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Title: Comparison of open‐source three‐dimensional reconstruction pipelines for maize‐root phenotyping

Journal Article · · Plant Phenome Journal
DOI: https://doi.org/10.1002/ppj2.20068 · OSTI ID:1973158
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]
  1. Department of Plant Biology University of Georgia Athens Georgia USA, School of Plant Sciences University of Arizona Tucson Arizona USA
  2. Institute of Bioinformatics University of Georgia Athens Georgia USA
  3. Department of Plant Biology University of Georgia Athens Georgia USA
  4. Department of Plant Biology University of Georgia Athens Georgia USA, Warnell School of Forestry and Natural Resources University of Georgia Athens Georgia USA, Institute of Bioinformatics University of Georgia Athens Georgia USA, School of Plant Sciences University of Arizona Tucson Arizona USA

Abstract Understanding three‐dimensional (3D) root traits is essential to improve water uptake, increase nitrogen capture, and raise carbon sequestration from the atmosphere. However, quantifying 3D root traits by reconstructing 3D root models for deeper field‐grown roots remains a challenge due to the unknown tradeoff between 3D root‐model quality and 3D root‐trait accuracy. Therefore, we performed two computational experiments. We first compared the 3D model quality generated by five state‐of‐the‐art open‐source 3D model reconstruction pipelines on 12 contrasting genotypes of field‐grown maize roots. These pipelines included COLMAP, COLMAP+PMVS (Patch‐based Multi‐View Stereo), VisualSFM, Meshroom, and OpenMVG+MVE (Multi‐View Environment). The COLMAP pipeline achieved the best performance regarding 3D model quality versus computational time and image number needed. In the second test, we compared the accuracy of 3D root‐trait measurement generated by the Digital Imaging of Root Traits 3D pipeline (DIRT/3D) using COLMAP‐based 3D reconstruction with our current DIRT/3D pipeline that uses a VisualSFM‐based 3D reconstruction on the same dataset of 12 genotypes, with 5–10 replicates per genotype. The results revealed that (1) the average number of images needed to build a denser 3D model was reduced from 3000 to 3600 (DIRT/3D [VisualSFM‐based 3D reconstruction]) to around 360 for computational test 1, and around 600 for computational test 2 (DIRT/3D [COLMAP‐based 3D reconstruction]); (2) denser 3D models helped improve the accuracy of the 3D root‐trait measurement; (3) reducing the number of images can help resolve data storage problems. The updated DIRT/3D (COLMAP‐based 3D reconstruction) pipeline enables quicker image collection without compromising the accuracy of 3D root‐trait measurements.

Sponsoring Organization:
USDOE
Grant/Contract Number:
NONE; AR0000821
OSTI ID:
1973158
Alternate ID(s):
OSTI ID: 1973519; OSTI ID: 1974814; OSTI ID: 1984641
Journal Information:
Plant Phenome Journal, Journal Name: Plant Phenome Journal Journal Issue: 1 Vol. 6; ISSN 2578-2703
Publisher:
Wiley Blackwell (John Wiley & Sons)Copyright Statement
Country of Publication:
United States
Language:
English

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