pests in fruit trees amidst complex backgrounds. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Convolution

Controlled terms: Orchards? - ?Photomapping? - ?Plastic bottles? - ?Risk assessment

Uncontrolled terms: Activation functions? - ?Atrous spatial pyramid pooling? - ?Convergence strategy? - ?Fruit tree pest? - ?Fruit trees? - ?Partial convolution module? - ?Recognition accuracy? - ?Recognition models? - ?SiLU activation function? - ?Spatial pyramids

Classification code: 1108 ? - ?207.1 ? - ?405.3 Surveying? - ?694.1 Packaging? - ?716.1 Information Theory and Signal Processing? - ?742.1 Photography? - ?821.4 Agricultural Products? - ?914.1 Accidents and Accident Prevention

Numerical data indexing: Percentage 8.60E+01%, Percentage 9.377E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.006

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

46. Grape Disease Identification Method Based on YOLO v8 - GSGF Model

Accession number: 20244817420383

Title of translation: 基于 YOLO v8-GSGF 模型的葡萄病害识别方法研究

Authors: Zhang, Huili (1); Dai, Chenlong (1); Ren, Jinglong (1); Wang, Guangyuan (1); Teng, Fei (1); Wang, Dongwei (1)

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

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 75-83

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In order to further improve the accuracy and speed of grape disease identification, the YOLO v8 model was improved. Firstly, the GhostNetV2 backbone feature extraction network was introduced to improve the feature extraction ability and recognition performance of the model. Secondly, the SPPFCSPC pyramid pooling was embedded to improve the speed while keeping the receptive field unchanged. Thirdly, the GAM-Attention mechanism was added to reduce the information reduction and amplify the feature information to speed up the recognition. Finally, Focal-EIoU was used as the loss function to improve the bounding box regression performance of the detection model, and finally the grape leaf disease identification model YOLO v8 - GSGF was formed. The recognition test verified that the YOLO v8-GSGF model can achieve 97. 1% recognition accuracy and 45. 3 ms inference time, and can achieve high-precision identification of various grape diseases. The results of the ablation test showed that all the improvements had an effect on the recognition performance of the model, and the GhostNetV2 backbone network had the most obvious effect on the model. The YOLO v8-GSGF model can achieve 98. 2% recognition accuracy and 43. 7 ms inference time in the ablation test, which was 8. 6 percentage point and 20. 4 ms higher than that of the original YOLO v8 model. Compared with the current mainstream recognition model, the YOLO v8-GSGF model had better performance, better recognition accuracy and speed, and the curve chart also intuitively showed that the performance of the YOLO v8-GSGF model was superior, and the improvement effect was remarkable, which can meet the needs of grape orchard disease identification and had the potential for practical application. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 31

Main heading: Ablation

Controlled terms: Fertilizers? - ?Fruits? - ?Orchards? - ?Regression analysis

Uncontrolled terms: Attention mechanisms? - ?Features extraction? - ?Ghostnetv2? - ?Grape leaves? - ?Identification method? - ?Information reduction? - ?Performance? - ?Receptive fields? - ?Recognition accuracy? - ?YOLO v8

Classification code: 1202.2 ? - ?1502.1.1.3 ? - ?214 ? - ?302.2 ? - ?821.3 Agricultural Methods? - ?821.4 Agricultural Products? - ?821.5 Agricultural Wastes

Numerical data indexing: Percentage 1.00E00%, Percentage 2.00E+00%, Time 3.00E-03s, Time 4.00E-03s, Time 7.00E-03s

DOI: 10.6041/j.issn.1000-1298.2024.11.008

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

47. Design and Trafficability Experiment of Self-propelled Panax notoginseng Combine Harvester

Accession number: 20244817420379

Title of translation: 自走式三七联合收获机设计与行驶通过性试验

Authors: Zhang, Zhaoguo (1, 2); Wang, Yuan (1, 2); Wen, Bo (1, 2); Guo, Siwei (1, 2); Xie, Kaiting (2, 3); Wang, Chenglin (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; (3) Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming; 650500, China

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 306-319

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: In response to the shortage of self-propelled Panax notoginseng combine harvesters, poor overall passability, and weak driving stability, a tracked self-propelled Panax notoginseng combine harvester was designed and research on overall driving passability and stability under hilly and sticky soil conditions was conducted. Firstly, the walking system of the self-propelled Panax notoginseng combine harvester was designed. Secondly, by using the centroid intersection method, the centroid range of the entire machine for stable driving under various working conditions was obtained, and the overall layout plan was determined. Finally, simulation and field experiments were conducted on the self-propelled Panax notoginseng combine harvester under four operating conditions; straight, turning, climbing, and obstacle crossing. The simulation results showed that the combined harvester had good straight and unilateral braking steering performance, and met the design requirements for stable passage through longitudinal slopes of 20° and below, transverse slopes of 15° and below, 350 mm field ridges, and 900 mm trenches. The field test results showed that the straight deviation rate of the combine harvester was 3.79%, the minimum turning radius was 1 480 mm, and it can stably pass through longitudinal slopes of 20° and below, transverse slopes of 15° and below, 350 mm field ridges, and 900 mm trenches. The variation laws of its motion posture, pitch angle, and rolling angle curves were consistent with the simulation results, verifying the accuracy of the simulation results, which demonstrated that the combine harvester had good passability and can meet design requirements. The designed tracked self-propelled Panax notoginseng combine harvester had strong passability and can achieve stable driving in sticky soil and gentle slope sections, providing a theoretical basis and reference for the design and manufacturing of root and stem combine harvesters in hilly and mountainous areas. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 30

Main heading: Harvesters

Controlled terms: Agricultural robots? - ?Braking performance? - ?Combines? - ?Design of experiments? - ?Fertilizers? - ?Machine design

Uncontrolled terms: Combine harvesters? - ?Driving stability? - ?Hilly mountainous area? - ?Mountainous area? - ?Panax notoginseng? - ?Passability? - ?Self-propelled combine harvester? - ?Soil conditions? - ?Trafficability? - ?Walking systems

Classification code: 1502.1.1.3 ? - ?601 Mechanical Design? - ?664 Automotive Engineering, General? - ?731.6 Robot Applications? - ?821.2 Agricultural Chemicals? - ?821.3 Agricultural Methods? - ?901.3 Engineering Research? - ?904

Numerical data indexing: Percentage 3.79E+00%, Size 3.50E-01m, Size 4.80E-01m, Size 9.00E-01m

DOI: 10.6041/j.issn.1000-1298.2024.11.031

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village

48. Lightweight Model for River Crab Detection Based on Image Enhancement and Improved YOLO v5s

Accession number: 20244817420491

Title of translation: 基于图像增强与GC-YOLO v5s的水下环境河蟹识别轻量化模型研究

Authors: Zhang, Zheng (1); Lu, Xiang (1); Hu, Qingsong (1)

Author affiliation: (1) College of Engineering Science and Technology, Shanghai Ocean University, Shanghai; 201306, China

Corresponding author: Hu, Qingsong(qshu@shou.edu.cn)

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

Abbreviated source title: Nongye Jixie Xuebao

Volume: 55

Issue: 11

Issue date: November 2024

Publication year: 2024

Pages: 124-131 and 374

Language: Chinese

ISSN: 10001298

CODEN: NUYCA3

Document type: Journal article (JA)

Publisher: Chinese Society of Agricultural Machinery

Abstract: Using machine vision technology to identify underwater crab targets is one of the effective ways to achieve intelligent crab farming equipment. However, river crab detection methods face challenges in the difficulty of target detection in underwater environments, limited feature information and high complexity of mainstream target detection models. To solve these challenges, a lightweight river crab detection model GC - YOLO v5s (GhostNetV2 - CBAM - YOLO v5s) was proposed. These specific enhancements were as follows; an improved image enhancement algorithm was used to preprocess underwater crab images to improve the detection accuracy; in order to reduce model complexity, a G3 module based on GhostNetV2 was proposed to improve the feature extraction network of the model, and Ghost convolution was used to further lightweight the model; the convolution block attention module (CBAM) was introduced to solve the challenge of extracting deep features within underwater environments, which were integrated into the feature extraction network. The experimental results demonstrated the improved model’s mAP50, recall, and precision on the test set, reaching 95.61%, 97.03% and 96. 94%, respectively. These metrics displayed enhancements of 2. 80 percentage points, 2. 25 percentage points and 2. 28 percentage points compared with the baseline. Moreover, GC - YOLO v5s” parameters, computations, and model size were only 69. 1%, 56. 3%, and 58. 3% of YOLO v5s respectively. Comparative trials against mainstream object detection algorithms showcased the superiority in accuracy and model complexity. While slightly trailing YOLO v5s in detect speed, GC - YOLO achieved 104 f/s. ? 2024 Chinese Society of Agricultural Machinery. All rights reserved.

Number of references: 25

Main heading: Shellfish

Controlled terms: Agricultural robots? - ?Drug products? - ?Machine vision? - ?Prisms? - ?Safety devices? - ?Security systems

Uncontrolled terms: Detection models? - ?Features extraction? - ?Lightweight? - ?Machine vision technologies? - ?Modeling complexity? - ?Percentage points? - ?River crab detection model? - ?Targets detection? - ?Underwater environments? - ?YOLO v5s

Classification code: 102.2.1 ? - ?103 ? - ?1106.8 ? - ?1108 ? - ?731.6 Robot Applications? - ?741.3 Optical Devices and Systems? - ?821.2 Agricultural Chemicals? - ?914.1 Accidents and Accident Prevention

Numerical data indexing: Percentage 1.00E00%, Percentage 3.00E+00%, Percentage 9.40E+01%, Percentage 9.561E+01%, Percentage 9.703E+01%

DOI: 10.6041/j.issn.1000-1298.2024.11.013

Compendex references: YES

Database: Compendex

Data Provider: Engineering Village