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4DRoot:用于通过X射线计算机断层扫描进行时间三维扫描的根系表型分析软件。

4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography.

作者信息

Herrero-Huerta Monica, Raumonen Pasi, Gonzalez-Aguilera Diego

机构信息

Department of Cartographic and Land Engineering, Higher Polytechnic School of Ávila, Universidad de Salamanca, Ávila, Spain.

Department of Computing Sciences, Tampere University, Tampere, Finland.

出版信息

Front Plant Sci. 2022 Sep 23;13:986856. doi: 10.3389/fpls.2022.986856. eCollection 2022.

DOI:10.3389/fpls.2022.986856
PMID:36212319
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9539560/
Abstract

Currently, plant phenomics is considered the key to reducing the genotype-to-phenotype knowledge gap in plant breeding. In this context, breakthrough imaging technologies have demonstrated high accuracy and reliability. The X-ray computed tomography (CT) technology can noninvasively scan roots in 3D; however, it is urgently required to implement high-throughput phenotyping procedures and analyses to increase the amount of data to measure more complex root phenotypic traits. We have developed a spatial-temporal root architectural modeling software tool based on 4D data from temporal X-ray CT scans. Through a cylinder fitting, we automatically extract significant root architectural traits, distribution, and hierarchy. The open-source software tool is named 4DRoot and implemented in MATLAB. The source code is freely available at https://github.com/TIDOP-USAL/4DRoot. In this research, 3D root scans from the black walnut tree were analyzed, a punctual scan for the spatial study and a weekly time-slot series for the temporal one. 4DRoot provides breeders and root biologists an objective and useful tool to quantify carbon sequestration throw trait extraction. In addition, 4DRoot could help plant breeders to improve plants to meet the food, fuel, and fiber demands in the future, in order to increase crop yield while reducing farming inputs.

摘要

目前,植物表型组学被认为是缩小植物育种中基因型与表型知识差距的关键。在此背景下,突破性成像技术已展现出高准确性和可靠性。X射线计算机断层扫描(CT)技术能够对根系进行非侵入式三维扫描;然而,迫切需要实施高通量表型分析程序,以增加数据量,从而测量更复杂的根系表型性状。我们基于时间分辨X射线CT扫描的四维数据,开发了一种时空根系结构建模软件工具。通过圆柱拟合,我们自动提取重要的根系结构特征、分布和层级信息。该开源软件工具名为4DRoot,用MATLAB实现。源代码可在https://github.com/TIDOP-USAL/4DRoot免费获取。在本研究中,对黑核桃树的三维根系扫描进行了分析,其中包括用于空间研究的定点扫描和用于时间研究的每周时间序列扫描。4DRoot为育种者和根系生物学家提供了一个客观且有用的工具,通过性状提取来量化碳固存。此外,4DRoot有助于植物育种者改良植物,以满足未来对食物、燃料和纤维的需求,从而在减少农业投入的同时提高作物产量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/fa9e0029b31b/fpls-13-986856-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/ebd5328b071c/fpls-13-986856-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/cd6adeaff077/fpls-13-986856-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/9a07a54c6c7e/fpls-13-986856-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/93bb2519a807/fpls-13-986856-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/8dc91fd4b359/fpls-13-986856-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/fa9e0029b31b/fpls-13-986856-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/ebd5328b071c/fpls-13-986856-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/cd6adeaff077/fpls-13-986856-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/9a07a54c6c7e/fpls-13-986856-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/93bb2519a807/fpls-13-986856-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/8dc91fd4b359/fpls-13-986856-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a9f/9539560/fa9e0029b31b/fpls-13-986856-g006.jpg

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