A 3D Canopy Reconstruction and Phenotype Analysis Method for Wheat - Computer and Computing Technologies in Agriculture XI Access content directly
Conference Papers Year : 2019

A 3D Canopy Reconstruction and Phenotype Analysis Method for Wheat


A high precise and high realistic three-dimensional wheat canopy model is important in modern agriculture. In this paper, we proposed a 3D reconstruction and quantitative calculation for phenotype analysis method for wheat. First, we made use of a 3D digitizer to acquire spatial structure and distribution data of wheat canopy. After data processing, we constructed three-dimensional organ models including stalks, leaves and others, based on a surface modeling algorithm. Under this process, we constructed a 3D canopy model by frames of wheat colony. Furthermore, we made phenotype analyses on structure and organs distribution features including leaf length, azimuth and obliquity values. By use of constructed 3D canopy model, we used a light distribution computing algorithm to analyze the potential light interception, and we also calculated interception in different layers and different organs. The synchronous light intensity and leaf area index (LAI) measured by a PAR device were used to compare and examine the constructed canopy models. We also compute macroscopic canopy attributes including leaf area, leaf area index, projection area, shading area, and so on. Finally, parts of experimental results are shown, and the results show that our method is feasible and effective for wheat as well as other similar crops. At the end, the main contributions and limitations are also discussed, and some future works are addressed.
Fichier principal
Vignette du fichier
478291_1_En_23_Chapter.pdf (485.79 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02124256 , version 1 (09-05-2019)





Boxiang Xiao, Sheng Wu, Xinyu Guo, Weiliang Wen. A 3D Canopy Reconstruction and Phenotype Analysis Method for Wheat. 11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.244-252, ⟨10.1007/978-3-030-06137-1_23⟩. ⟨hal-02124256⟩
46 View
65 Download



Gmail Facebook X LinkedIn More