Non-destructive 3D geometric modeling of maize root-stubble in-situ via X-ray computed tomography

Xu Zhao, Luyu Xing, Shifan Shen, Jiaming Liu, Daixing Zhang

Abstract


No-tillage seeding has become an important approach to improve crop productivity, which needs colters of high performance to cut the root-stubble-soil composite. However, the difficulty of maize root-stubbles three-dimensional (3D) modeling hinders finite element (FE) simulation to improve development efficiency of such colters because of maize root system complexity and opaque nature of the soil. Fortunately, the non-destructive 3D geometric model of the maize root-stubble in-situ can be established via X-ray computed tomography (CT) following by a systematic procedure. The whole procedure includes CT scanning of the maize root-stubble-soil composite sample, image reconstruction via filtered back-projection (FBP) with the Hanning filter, segmentation of root-stubble via a variational level set method, and post-processing via morphological operations. The 3D reconstruction model of the maize root-stubble in-situ presents a complete, complex and in-situ geometrical morphology, which cannot be realized via other methods, including the destructive modelling after washing via CT. This study is the first to build a 3D geometric model of a maize root-stubble in-situ via CT, which opens up new possibilities for simulation of root-stubble-soil cutting using FEM, and much other research related to plant root-stubbles.
Keywords: maize root-stubble, non-destructive modeling, X-ray computed tomography, variational level set method
DOI: 10.25165/j.ijabe.20201303.5268

Citation: Zhao X, Xing L Y, Shen S F, Liu J M, Zhang D X. Non-destructive 3D geometric modeling of maize root-stubble in-situ via X-ray computed tomography. Int J Agric & Biol Eng, 2020; 13(3): 174–179.

Keywords


maize root-stubble, non-destructive modeling, X-ray computed tomography, variational level set method

Full Text:

PDF

References


Zeng, Z W, Chen Y. The performance of a fluted coulter for vertical tillage as affected by working speed. Soil and Tillage Research, 2018; 175: 112–118.

Upadhyaya S K., Rosa U A., Wulfsohn D. Application of the finite element method in agricultural soil mechanics. Advances in Soil Dynamics, 2002; 2: 117–153.

Li M, Xu S, Yang Y W, Guo L, Tong J. A 3D simulation model of corn stubble cutting using finite element method. Soil and Tillage Research, 2017; 166: 43–51.

Mairhofer S, Sturrock C, Wells D M., Bennett M J, Mooney S J, Pridmore T P. On the evaluation of methods for the recovery of plant root systems from X-ray computed tomography images. Functional Plant Biology, 2015; 42(5): 460.

Mooney S J, Morris C, Berry P M. Visualization and quantification of the effects of cereal root lodging on three-dimensional soil macrostructure using X-ray computed tomography. Soil science, 2006; 171(9): 706–718.

Kaestner A, Schneebeli M, Graf F. Visualizing three-dimensional root networks using computed tomography. Geoderma, 2006; 136(1-2): 459–469.

Lontoc-Roy M, Dutilleul P, Prasher S O, Han L, Brouillet T, Smith D L. Advances in the acquisition and analysis of CT scan data to isolate a crop root system from the soil medium and quantify root system complexity in 3-D space. Geoderma, 2006; 137(1-2): 231–241.

Perret J S, Al-Belushi M E, Deadman M. Non-destructive visualization and quantification of roots using computed tomography. Soil Biology and Biochemistry, 2007; 39(2): 391–399.

Han L, Dutilleul P, Prasher S O, Beaulieu C, Smith D L. Assessment of density effects of the common scab-inducing pathogen on the seed and peripheral organs of potato during growth using computed tomography scanning data. Transactions of the ASABE, 2009; 52(1): 305–311.

Hargreaves C E, Gregory P J, Bengough A G. Measuring root traits in barley (Hordeum vulgare ssp. vulgare and ssp. spontaneum) seedlings using gel chambers, soil sacs and X-ray microtomography. Plant and Soil, 2009; 316(1-2): 285–297.

Mairhofer S, Zappala S, Tracy S, Sturrock C, Bennett M. J, Mooney S. J, et al. Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography. Plant Methods, 2013; 9(1): 8.

Koebernick N, Weller U, Huber K, Schlüter S, Vogel H J, Jahn R, et al. In situ visualization and quantification of three-dimensional root system architecture and growth using X-ray computed tomography. Vadose Zone Journal, 2014; 13(8).

Xu Z, Valdes C, Clarke J. Existing and potential statistical and computational approaches for the analysis of 3D CT images of plant roots. Agronomy, 2018; 8(5): 71.

Tabb A, Duncan K E, Topp C N. Segmenting root systems in X-ray computed tomography images using level sets. In: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe: IEEE. 2018. pp. 586–595.

Maenhout P, Sleutel S, Xu H, Van Hoorebeke L, Cnudde V, De Neve S. Semi-automated segmentation and visualization of complex undisturbed root systems with X-ray μCT. Soil and Tillage Research, 2019; 192: 59–65.

Zheng X, Valdes C, Clarke J. Existing and potential statistical and computational approaches for the analysis of 3D CT images of plant roots. Agronomy, 2018; 8(5): 71.

Kalender W A. Computed tomography: Fundamentals, system technology, image quality, applications. John Wiley & Sons, 2011. 372 p.

Li J Y, Jaszczak R J, Coleman R E. A filtered backprojection algorithm for axial head motion correction in fan-beam SPECT. Physics in Medicine and Biology, 1995; 40(12): 2053–2063.

Li C M, Kao C Y, Gore J C, Ding Z H. Minimization of region-scalable fitting energy for image segmentation. IEEE transactions on image processing, 2008; 17(10): 1940–1949.

Gonzalez R C, Woods R E, Eddins S L. Digital Image Processing Using MATLAB, 2nd Edition. Gatesmark Publishing, 2010; 827 p.




Copyright (c) 2020 International Journal of Agricultural and Biological Engineering

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

2023-2026 Copyright IJABE Editing and Publishing Office