首站-论文投稿智能助手
典型文献
Estimation of chlorophyll content in Brassica napus based on unmanned aerial vehicle images
文献摘要:
The chlorophyll content has a direct effect on photosynthesis of crops.In order to explore a quick and convenient method for estimating the chlorophyll content of Brassica napus and facilitate efficient crop monitoring,we measured the actual value of chlorophyll with a SPAD-502 chlorophyll detector,and collected aerial images of B.napus with an unmanned aerial vehicle(UAV)carrying a RGB camera in this study.The total number of 270 samples collected images were divided into regions according to the planting conditions of different B.napus varieties in the field.Then,according to the empirical formula,there were 36 colors'characteristic parameters calculated and combined.To estimate the chlorophyll content of rape,189 samples were included in the modeling set,while the other 81 samples were enrolled in the validation set for testing the accuracy of this model.After the combination of R(red),G(green)and B(blue)color channels,the results showed that the color characteristics B/(R+G),b,B/G,(G-B)/(G+B),g-b were highly connected with the measured value of chlorophyll SPAD,and the correlation coefficient between the combination based on B/(R+G)and SPAD value was 0.747.With R2=0.805,RMSE=3.343,and RE=6.84%,the regression model created using random forest had superior outcomes,ac-cording to the model comparison.This study offers a new method for quickly estimating the amount of chloro-phyll in rapeseed and a workable reference for crop monitoring using the UAV platform.
文献关键词:
作者姓名:
Yayi Huang;Qiming Ma;Xiaoming Wu;Hao Li;Kun Xu;Gaoxiang Ji;Fang Qian;Lixia Li;Qian Huang;Ying Long;Xiaojun Zhang;Biyun Chen;Changhua Liu
作者机构:
School of Mathematics and Computer Science,Wuhan Polytechnic University,Wuhan,430023,China;Oil Crops Research Institute,Chinese Academy of Agricultural Sciences,Key Laboratory of Oil Crop Biology and Genetic Improvement,Ministry of Agriculture and Rural Affairs,Wuhan,430062,China
引用格式:
[1]Yayi Huang;Qiming Ma;Xiaoming Wu;Hao Li;Kun Xu;Gaoxiang Ji;Fang Qian;Lixia Li;Qian Huang;Ying Long;Xiaojun Zhang;Biyun Chen;Changhua Liu-.Estimation of chlorophyll content in Brassica napus based on unmanned aerial vehicle images)[J].中国油料作物学报(英文),2022(03):149-155
A类:
G+B,phyll
B类:
Estimation,chlorophyll,content,Brassica,napus,unmanned,aerial,vehicle,images,has,direct,effect,photosynthesis,crops,In,order,explore,convenient,method,estimating,facilitate,monitoring,measured,actual,value,SPAD,detector,collected,UAV,carrying,RGB,camera,this,study,total,number,samples,were,divided,into,regions,according,planting,conditions,different,varieties,field,Then,empirical,formula,there,colors,parameters,calculated,combined,To,estimate,included,modeling,set,while,other,enrolled,validation,testing,accuracy,After,combination,green,blue,channels,results,showed,that,characteristics,R+G,highly,connected,correlation,coefficient,between,was,With,RMSE,RE,regression,created,using,random,forest,had,superior,outcomes,comparison,This,offers,new,quickly,amount,rapeseed,workable,reference,platform
AB值:
0.510283
相似文献
Detection of oil spill based on CBF-CNN using HY-1C CZI multispectral images
Kai Du;Yi Ma;Zongchen Jiang;Xiaoqing Lu;Junfang Yang-College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,China;First Institute of Oceanology,Ministry of Natural Resources,Qingdao 266061,China;Technology Innovation Center for Ocean Telemetry,Ministry of Natural Resources,Qingdao 266061,China;National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology,Xi'an 710072,China;School of Electronics and Information Engineering,Harbin Institute of Technology,Harbin 150001,China;National Satellite Ocean Application Service,Beijing 100081,China;College of Oceanography and Space Informatics,China University of Petroleum(East China),Qingdao 266580, China
Measuring loblolly pine crowns with drone imagery through deep learning
Xiongwei Lou;Yanxiao Huang;Luming Fang;Siqi Huang;Haili Gao;Laibang Yang;Yuhui Weng;I.-K.uai Hung-School of Information Engineering,Zhejiang A & F University,Lin'an 311300,Zhejiang,People's Republic of China;Key Laboratory of State Forestry and Grassland Administration On Forestry Sensing Technology and Intelligent Equipment,Zhejiang A & F University,Lin'an 311300,Zhejiang,People's Republic of China;Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province,Zhejiang A & F University,Lin'an 311300,Zhejiang,People's Republic of China;Jiyang College of Zhejiang A & F University,Zhuji 311800,Zhejiang,People's Republic of China;College of Forestry and Biotechnology,Zhejiang A & F University,Lin'an 311300,Zhejiang,People's Republic of China;College of Forestry and Agriculture,Stephen F.Austin State University,Nacogdoches,TX 75962,USA
Leaf pigment retrieval using the PROSAIL model:Influence of uncertainty in prior canopy-structure information
Jia Sun;Lunche Wang;Shuo Shi;Zhenhai Li;Jian Yang;Wei Gong;Shaoqiang Wang;Torbern Tagesson-Key Laboratory of Regional Ecology and Environmental Change,School of Geography and Information Engineering,China University of Geoscience,Wuhan 430079,Hubei,China;Department of Physical Geography and Ecosystem Science,Lund University,Lund 117 SE-22100,Sweden;State Key Laboratory of Information Engineering in Surveying,Mapping,and Remote Sensing,Wuhan University,Wuhan 430079,Hubei,China;Key Laboratory of Quantitative Remote Sensing in Ministry of Agriculture and Rural Affairs,Beijing Research Center for Information Technology in Agriculture,Beijing 100097,China;Department of Geosciences and Natural Resource Management,University of Copenhagen,Copenhagen 1172,Denmark
Estimation of transpiration coefficient and aboveground biomass in maize using time-series UAV multispectral imagery
Guomin Shao;Wenting Han;Huihui Zhang;Yi Wang;Liyuan Zhang;Yaxiao Niu;Yu Zhang;Pei Cao-College of Mechanical and Electronic Engineering,Northwest A&F University,Yangling 712100,Shaanxi,China;Key Laboratory of Agricultural Internet of Things,Ministry of Agriculture,Yangling 712100,Shaanxi,China;Institute of Water-Saving Agriculture in Arid Areas of China,Northwest A&F University,Yangling 712100,Shaanxi,China;Water Management and Systems Research Unit,USDA-ARS,2150 Centre Avenue,Bldg.D.,Fort Collins,CO 80526,USA;College of Information,Xi'an University of Finance and Economics,Xi'an 710100,Shaanxi,China;Institute of Soil and Water Conservation,Northwest A&F University,Yangling 712100,Shaanxi,China;University of Chinese Academy of Sciences,Beijing 100049,China
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。