estimated by taking the 2D projection of the 3D volume, then 185 calculated using a similar approach to that described in Grift et al., 2011. DensityS features are 186 computationally similar to plant compactness traits described in Yang et al., 2014. Scripts used 187 for image processing and feature extraction are available at https://github.com/Topp-Roots-Lab/ 188 189 Statistical Analysis 190 191 All downstream (i.e. post feature extraction) analysis was performed in the R statistical 192 computing environment. Initially, principal component analysis using all 71 3D roots traits was 193 used to identify large outliers, leading to the removal of 2 samples in the G2F 2017 data and 3 19
Open resource ↗Topp-Roots-Lab · pdf-layout-page:5 lines:1-56Unverified paper record
Complementary Phenotyping of Maize Root Architecture by Root Pulling Force and X-Ray Computed Tomography
bioRxiv · 4 Mar 2021 · 10.1101/2021.03.03.433776
Abstract
ABSTRACT The root system is critical for the survival of nearly all land plants and a key target for improving abiotic stress tolerance, nutrient accumulation, and yield in crop species. Although many methods of root phenotyping exist, within field studies one of the most popular methods is the extraction and measurement of the upper portion of the root system, known as the root crown, followed by trait quantification based on manual measurements or 2D imaging. However, 2D techniques are inherently limited by the information available from single points of view. Here, we used X-ray computed tomography to generate highly accurate 3D models of maize root crowns and created computational pipelines capable of measuring 71 features from each sample. This approach improves estimates of the genetic contribution to root system architecture, and is refined enough to detect various changes in global root system architecture over developmental time as well as more subtle changes in root distributions as a result of environmental differences. We demonstrate that root pulling force, a high-throughput method of root extraction that provides an estimate of root biomass, is associated with multiple 3D traits from our pipeline. Our combined methodology can therefore be used to calibrate and interpret root pulling force measurements across a range of experimental contexts, or scaled up as a stand-alone approach in large genetic studies of root system architecture.
Plant phenotyping relevance
トウモロコシ根系を対象に、X線CTによる3Dモデル化と計算パイプラインで71形質を抽出し、根引抜き力との較正・解釈まで行う、中心的な表現型計測手法研究である。
abstractHere, we used X-ray computed tomography to generate highly accurate 3D models of maize root crowns and created computational pipelines capable of measuring 71 features from each sample.
abstractOur combined methodology can therefore be used to calibrate and interpret root pulling force measurements across a range of experimental contexts, or scaled up as a stand-alone approach in large genetic studies of root system architecture.
Code and data availability
The paper states that the authors' scripts for X-ray CT image processing and root feature extraction (batch-segmentation, batch-skeleton) are publicly available in the Topp-Roots-Lab GitHub repository. Raw phenotype data is said to be in Supplemental File 1, but no public URL for it is provided in the supplied blocks.
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