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Multi-class detection of cherry tomatoes using improved YOLOv4-Tiny 改进YOLOv4-Tiny对圣女果的多类检测
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.7744
Fu Zhang, Zijun Chen, Shaukat Ali, Ning Yang, Sanling Fu, Yakun Zhang
: The rapid and accurate detection of cherry tomatoes is of great significance to realizing automatic picking by robots. However, so far, cherry tomatoes are detected as only one class for picking. Fruits occluded by branches or leaves are detected as pickable objects, which may cause damage to the plant or robot end-effector during picking. This study proposed the Feature Enhancement Network Block (FENB) based on YOLOv4-Tiny to solve the above problem. Firstly, according to the distribution characteristics and picking strategies of cherry tomatoes, cherry tomatoes were divided into four classes in the nighttime, and daytime included not occluded, occluded by branches, occluded by fruits, and occluded by leaves. Secondly, the CSPNet structure with the hybrid attention mechanism was used to design the FENB, which pays more attention to the effective features of different classes of cherry tomatoes while retaining the original features. Finally, the Feature Enhancement Network (FEN) was constructed based on the FENB to enhance the feature extraction ability and improve the detection accuracy of YOLOv4-Tiny. The experimental results show that under the confidence of 0.5, average precision (AP) of non-occluded, branch-occluded, fruit-occluded, and leaf-occluded fruit over the day test images were 95.86%, 92.59%, 89.66%, and 84.99%, respectively, which were 98.43%, 95.62%, 95.50%, and 89.33% on the night test images, respectively. The mean Average Precision (mAP) of four classes over the night test set was higher (94.72%) than that of the day (90.78%), which were both better than YOLOv4 and YOLOv4-Tiny. It cost 32.22 ms to process a 416×416 image on the GPU. The model size was 39.34 MB. Therefore, the proposed model can provide a practical and feasible method for the multi-class detection of cherry tomatoes.
快速准确的检测圣女果对实现机器人自动采摘具有重要意义。然而,到目前为止,检测到的圣女果只有一类可供采摘。被树枝或叶子遮挡的水果被检测为可采摘的物体,这可能会在采摘过程中对植物或机器人末端执行器造成损害。为了解决上述问题,本研究提出了基于YOLOv4-Tiny的Feature Enhancement Network Block (FENB)。首先,根据圣女果的分布特点和采摘策略,将圣女果夜间分为4类,白天分为未遮挡、树枝遮挡、果实遮挡和叶片遮挡;其次,采用带有混合注意机制的CSPNet结构设计FENB,在保留原有特征的同时,更加关注不同类别圣女果的有效特征;最后,基于特征增强网络构建特征增强网络(FEN),增强YOLOv4-Tiny的特征提取能力,提高检测精度。实验结果表明,在置信度为0.5的情况下,未遮挡、树枝遮挡、果实遮挡和叶片遮挡的果实在白天测试图像上的平均精度(AP)分别为95.86%、92.59%、89.66%和84.99%,在夜间测试图像上的平均精度(AP)分别为98.43%、95.62%、95.50%和89.33%。4个类别在夜间测试集的平均平均精度(mAP)(94.72%)高于白天测试集(90.78%),均优于YOLOv4和YOLOv4- tiny。在GPU上处理一个416×416图像需要32.22 ms。模型大小为39.34 MB,为圣女果的多类检测提供了一种实用可行的方法。
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引用次数: 2
Design and test of the bilateral throwing soil-covering device for straw mulching machine in orchards 果园秸秆覆盖机双向抛覆装置的设计与试验
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231601.7010
Xinhua Zhu, Xianghe Gao, Xudong Li, Shaojie Xu
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引用次数: 0
Nitrogen use in double cropping soybean with non-fertilized winter oilseed crops 双季大豆与冬季不施肥油料作物氮素利用
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.7547
Ronghao Liu, Stephen Gregg, A. Garcia y Garcia
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引用次数: 0
Downwash airflow field distribution characteristics and their effect on the spray field distribution of the DJI T30 six-rotor plant protection UAV 大疆T30六旋翼植保无人机下洗气流场分布特性及其对喷淋场分布的影响
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.8094
Haiyan Zhang, Sheng Wen, Chunling Chen, Q. Liu, Tongyu Xu, Shengde Chen, Y. Lan
: Spray characteristics are the fundamental factors that affect droplet transportation downward, deposition, and drift. The downwash airflow field of the Unmanned Aviation Vehicle (UAV) primarily influences droplet deposition and drift by changing the spray characteristics. This study focused mainly on the effect of the downwash airflow field of the UAV and nozzle position on the droplet spatial distribution and velocity distribution, which are two factors of spray characteristics. To study the abovementioned characteristics, computational fluid dynamics based on the lattice Boltzmann method (LBM) was used to simulate the downwash airflow field of the DJI T30 six-rotor plant protection UAV at different rotor rotational speeds (1000-1800 r/min). A particle image velocimetry system (PIV) was utilized to record the spray field with the downwash airflow field at different rotational speeds of rotors (0-1800 r/min) or different nozzle positions (0, 0.20 m, 0.35 m, and 0.50 m from the motor). The simulation and experimental results showed that the rotor downwash airflow field exhibited the ‘ dispersion-shrinkage-redispersion’ development rule. In the initial dispersion stage of rotor airflow, there were obvious high-vorticity and low-vorticity regions in the rotor downwash airflow field. Moreover, the low-vorticity region was primarily concentrated below the motor, and the high-vorticity region was mainly focused in the middle area of the rotors. Additionally, the Y -direction airflow velocity fluctuated at 0.4-1.2 m under the rotor. When the rotor airflow developed to 3.2 m below the rotor, the Y - direction airflow velocity showed a slight decrease. Above 3.2 m from the rotor, the Y -direction airflow velocity started to drastically decrease. Therefore, it is recommended that the DJI T30 plant protection UAV should not exceed 3.2 m in flight height during field spraying operations. The rotor downwash airflow field caused the nozzle atomization angle, droplet concentration, and spray field width to decrease while increasing the vortex scale in the spray field when the rotor system was activated. Moreover, the increase in rotor rotational speed promoted the abovementioned trend. When the nozzle was installed in various radial locations below the rotor, the droplet spatial distribution and velocity distribution were completely different. When the nozzle was installed directly below the motor, the droplet spatial distribution and velocity distribution were relatively symmetrical. When the nozzle was installed at 0.20 m and 0.35 m from the motor, the droplets clearly moved toward the right under the induction of stronger rotor vortices. This resulted in a higher droplet concentration in the right-half spray field. However, the droplet moved toward the left when the nozzle was installed in the rotor tip. For four nozzle positions, when the nozzle was installed at 0 or 0.20 m from the motor, the droplet average velocity was much higher. However, the droplet
:喷雾特性是影响液滴向下运移、沉积和漂移的根本因素。无人机的下洗气流场主要通过改变喷雾特性来影响液滴的沉积和漂移。本文主要研究了无人机下洗气流场和喷嘴位置对雾滴空间分布和速度分布的影响,这是影响喷雾特性的两个因素。为了研究上述特性,采用基于晶格玻尔兹曼方法(LBM)的计算流体力学方法,对大疆T30六旋翼植保无人机在不同旋翼转速(1000 ~ 1800 r/min)下的下洗气流场进行了仿真。利用粒子图像测速系统(PIV)记录不同转子转速(0 ~ 1800 r/min)和不同喷嘴位置(距离电机0、0.20 m、0.35 m、0.50 m)下洗气流场的喷雾场。仿真和实验结果表明,转子下洗气流场呈现“分散-收缩-再分散”的发展规律。在旋翼气流弥散初期,旋翼下洗气流场中存在明显的高涡度区和低涡度区。低涡度区主要集中在电机下方,高涡度区主要集中在转子中部。Y向气流速度在转子下方0.4 ~ 1.2 m处有波动。当转子气流发展到转子以下3.2 m时,Y方向气流速度略有下降。在距转子3.2 m以上,Y向气流速度开始急剧下降。因此,建议大疆T30植保无人机在进行田间喷洒作业时,飞行高度不要超过3.2 m。旋翼下洗气流场使旋翼系统启动时喷嘴雾化角减小,液滴浓度减小,喷雾场宽度减小,喷雾场涡流规模增大。而转子转速的增加则促进了上述趋势。当喷嘴安装在转子下方不同径向位置时,液滴的空间分布和速度分布完全不同。当喷嘴安装在电机正下方时,液滴的空间分布和速度分布相对对称。当喷嘴安装在距离电机0.20 m和0.35 m处时,液滴在较强转子涡的诱导下明显向右移动。这导致右半喷雾区液滴浓度较高。然而,当喷嘴安装在转子尖端时,液滴向左移动。对于四个喷嘴位置,当喷嘴安装在距离电机0或0.20 m处时,液滴的平均速度要高得多。而当喷嘴安装在另外两个位置时,液滴平均速度较慢。因此,建议将喷嘴安装在距离电机0或0.20 m处。研究结果可以加深对无人机下洗气流场分布特性及其对液滴空间分布和速度分布特性的影响的认识。同时,研究结果可为转子下方喷管位置的选择提供一定的理论指导。
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引用次数: 2
Evaluation of the nonmarket value of livestock and poultry feces returning to farmland utilization using CVM in Heilongjiang, China 基于CVM的黑龙江省畜禽粪便退耕还田利用非市场价值评价
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.7588
Jiajie Shang, Yongtao Xie, Lifeng Guo, Jinxia Fan, Hongxin Liu
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引用次数: 0
Investigation of distribution uniformity of distributor for biogas slurry application based on CFD analysis 基于CFD分析的沼液施浆器分布均匀性研究
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231601.7460
Jingjing Fu, Yongsheng Chen, Binxing Xu, Biao Ma, Pengjun Wang, A. Wu, Mingjiang Chen
{"title":"Investigation of distribution uniformity of distributor for biogas slurry application based on CFD analysis","authors":"Jingjing Fu, Yongsheng Chen, Binxing Xu, Biao Ma, Pengjun Wang, A. Wu, Mingjiang Chen","doi":"10.25165/j.ijabe.20231601.7460","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.7460","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86522500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Method for the automatic recognition of cropland headland images based on deep learning 基于深度学习的农田岬角图像自动识别方法
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.6195
Yujie Qiao, Hui Liu, Zhijun Meng, Jingping Chen, Luyao Ma
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引用次数: 1
Airflow distribution law of multi-branch pipe of pneumatic rice direct seeder based on dimensional analysis 基于量纲分析的水稻直播机多支管气流分布规律
IF 2.4 2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231601.7663
W. Qin, Zaimang Wang, Minghua Zhang, Siyu He, Xuguo Wang, Youcong Jiang, Zishun Huang, Ying Zang
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引用次数: 0
Automatic detection of sow estrus using a lightweight real-time detector and thermal images 使用轻型实时检测器和热图像自动检测母猪发情
2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231603.7711
Haibo Zheng, Hang Zhang, Shuang Song, Yue Wang, Tonghai Liu
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引用次数: 1
Effects of self-healing biomimetic subsoiler on tillage resistance, wear-corrosion performance and soil disturbance morphology under different soil types 自修复仿生深层土壤对不同土壤类型下土壤抗耕性能、耐磨性和扰动形态的影响
2区 农林科学 Q1 Agricultural and Biological Sciences Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231603.7876
Yueming Wang, Chenjie Lu, Jing Chen, Chenhuan Cui, Yijie Pan, Wilhelm Pfleging, Jiyu Sun
Subsoiling has been widely used all over the world as an important operation method of no-tillage farming. For energy-saving and life-extension, the tillage resistance and wear-corrosion of subsoilers have attracted wide attention. In this study, the tillage resistance, soil disturbance, wear and corrosion of subsoiler with S-T-SK-2# biomimetic structures (S means subsoiler; T means tine; SK means shank; 2#, h/s=0.57, h=5 mm and α=45°.) and self-healing coating under two seasons, two locations with different soil properties (black loam and clay soil) and subsoiling speeds (2 km/h and 3.6 km/h) were investigated. The soil moisture content and compactness affected the tillage resistance and wear-corrosion. The tillage resistance and degree of corrosion on all subsoilers were much larger in clay soil than that in black loam soil. Compared with S-T-SK-2#, the tillage reduction rate of C-S-T-SK-2# (S-T-SK-2# with self-healing coating) was up to 14.32% in clay soil under the speed of 2 km/h. The significance tests of regression equation results showed that subsoiler type and soil properties had a significant impact on soil disturbance coefficient, swelling of total soil layer, bulkiness of the plough pan. It is of a guiding significance for the analysis of soil disturbance. Synergism mechanism of subsoiler coupling with biomimetic structures and self-healing coating was analyzed in following. It depicted the guiding effect of biomimetic structure and the shield function of self-healing coating, resulting in anticorrosion and wear resistance of subsoiler. Keywords: soil types, tillage resistance, wear-corrosion, soil disturbance, self-healing DOI: 10.25165/j.ijabe.20231603.7876 Citation: Wang Y M, Lu C J, Chen J, Cui C H, Pan Y J, Pfleging W, et al. Effects of self-healing biomimetic subsoiler on tillage resistance, wear-corrosion performance and soil disturbance morphology under different soil types. Int J Agric & Biol Eng, 2023; 16(3): 7–14.
深埋作为一种重要的免耕耕作方式,在世界各国得到了广泛的应用。为了节能和延长使用寿命,深耕器的耐耕性和耐磨性引起了人们的广泛关注。在本研究中,S- t - sk -2#仿生结构的深耕器(S表示深耕器;T表示时间;SK是指柄;2#, h/s=0.57, h=5 mm, α=45°),在2个季节、2个土壤性质不同的地点(黑壤土和粘土)和2 km/h和3.6 km/h的沉土速度下,对自愈涂层进行了研究。土壤含水量和密实度影响土壤的耐耕性和耐磨性。土中土壤的抗耕性和腐蚀程度均大于黑壤土。与S-T-SK-2#相比,在2 km/h的速度下,C-S-T-SK-2#(带自愈涂层的S-T-SK-2#)在粘土中的减耕率可达14.32%。回归方程结果的显著性检验表明,土壤类型和土壤性质对土壤扰动系数、全土层膨胀、犁盘体积有显著影响。对土壤扰动分析具有一定的指导意义。分析了深层土壤与仿生结构和自愈涂层耦合的协同作用机理。描述了仿生结构的引导作用和自愈涂层的屏蔽作用,从而实现了土壤的防腐耐磨。关键词:土壤类型,抗耕性,磨损腐蚀,土壤扰动,自愈DOI: 10.25165/ j.j ijabe.20231603.7876引用本文:王永明,卢春江,陈健,崔春华,潘玉杰,Pfleging W,等。自修复仿生深层土壤对不同土壤类型下土壤抗耕性能、耐磨性和扰动形态的影响农业与生物工程学报,2023;16(3): 7 - 14。
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International Journal of Agricultural and Biological Engineering
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