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MISIROOT: A ROBOTIC MINIMUM INVASION IN SITU IMAGING SYSTEM FOR PLANT ROOT PHENOTYPING

<p>Plant
root phenotyping technologies play an important role in breeding, plant
protection, and other plant science research projects. The root phenotyping
customers urgently need technologies that are low-cost, in situ,
non-destructive to the roots, and suitable for the natural soil environment.
Many recently developed root phenotyping methods such as minirhizotron, CT, and
MRI scanners have their unique advantages in observing plant roots, but they
also have disadvantages and cannot meet all the critical requirements
simultaneously. The study in this paper focuses on the development of a new
plant root phenotyping robot that is minimally invasive to plants and working
in situ inside natural soil, called “MISIRoot”. The MISIRoot system (patent
pending) mainly consists of an industrial-level robotic arm, a mini-size camera
with lighting set, a plant pot holding platform, and the image processing
software for root recognition and feature extraction. MISIRoot can take
high-resolution color images of the roots in soil with minimal disturbance to
the root and reconstruct the plant roots’ three-dimensional (3D) structure at
an accuracy of 0.1 mm. In a test assay, well-watered and drought-stressed
groups of corn plants were measured by MISIRoot at V3, V4, and V5 stages. The
system successfully acquired the RGB color images of the roots and extracted
the 3D points cloud data which showed the locations of the detected roots in
the soil. The plants measured by MISIRoot and plants not measured (controls)
were carefully compared with Purdue’s Lilly 13-4 Hyperspectral Imaging Facility
(reference). No significant differences were found between the two groups of
plants at different growth stages. Therefore, it was concluded that MISIRoot
measurements had no significant disturbance to the corn plant’s growth.</p>

  1. 10.25394/pgs.12194874.v1
Identiferoai:union.ndltd.org:purdue.edu/oai:figshare.com:article/12194874
Date28 April 2020
CreatorsZhihang Song (8764215)
Source SetsPurdue University
Detected LanguageEnglish
TypeText, Thesis
RightsCC BY 4.0
Relationhttps://figshare.com/articles/MISIROOT_A_ROBOTIC_MINIMUM_INVASION_IN_SITU_IMAGING_SYSTEM_FOR_PLANT_ROOT_PHENOTYPING/12194874

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