Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery
文献类型: 外文期刊
作者: Chen, Bo 1 ; Huang, Guanmin 1 ; Lu, Xianju 1 ; Gu, Shenghao 1 ; Wen, Weiliang 1 ; Wang, Guangtao 2 ; Chang, Wushuai 2 ; Guo, Xinyu 1 ; Zhao, Chunjiang 1 ;
作者机构: 1.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Beijing, Peoples R China
2.China Natl Engn Res Ctr Informat Technol Agr, Beijing Key Lab Digital Plant, Beijing, Peoples R China
3.Jilin Agr Univ, Coll Resources & Environm, Changchun, Peoples R China
4.Nongxin Sci & Technol Beijing Co Ltd, Beijing, Peoples R China
关键词: canopy chlorophyll; SPAD values; maize; UAV multispectral; vertical distribution
期刊名称:FRONTIERS IN PLANT SCIENCE ( 影响因子:5.6; 五年影响因子:6.8 )
ISSN: 1664-462X
年卷期: 2023 年 14 卷
页码:
收录情况: SCI
摘要: Real-time monitoring of canopy chlorophyll content is significant in understanding crop growth status and guiding precision agricultural management. Remote sensing methods have demonstrated great potential in this regard. However, the spatiotemporal heterogeneity of chlorophyll content within crop canopies poses challenges to the accuracy and stability of remote sensing estimation models. Hence, this study aimed to develop a novel method for estimating canopy chlorophyll content (represented by SPAD values) in maize (Zea mays L.) canopies. Firstly, we investigated the spatiotemporal distribution patterns of maize canopy SPAD values under varying nitrogen application rates and different growth stages. The results revealed a non-uniform, "bell-shaped" curve distribution of maize canopy SPAD values in the vertical direction. Nitrogen application significantly influenced the distribution structure of SPAD values within the canopy. Secondly, we achieved satisfactory results by fitting the Lorentz peak distribution function to the SPAD values of different leaf positions in maize. The fitting performance, evaluated using R2 and RMSE, ranged from 0.69 to 0.98 and 0.45 to 3.59, respectively, for the year 2021, and from 0.69 to 0.77 and 2.38 to 6.51, respectively, for the year 2022.Finally, based on the correlation between canopy SPAD values and vegetation indices (VIs) at different growth stages, we identified the sensitive leaf positions for the selected CCCI (Canopy Chlorophyll Index) in each growth stage. The 6th (r = 0.662), 4th (r = 0.816), 12th (r = 0.722), and 12th (r = 0.874) leaf positions exhibited the highest correlations. Compared to the estimation model using canopy wide SPAD values, the model based on sensitive leaf positions showed improved accuracy, with increases of 34%, 3%, 20%, and 3% for each growth stage, respectively. In conclusion, the findings of this study contribute to the enhancement of chlorophyll content estimation models in crop canopies and provide valuable insights for the integration of crop growth models with remote sensing methods.
- 相关文献
作者其他论文 更多>>
-
3D Reconstruction of Wheat Plants by Integrating Point Cloud Data and Virtual Design Optimization
作者:Gu, Wenxuan;Guo, Xinyu;Wen, Weiliang;Wu, Sheng;Lu, Xianju;Guo, Xinyu;Wen, Weiliang;Wu, Sheng;Zheng, Chenxi;Lu, Xianju;Chang, Wushuai;Xiao, Pengliang;Guo, Xinyu
关键词:wheat; plant architecture; three-dimensional reconstruction; virtual design; plant phenotyping
-
Staggered-Phase Spray Control: A Method for Eliminating the Inhomogeneity of Deposition in Low-Frequency Pulse-Width Modulation (PWM) Variable Spray
作者:Zhang, Chunfeng;Zhao, Chunjiang;Zhang, Chunfeng;Zhai, Changyuan;Zhang, Meng;Zhang, Chi;Zou, Wei;Zhao, Chunjiang;Zhang, Chunfeng;Zou, Wei;Zhai, Changyuan;Zhang, Meng;Zhao, Chunjiang
关键词:precision spray; variable spray; PWM; deposition; duty cycle; frequency
-
Automatic acquisition, analysis and wilting measurement of cotton 3D phenotype based on point cloud
作者:Hao, Haoyuan;Zhuang, Lvhan;Xu, Longqin;Li, Hongxin;Liu, Shuangyin;Hao, Haoyuan;Wu, Sheng;Li, Yuankun;Wen, Weiliang;Zhuang, Lvhan;Guo, Xinyu;Hao, Haoyuan;Wu, Sheng;Li, Yuankun;Wen, Weiliang;Zhuang, Lvhan;Guo, Xinyu;Hao, Haoyuan;Zhuang, Lvhan;Xu, Longqin;Li, Hongxin;Liu, Shuangyin;Li, Yuankun;Zhang, Yongjiang
关键词:Phenotypic analysis; Deep learning; Leaf wilting; Multi-view
-
Maize emergence rate and leaf emergence speed estimation via image detection under field rail-based phenotyping platform
作者:Zhuang, Lvhan;Hao, Haoyuan;Li, Jinhui;Xu, Longqin;Liu, Shuangyin;Zhuang, Lvhan;Wang, Chuanyu;Hao, Haoyuan;Guo, Xinyu;Zhuang, Lvhan;Wang, Chuanyu;Hao, Haoyuan;Guo, Xinyu;Zhuang, Lvhan;Hao, Haoyuan;Li, Jinhui;Xu, Longqin;Liu, Shuangyin;Zhuang, Lvhan;Hao, Haoyuan;Li, Jinhui;Xu, Longqin;Liu, Shuangyin
关键词:Field rail-based phenotyping platform; Emergence rate; Leaf emergence speed; Faster R-CNN; Mask R-CNN
-
A novel electrochemical sensor for in situ and in vivo detection of sugars based on boronic acid-diol recognition
作者:Liu, Ke;Xu, Tongyu;Zhao, Chunjiang;Liu, Ke;Li, Aixue;Zhao, Chunjiang
关键词:Fructose; Glucose; Electrochemical biosensor; In situ; In vivo; Artificial neural network
-
Eliminating Primacy Bias in Online Reinforcement Learning by Self-Distillation
作者:Li, Jingchen;Wu, Huarui;Zhao, Chunjiang;Shi, Haobin;Hwang, Kao-Shing
关键词:Online reinforcement learning; overfitting; reinforcement learning
-
Using high-throughput phenotype platform MVS-Pheno to reconstruct the 3D morphological structure of wheat
作者:Li, Wenrui;Zhao, Chunjiang;Li, Wenrui;Wu, Sheng;Wen, Weiliang;Lu, Xianju;Liu, Haishen;Zhang, Minggang;Xiao, Pengliang;Guo, Xinyu;Zhao, Chunjiang;Li, Wenrui;Wu, Sheng;Wen, Weiliang;Lu, Xianju;Liu, Haishen;Zhang, Minggang;Xiao, Pengliang;Guo, Xinyu
关键词:3D reconstruction; plant morphology; point cloud segmentation; Wheat