International Journal of Agricultural and Biological Engineering最新文献_第5页

Effects of yellow and green light stress on emergence, feeding and mating of Anomala corpulenta Motschulsky and Holotrichia parallela Motschulsky (Coleoptera: Scarabaeidae) 黄光和绿光胁迫对褐斑金龟和褐斑金龟羽化、取食和交配的影响(鞘翅目:金龟科)

IF 2.4 2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231601.7639

Yue-li Jiang, Qiuying Huang, Guoshu Wei, Zhongjun Gong, Tong Li, J. Miao, Ruijie Lu, Shiqiong Mei, Xueqin Wang, Y. Duan, Yu-Qing Wu, Chuantao Lu

引用次数: 0

Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach 基于三维仿真方法的植保无人机飞行参数对液滴沉积速率的影响

IF 2.4 2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231601.6581

Lifeng Xu, Zhongzhuo Yang, Zusheng Huang, Weilong Ding, G. Buck-Sorlin

引用次数: 2

Review of deep learning-based weed identification in crop fields 基于深度学习的作物田间杂草识别研究进展

2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231604.8364

Wenze Hu, Samuel Oliver Wane, Junke Zhu, Dongsheng Li, Qing Zhang, Xiaoting Bie, Yubin Lan

{"title":"Review of deep learning-based weed identification in crop fields","authors":"Wenze Hu, Samuel Oliver Wane, Junke Zhu, Dongsheng Li, Qing Zhang, Xiaoting Bie, Yubin Lan","doi":"10.25165/j.ijabe.20231604.8364","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.8364","url":null,"abstract":"Automatic weed identification and detection are crucial for precision weeding operations. In recent years, deep learning (DL) has gained widespread attention for its potential in crop weed identification. This paper provides a review of the current research status and development trends of weed identification in crop fields based on DL. Through an analysis of relevant literature from both within and outside of China, the author summarizes the development history, research progress, and identification and detection methods of DL-based weed identification technology. Emphasis is placed on data sources and DL models applied to different technical tasks. Additionally, the paper discusses the challenges of time-consuming and laborious dataset preparation, poor generality, unbalanced data categories, and low accuracy of field identification in DL for weed identification. Corresponding solutions are proposed to provide a reference for future research directions in weed identification. Keywords: deep learning, weed detection, weed classiﬁcation, image segmentation, Convolutional Neural Network, image processing DOI: 10.25165/j.ijabe.20231604.8364 Citation: Hu W Z, Wane S O, Zhu J K, Li D S, Zhang Q, Bie X T, et al. Review of deep learning-based weed identification in crop fields. Int J Agric & Biol Eng, 2023; 16(4): 1-10.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135660077","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

sugarcane, single-bud sugarcane seed, disc-type seeding device, seeding uniformity 甘蔗，单芽甘蔗种子，圆盘式播种器，播种均匀

IF 2.4 2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.7067

Yulong Feng, Xuchao Yin, Hairong Jin, Wenyu Tong, Xiaofeng Ning

引用次数: 0

In-situ soil texture classification and physical clay content measurement based on multi-source information fusion 基于多源信息融合的原位土壤质地分类与物理粘土含量测量

IF 2.4 2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231601.6918

Chao Meng, Wei Yang, Xinjian Ren, D. Wang, Minzan Li

引用次数: 0

DR-XGBoost: An XGBoost model for field-road segmentation based on dual feature extraction and recursive feature elimination DR-XGBoost:一种基于双特征提取和递归特征消除的野外道路分割XGBoost模型

2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231603.8187

Yuzhen Xiao, Guozhao Mo, Xiya Xiong, Jiawen Pan, Bingbing Hu, Caicong Wu, Weixin Zhai

{"title":"DR-XGBoost: An XGBoost model for field-road segmentation based on dual feature extraction and recursive feature elimination","authors":"Yuzhen Xiao, Guozhao Mo, Xiya Xiong, Jiawen Pan, Bingbing Hu, Caicong Wu, Weixin Zhai","doi":"10.25165/j.ijabe.20231603.8187","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.8187","url":null,"abstract":"Field-road segmentation is one of the key tasks in the processing of the trajectory of agricultural machinery. To improve the accuracy of the field-road segmentation, this study proposed an XGBoost model based on dual feature extraction and recursive feature elimination called DR-XGBoost. DR-XGBoost takes only a small amount of agricultural machine trajectory features as input. Firstly, the model adopted the dual feature extraction method we designed to rapidly expand the number of features and then adequately extract local trajectory features by the time window and feature extraction operator. Secondly, the model applies the recursive feature elimination algorithm to eliminate redundant features from the perspective of the model segmentation effect and thus reduce the computational consumption of model training. Thirdly, it trains XGBoost to complete the trajectory segmentation. To evaluate the effectiveness of DR-XGBoost, we conducted a series of experiments on a real trajectory dataset of agricultural machines. The model achieves a 98.2% Macro-F1 score on the dataset, which is 10.9% higher than the previous state-of-art. The proposal of DR-XGBoost fills the knowledge gap of trajectory feature extraction for agricultural machinery and provides a reasonable and effective feature selection scheme for the field-road segmentation problem. Keywords: trajectory segmentation, feature extraction, recursive feature elimination, time window, XGBoost DOI: 10.25165/j.ijabe.20231603.8187 Citation: Xiao Y Z, Mo G Z, Xiong X Y, Pan J W, Hu B B, Wu C C, et al. DR-XGBoost: An XGBoost model for field-road segmentation based on dual feature extraction and recursive feature elimination. Int J Agric & Biol Eng, 2023; 2023; 16(3): 169–179.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135357560","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

Optimization of a three-row air-suction Brassica chinensis precision metering device based on CFD-DEM coupling simulation 基于CFD-DEM耦合仿真的三排空气吸式芸苔精密计量装置优化

2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231603.7812

Xinping Sun, Hua Li, Xindan Qi, Dinghao Feng, Jianqi Zhou, Yongjian Wang, Samuel Mbugua Nyambura, Xiaoyu Zhang, Xi Chen

{"title":"Optimization of a three-row air-suction Brassica chinensis precision metering device based on CFD-DEM coupling simulation","authors":"Xinping Sun, Hua Li, Xindan Qi, Dinghao Feng, Jianqi Zhou, Yongjian Wang, Samuel Mbugua Nyambura, Xiaoyu Zhang, Xi Chen","doi":"10.25165/j.ijabe.20231603.7812","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.7812","url":null,"abstract":"This study aimed to optimize a three-row air-suction Brassica chinensis precision metering device to improve the low seeding performance. ANSYS 17.0 Software was used to analyze the effect of different numbers of suction holes and different suction hole structures on the airflow field. It was found that a suction hole number of 60 was beneficial to the flow field stability and a conical hole structure was beneficial to the adsorption of seeds. Box-Behnken design experiments were carried out with negative pressure, rotational speed, and hole diameter as the experimental factors. The optimal parameter combination was achieved when the negative pressure was 3.96 kPa, the rotational speed of the seeding plate was 1.49 rad/s and the hole diameter was 1.10 mm. The qualification rate of inner, middle, and outer rings were 87.580%, 90.548%, and 90.117%, respectively, and the miss seeding rate of inner, middle, and outer rings were 10.915%, 7.139%, and 5.920%, respectively. Keywords: Brassica chinensis, metering device, airflow field, Box-Behnken design DOI: 10.25165/j.ijabe.20231603.7812 Citation: Sun X P, Li H, Qi X D, Feng D H, Zhou J Q, Wang Y J, et al. Optimization of a three-row air-suction Brassica chinensis precision metering device based on CFD-DEM coupling simulation. Int J Agric & Biol Eng, 2023; 16(3): 130–142.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135358842","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

Automatic lameness detection in dairy cows based on machine vision 基于机器视觉的奶牛跛行自动检测

2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231603.8097

Zongwei Jia, Xuhui Yang, Zhi Wang, Ruirui Yu, Ruibin Wang

引用次数: 0

Improvement of gelation properties of myofibrillar proteins from porcine longissimus dorsi muscle through microwave combined with air convection thawing treatment 微波联合空气对流解冻改善猪背最长肌纤维蛋白凝胶化性能

2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231603.7842

Fenxia Han, Mingming Zhu, Yi Xing, Hanjun Ma

引用次数: 0

Effect of temperature on the leaching of heavy metals from nickel mine tailings in the arctic area, Norway 温度对挪威北极镍矿尾矿中重金属浸出的影响

IF 2.4 2区农林科学

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI: 10.25165/j.ijabe.20231602.7216

S. Fu, Jin-Quan Lu, I. Walder, Daishe Wu

{"title":"Effect of temperature on the leaching of heavy metals from nickel mine tailings in the arctic area, Norway","authors":"S. Fu, Jin-Quan Lu, I. Walder, Daishe Wu","doi":"10.25165/j.ijabe.20231602.7216","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.7216","url":null,"abstract":": The leaching of heavy metals from tailings deposit due to the oxidation of sulphidic tailings and formation of acidic leachate is considered a high risk to the surrounding environment. Temperature plays an important role in the leaching of heavy metals from tailings in changing acid-based environment, especially in the Arctic area. To investigate how the temperature variation affected metal release from tailings in the Arctic area, a series of column leaching experiments was conducted under four temperature situations (5°C, 10°C, 14°C and 18°C). Physicochemical properties, Fe, Zn, Ni and Mn concentrations of leachates at each cycle were measured, and multivariate statistical analysis was applied to research the effect of temperature on heavy metals leaching from tailings in the Arctic area. The results showed that higher temperatures encouraged tailings to oxidation and sulfuration of and promoted heavy metal release from the tailings through precipitation and erosion. Ni, Zn and Mn have similar releasing resources from tailings and positive correlation in the leaching activity. Rising temperature accelerated Fe leaching; Fe leaching promoted leaching of the other metals, especially of Mn. Appropriately increase temperature will accelerate oxidization and sulfidization of the tailings, promote acid generation and increase TDS and, finally, promote the release of heavy metals. Climate change, with rising temperatures increasing the risk of heavy metals leaching from the tailings, should be given greater attention. Keeping tailings away from the appropriate temperature and in a higher alkalinity is a good method to control the leaching of heavy metals from tailings.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81630699","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: 1