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A 3D Canopy Reconstruction and Phenotype Analysis Method for Wheat

  • Boxiang Xiao
  • Sheng WuEmail author
  • Xinyu Guo
  • Weiliang Wen
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 545)

Abstract

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.

Keywords

Wheat Canopy reconstruction 3D Phenotype analysis Light distribution 

Notes

Acknowledgment

This work is supported by National Natural Science Foundation of China (Grant No. 61300079); by Beijing Municipal Science and Technology Project (Grant No. D151100004215004); by Creative Team Project of Beijing Academy of Agriculture and Forestry Science (Grant No. JNKYT201604).

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Boxiang Xiao
    • 1
    • 2
    • 3
  • Sheng Wu
    • 1
    • 2
    • 3
  • Xinyu Guo
    • 1
    • 2
    • 3
  • Weiliang Wen
    • 1
    • 2
    • 3
  1. 1.Beijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry ScienceBeijingChina
  2. 2.National Engineering Research Center for Information Technology in AgricultureBeijingChina
  3. 3.Beijing Key Lab of Digital PlantBeijingChina

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