Assessing the ratio of leaf carbon to nitrogen in winter wheat and spring barley based on hyperspectral data
文献类型: 外文期刊
作者: Xu, Xin-gang 1 ; Gu, Xiao-he 1 ; Song, Xiao-yu 1 ; Xu, Bo 1 ; Yu, Hai-yang 1 ; Yang, Gui-jun 1 ; Feng, Hai-kuan 1 ;
作者机构: 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, POB 2449-26, Beijing 100097, Peoples R China
关键词: leaf C/N;spectral index;winter wheat;spring barley;branch-and-bound method
期刊名称:REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XVIII
ISSN: 0277-786X
年卷期: 2016 年 9998 卷
页码:
收录情况: SCI
摘要: The metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production. The ratio of carbon to nitrogen (C/N) from crop leaves, defined as ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), is an important index that can be used to diagnose the balance between carbon and nitrogen, nutrient status, growth vigor and disease resistance in crop plants. Thus, it is very significant for effectively evaluating crop growth in field to monitor changes of leaf C/N quickly and accurately. In this study, some typical indices aimed at N estimation and chlorophyll evaluation were tested to assess leaf C/N in winter wheat and spring barley. The multi-temporal hyperspectral measurements from the flag-leaf, anthesis, filling, and milk-ripe stages were used to extract these selected spectral indices to estimate leaf C/N in wheat and barley. The analyses showed that some tested indices such as MTCI, MCARI/OSAVI2, and R-M had the better performance of assessing C/N for both of crops. Besides, a mathematic algorithm, Branch-and-Bound (BB) method was coupled with the spectral indices to assess leaf C/N in wheat and barley, and yielded the R-2 values of 0.795 for winter wheat, R-2 of 0.727 for spring barley, 0.788 for both crops combined. It demonstrates that using hyperspectral data has a good potential for remote assessment of leaf C/N in crops.
- 相关文献
作者其他论文 更多>>
-
A Two-Stage Leaf-Stem Separation Model for Maize With High Planting Density With Terrestrial, Backpack, and UAV-Based Laser Scanning
作者:Lei, Lei;Lei, Lei;Li, Zhenhong;Li, Zhenhong;Yang, Hao;Xu, Bo;Yang, Guijun;Hoey, Trevor B.;Wu, Jintao;Yang, Xiaodong;Feng, Haikuan;Yang, Guijun;Yang, Guijun
关键词:Vegetation mapping; Laser radar; Point cloud compression; Feature extraction; Agriculture; Data models; Data mining; Different cultivars; different growth stages; different planting densities; different platforms; light detection and ranging (LiDAR) data; simulated datasets; two-stage leaf-stem separation model
-
Leaf phenotypic difference analysis and variety recognition of tea cultivars based on multispectral imaging technology
作者:Cao, Qiong;Xu, Bo;Wang, Fan;Chen, Longyue;Jiang, Xiangtai;Zhao, Chunjiang;Yang, Guijun;Cao, Qiong;Zhao, Chunjiang;Jiang, Ping;Xu, Bo;Xu, Ze;Yang, Haibin;Wu, Quan
关键词:Tea leaf phenotype; Germplasm resources; Multispectral imaging
-
Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data
作者:Liu, Yang;Feng, Haikuan;Fan, Yiguang;Chen, Riqiang;Bian, Mingbo;Ma, Yanpeng;Li, Jingbo;Xu, Bo;Yang, Guijun;Liu, Yang;Liu, Yang;Feng, Haikuan;Yue, Jibo;Jin, Xiuliang
关键词:AGB; Hyperspectral features; Deep features; SPA; LSTM; PLSR
-
Real-time monitoring of maize phenology with the VI-RGS composite index using time-series UAV remote sensing images and meteorological data
作者:Feng, Ziheng;Ma, Xinming;Feng, Ziheng;Cheng, Zhida;Ren, Lipeng;Liu, Bowei;Zhang, Chengjian;Zhao, Dan;Sun, Heguang;Feng, Haikuan;Long, Huiling;Xu, Bo;Yang, Hao;Song, Xiaoyu;Yang, Guijun;Zhao, Chunjiang
关键词:UAV; Real-time; Composite index; Maize phenology; BBCH
-
Removal of canopy shadows improved retrieval accuracy of individual apple tree crowns LAI and chlorophyll content using UAV multispectral imagery and PROSAIL model
作者:Zhang, Chengjian;Chen, Zhibo;Chen, Riqiang;Qi, Ning;Zhang, Wenjie;Yang, Hao;Zhang, Chengjian;Yang, Guijun;Xu, Bo;Feng, Haikuan;Chen, Riqiang;Qi, Ning;Zhang, Wenjie;Zhao, Dan;Yang, Hao;Zhao, Dan;Cheng, Jinpeng
关键词:Leaf area index (LAI); Leaf chlorophyll content (LCC); Canopy chlorophyll content (CCC); Broad -band vegetation indexes (VIs); A hybrid inversion model
-
Fine-Scale Quantification of the Effect of Maize Tassel on Canopy Reflectance with 3D Radiative Transfer Modeling
作者:Jiang, Youyi;Cheng, Zhida;Zhang, Yuan;Cheng, Zhida;Yang, Guijun;Zhao, Dan;Zhang, Chengjian;Xu, Bo;Feng, Haikuan;Feng, Ziheng;Ren, Lipeng;Zhang, Yuan;Yang, Hao
关键词:maize tassel; spectrum; canopy; three-dimensional radiative transfer modeling; directional effects; influence mechanism
-
Orchard classification based on super-pixels and deep learning with sparse optical images
作者:Li, Jingbo;Yang, Guijun;Yang, Hao;Li, Jingbo;Xu, Weimeng;Feng, Haikuan;Xu, Bo;Chen, Riqiang;Zhang, Chengjian;Wang, Han;Yang, Guijun
关键词:Time series; Deep learning; Transformer; SAR data; Orchard



