Comparison of open-source three-dimensional reconstruction pipelines for maize-root phenotyping
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comparison_open‐source_three‐d ...
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School of Plant Sciences, University of ArizonaIssue Date
2023-05-09
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John Wiley and Sons IncCitation
Liu, S., Bonelli, W. P., Pietrzyk, P., & Bucksch, A. (2023). Comparison of open-source three-dimensional reconstruction pipelines for maize-root phenotyping. The Plant Phenome Journal, 6, e20068. https://doi.org/10.1002/ppj2.20068Journal
Plant Phenome JournalRights
© 2023 The Authors. The Plant Phenome Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy and Crop Science Society of America. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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. © 2023 The Authors. The Plant Phenome Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy and Crop Science Society of America.Note
Open access journalISSN
2578-2703Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1002/ppj2.20068
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Except where otherwise noted, this item's license is described as © 2023 The Authors. The Plant Phenome Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy and Crop Science Society of America. This is an open access article under the terms of the Creative Commons Attribution License.