Research on High-Throughput Crop Root Phenotype 3D Reconstruction Using X-ray CT in 5G Era

被引:4
作者
Wang, Jinpeng [1 ,2 ]
Liu, Haotian [1 ]
Yao, Qingxue [1 ]
Gillbanks, Jeremy [2 ]
Zhao, Xin [1 ]
机构
[1] Dalian Polytech Univ, Sch Informat Sci & Engn, Dalian 116034, Peoples R China
[2] Univ Western Australia, Sch Elect Elect & Comp Engn, M350, Perth, WA 6009, Australia
基金
中国国家自然科学基金;
关键词
high-throughput; root phenotype; 3D reconstruction; X-ray CT technology; SYSTEM; MRI; ARCHITECTURE; BIOMASS; GROWTH; PLANTS;
D O I
10.3390/electronics12020276
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Currently, the three-dimensional detection of plant root structure is one of the core issues in studies on plant root phenotype. Manual measurement methods are not only cumbersome but also have poor reliability and damage the root. Among many solutions, X-ray computed tomography (X-ray CT) can help us observe the plant root structure in a three-dimensional and non-destructive form under the condition of underground soil in situ. Therefore, this paper proposes a high-throughput method and process for plant three-dimensional root phenotype and reconstruction based on X-ray CT technology. Firstly, this paper proposes a high-throughput transmission for the root phenotyping and utilizing the imaging technique to extract the root characteristics; then, the study adopts a moving cube algorithm to reconstruct the 3D (three-dimensional) root. Finally, this research simulates the proposed algorithm, and the simulation results show that the presented method in this paper works well.
引用
收藏
页数:19
相关论文
共 46 条
  • [1] Alenya G., 2011, 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), P3408, DOI 10.1109/ICRA.2011.5980092
  • [2] What Will 5G Be?
    Andrews, Jeffrey G.
    Buzzi, Stefano
    Choi, Wan
    Hanly, Stephen V.
    Lozano, Angel
    Soong, Anthony C. K.
    Zhang, Jianzhong Charlie
    [J]. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2014, 32 (06) : 1065 - 1082
  • [3] Arora A., 2014, J WHEAT RES, V6, P74
  • [4] Uncovering the hidden half of plants using new advances in root phenotyping
    Atkinson, Jonathan A.
    Pound, Michael P.
    Bennett, Malcolm J.
    Wells, Darren M.
    [J]. CURRENT OPINION IN BIOTECHNOLOGY, 2019, 55 : 1 - 8
  • [5] Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat
    Atkinson, Jonathan A.
    Wingen, Luzie U.
    Griffiths, Marcus
    Pound, Michael P.
    Gaju, Oorbessy
    Foulkes, M. John
    Le Gouis, Jacques
    Griffiths, Simon
    Bennett, Malcolm J.
    King, Julie
    Wells, Darren M.
    [J]. JOURNAL OF EXPERIMENTAL BOTANY, 2015, 66 (08) : 2283 - 2292
  • [6] Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor
    Azzari, George
    Goulden, Michael L.
    Rusu, Radu B.
    [J]. SENSORS, 2013, 13 (02): : 2384 - 2398
  • [7] Development of a controlled vocabulary and software application to analyze fruit shape variation in tomato and other plant species
    Brewer, MT
    Lang, LX
    Fujimura, K
    Dujmovic, N
    Gray, S
    van der Knaap, E
    [J]. PLANT PHYSIOLOGY, 2006, 141 (01) : 15 - 25
  • [8] On the use of depth camera for 3D phenotyping of entire plants
    Chene, Yann
    Rousseau, David
    Lucidarme, Philippe
    Bertheloot, Jessica
    Caffier, Valerie
    Morel, Philippe
    Belin, Etienne
    Chapeau-Blondeau, Francois
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2012, 82 : 122 - 127
  • [9] Colombo GA, 2014, AGRARIAN, V7, P60
  • [10] LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status
    Eitel, Jan U. H.
    Magney, Troy S.
    Vierling, Lee A.
    Brown, Tabitha T.
    Huggins, David R.
    [J]. FIELD CROPS RESEARCH, 2014, 159 : 21 - 32