Name: extracting metrics for three-dimensional root systems: volume and surface analysis from in-soil x-ray computed tomography data
Uploaded: 2016-04-26T15:00:00.000+00:00
Duration: 9 min 37 s
Description: Watch this Scientific Journal Video about Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data at JoVE.com

This work was performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory.

注意:X射线断层摄影扫描仪的操作需要两个一般辐射训练，和特定仪器的辐射安全训练。相关实验者的实验室所有相应的程序应遵循。 1.根成像注意:此步骤描述了在管状塑料盆原文土壤保持的草标本的摄像（塑料管，其直径为40毫米，210毫米的高度，以及约2mm壁厚）。 <ol><li>放在仪器的样品操纵器盆栽植物在期望目标倍率的距离。在一个2英寸直径的支架的植物中，样品到源的距离应为约3英寸（7厘米）。 </li><li>调整所述X射线扫描设置，以达到最佳的颜色（灰度级）的检测器图像的对比度。注意:这些设置中使用的仪器控制软件可用。 <ol><li>一套X射线电源设置; 85千伏和190μA在这次考试中使用PLE。 </li><li>设置曝光时间。这里，被用于更好信噪比1秒的相对长的曝光时间。 </li><li>集数每个投影预测和帧;每个投影4帧，共计3,142预测建议为良好的数据统计。 </li><li>使用运行通过选择"阴影校正"选项卡，并单击"创建"上面设置的测量条件阴影校正。 注意:当具有恒定集合X射线通量的照亮变化在成像装置的像素的响应的阴影校正补偿。这个过程需要空白图像（与光束路径移除样品）与X射线束接通，并且与梁关闭。这种校正被施加到收集到的所有图像。 </li><li>选择"最小化环假象"选项（也称为"穿梭模式"）;样品将在角的步骤，而在投影图像获取旋转。这导致的DAT一个采集以较慢的速度，但有助于消除环假象。 </li><li>通过点击采集标签下的"采集"按钮开始扫描（与上面列出的设置，图像采集将需要大约4小时）。 </li></ol></li></ol> 2.数据重构注意:本节介绍了从原始图像（从CT扫描X光片）三维数据的重建。 <ol><li>加载的原始数据到程序中。 </li><li>比较第一和最后一个图像，以确保样品不移动或扫描设置数据采集过程中没有改变（作为最后图象被检体的360°旋转后取它们应该是几乎相同）。 </li><li>通过选择"旋转中心"选项卡，并单击"开始"计算旋转（COR）的中心;使用选项"自动"COR寻找具有"高品质"的精度，而"双反"（上，下）片小号选举COR计算。 </li><li>选择样本量进行重构:选择"音量"选项卡，并编辑使用缩略图音量选择窗口。 </li><li>执行重建通过单击"开始"，以创建一个包含3D数据的卷文件。 </li></ol> 3.数据处理/分割注:这部分描述了要采取的步骤，以在程序RooTrak跟踪根准备用于进一步处理重建的数据，因为他们从任何周围材料分支通过土壤，并隔离根部产生的仅仅是二进制图像的堆叠根本身。 <ol><li>在ImageJ的数据量的处理准备一个RooTrak处理的图像堆栈: <ol><li>加载卷文件到ImageJ的。 </li><li>通过调整亮度和对比度设置优化根系与土壤之间的图像对比（点击图像/调整/亮度/对比度）。当的图像内感兴趣的区域是可见的和clearly区分，设置将被视为进行了优化。 </li><li>保存为JPEG，BMP，或PNG格式的图像堆栈。 </li></ol></li><li>处理RooTrak分割的根源: <ol><li>加载图像进栈RooTrak（进入"工具"选项卡，然后按"跟踪"）。 </li><li>内根设置种子点:点击内的各相关根段卷中的数据的顶视图切片可见的几个点。 </li><li>设置跟踪参数"平滑度"和"相似性"分别为0.3和0.8。 </li><li>运行跟踪功能。这会跟随根从顶部图像切片一路底部片。 </li><li>查看体数据后，选择根据该可用数据卷片的数目;在这种情况下，跟踪被停止了在200切片，相当于6.2毫米的深度，其中，根的边界变得不明确（被跟踪的根的图像开始混合到该土壤）。 注意:产生的图像堆栈将被自动保存到哪里输出目录已创建。 </li></ol></li></ol> 4.音量和表面分析注:此步骤描述了从RooTrak创建的图像堆栈等值面网格生成。 <ol><li>转换RooTrak图像堆栈成ImageJ的二进制图像格式。选择"进程"，然后是"二进制"，然后"让二进制"。 </li><li>使用开放源代码的ImageJ插件，BoneJ，创造了三角形网格;在ImageJ的选择"插件"，然后在"BoneJ"，然后"等值面"。 </li><li>设置"重采样"和"阈值"为6，120，分别为（默认设置）。勾选"显示面"，然后按"确定"按钮。 </li><li>在"3D查看器"，单击文件选项卡，然后在"导出面"，然后保存为"STL（二进制）"。 </li><li>打开imeshJ，选择STL文件，并在微米像素输入大小。点击"Calculate表面积"在2毫米收购总样本根表面积。同样，点击"计算容积"，取得3毫米的总样本根卷。 </li></ol>

<ol>
	<li>McKenzie, B. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Rhizosphere:+An+Ecological+Perspective.">The Rhizosphere: An Ecological Perspective.</a> Eur. J. Soil Sci. 59 (2), 416-417 (2008).</li><li>Farrar, J., Hawes, M., Jones, D., Lindow, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+roots+control+the+flux+of+carbon+to+the+rhizosphere.">How roots control the flux of carbon to the rhizosphere.</a> Ecology. 84 (4), 827-837 (2003).</li><li>Gregory, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Roots+rhizosphere+and+soil:+the+route+to+a+better+understanding+of+soil+science?.">Roots rhizosphere and soil: the route to a better understanding of soil science?.</a> Eur. J. Soil Sci. 57 (1), 2-12 (2006).</li><li>Philippot, L., Raaijmakers, J. M., Lemanceau, P., van der Putten, W. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Going+back+to+the+roots:+the+microbial+ecology+of+the+rhizosphere.">Going back to the roots: the microbial ecology of the rhizosphere.</a> Nat. Rev. Microbiol. 11 (11), 789-799 (2013).</li><li>Gregory, P. J., Hutchison, D. J., Read, D. B., Jenneson, P. M., Gilboy, W. B., Morton, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-invasive+imaging+of+roots+with+high+resolution+X-ray+micro-tomography.">Non-invasive imaging of roots with high resolution X-ray micro-tomography.</a> Plant and Soil. 255 (1), 351-359 (2003).</li><li>Mairhofer, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RooTrak:+Automated+Recovery+of+Three-Dimensional+Plant+Root+Architecture+in+Soil+from+X-Ray+Microcomputed+Tomography+Images+Using+Visual+Tracking.">RooTrak: Automated Recovery of Three-Dimensional Plant Root Architecture in Soil from X-Ray Microcomputed Tomography Images Using Visual Tracking.</a> Plant Physiol. 158 (2), 561-569 (2012).</li><li>Anderson, S. H., Hopmans, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Soil-Water-Root Processes: Advances in Tomography and Imaging. , (2013).</li><li>Mairhofer, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recovering+complete+plant+root+system+architectures+from+soil+via+X-ray+mu-Computed+Tomography.">Recovering complete plant root system architectures from soil via X-ray mu-Computed Tomography.</a> Plant Methods. 9, 8 (2013).</li><li>Lorensen, W. E., Cline, H. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Marching+cubes:+a+high+resolution+3D+surface+construction+algorithm.">Marching cubes: a high resolution 3D surface construction algorithm.</a> Comput. Graph. 21 (4), 163-169 (1987).</li><li>Lobet, G., Draye, X., Perilleux, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+online+database+for+plant+image+analysis+software+tools.">An online database for plant image analysis software tools.</a> Plant Methods. 9 (38), (2013).</li><li>Schmidt, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+iRoCS+Toolbox+-+3D+analysis+of+the+plant+root+apical+meristem+at+cellular+resolution.">The iRoCS Toolbox - 3D analysis of the plant root apical meristem at cellular resolution.</a> Plant J. 77 (5), 806-814 (2014).</li><li>Galkovskyi, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GiA+Roots:+software+for+the+high+throughput+analysis+of+plant+root+system+architecture.">GiA Roots: software for the high throughput analysis of plant root system architecture.</a> BMC Plant Biol. 12, 116 (2012).</li><li>Clark, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3-Dimensional+Root+Phenotyping+with+a+Novel+Imaging+and+Software+Platform.">3-Dimensional Root Phenotyping with a Novel Imaging and Software Platform.</a> Plant Physiol. 156, 455-465 (2011).</li><li>. RootSnap! Available from: <a target="_blank" href="https://www.cid-inc.com">https://www.cid-inc.com</a> (2013)</li><li>Arsenault, J. L., Pouleur, S., Messier, C., Guay, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=WinRHIZO&#8482;+a+root-measuring+system+with+a+unique+overlap+correction+method.">WinRHIZO&#8482; a root-measuring system with a unique overlap correction method.</a> HortSci. 30, 906-906 (1995).</li></ol>

We have nothing to disclose.

X射线计算机断层扫描和证明一些开放源代码程序的组合是一个强大的组合，以非侵入性的图像植物根系样品，段根数据，并从中提取三维数据的定量信息（表面积和体积）。我们的可视化和测量功能的能力总是由扫描分辨率，以及由RooTrak软件的限制的限制。然而，扫描分辨率足以捕捉大多数的本研究中的样品的特性，并RooTrak能够成功段根的显​​著一部分。在这项工作中所用的RooTrak的版本没?...

根，作为根际2-5的一部分，代表植物生物学的"看不见"的一部分，因为土壤使得难以图像根非侵入6,7，但是，研究土壤环境中的根生长和相互作用是理解临界根/植物的生长和养分循环，进而影响造林，粮食安全和气候。 X射线计算机断层扫描（XCT）已被证明是在其本地环境8植物根样本的非侵入性成像的有价值的工具。为了测量在不同条件下的根发育和尺寸的变化，并且可以比较从不同的数据集/标本数据，需要提取该断层摄影数据的定量信息。从周围的土壤的根数据的分割，即，基础图像的从一切它周围其他的隔离（包括，例如，一个相邻植物）是ACCU前一个关键步骤率大小分析可以做到的。然而，一个简单的阈值的方法是经常不可行的根数据。在土壤成像植物根部有关的挑战包括在根材料的X射线衰减特性的变化，和引起的水和有机物质的根和土壤之间的衰减值的重叠。这些问题已被寄望Mairhofer 等近期解决。在他们的视觉跟踪工具RooTrak 7,9。成功的分割后的下一步是根体积和表面积的准确测定。体积可以通过计数的体素的数量并作为7之前所示的体素"尺寸的立方相乘来估计。为了更准确地测定根表面积和体积的，所述分段根系的等值面可以由三角形网格使用被称为移动立方体10的算法表示。开源的ImageJ 11可以采用近似第基于对移动立方体算法E根卷。据我们所知，致力于在厘米范围计算为根基于标本断层体积/表面数据只有开放源代码软件数量有限，以上是目前可用12。我们看了13张开源软件侧重于根系生长，旨在细胞特征在单细胞分辨率，可以定量分析的体积。一些专门为整根系统14开源软件是极好的基础上近似，他们的造型实际上是管小口径管的根部系统。然而，随着二维图像一些工作，无法处理3D堆栈14。此外，当表面粗糙和不均匀的形状，如那些树根系统，进行了研究，管状形状近似可能是无效的。另一种方法15使用创新绕过第二维（2D）旋转图像序列Ë需要昂贵的CT扫描仪。它可以测量，记录和显示根系长度。我们从那些仅可以买到16-18测试的软件;一个不出现，以便能够处理三维图像栈16，第二是一个叶面积和根长度测量工具17，而第三个是基于颜色分析18。在此基础上的调查，我们建议，从3D断层扫描数据，而不管其形状接近根部的表面和体积的无成本的选择是理想的。 上可免费获得的RooTrak和ImageJ的基础上，我们已经开发出一种方案，名为imeshJ（参见补充编码文件），其处理来自分段根数据产生的等值面目（表面立体文件），并通过计算该根的体积和表面积做网格上的三角形索引数据简单的几何计算。在这里，我们报告说，综合运用XCT成像的方法，数据重建和可视化（软件CT临3D和VG工作室），从3D数据（开源软件ImageJ的和RooTrak）土壤样品的根分割，并且表面和体积信息提取从三角形网格（ImageJ的和计算机代码imeshJ）。

<table><tbody><tr><td>X-Tek/Metris XTH 320/225 kV&amp;nbsp;</td><td>Nikon Metrology</td><td></td><td>X-ray tomography scanner</td></tr><tr><td>Inspect X</td><td>Nikon Metrology</td><td></td><td>Instrument control software</td></tr><tr><td>CT Pro 3D</td><td>Nikon Metrology</td><td></td><td>Reconstruction software, version XT 2.2</td></tr><tr><td>VG Studio MAX</td><td>Visual Graphics GmbH</td><td></td><td>Visualization software for 3D volumes, version 2.1.5</td></tr><tr><td>ImageJ</td><td>Open-source</td><td></td><td>Image processing and analysis software, version 1.6</td></tr><tr><td>RooTrak</td><td>Open-source</td><td></td><td>Root segmentation software, version 0.3.1-b1 beta</td></tr><tr><td>imeshJ</td><td>EMSL</td><td></td><td>MATLAB script developed by the authors</td></tr><tr><td>Prairie dropseed grass sample</td><td></td><td></td><td>Sample obtained from ground in residential area</td></tr></tbody></table>

extracting metrics for three-dimensional root systems: volume and surface analysis from in-soil x-ray computed tomography data

植物根系在植物 - 土壤 - 微生物相互作用发生在根际的重要作用，以及与处理气候变化和作物管理具有重要意义。在他们自然环境对根的定量大小的信息是非常宝贵的学习根系生长，在涉及植物环境过程。 X射线计算机断层扫描（XCT）已被证明是用于原位根扫描和分析的有效工具。我们的目的是开发一种没有成本和高效率的工具，从三维（3D）断层扫描数据，而不管其形状接近根部的表面和体积。一个草原dropseed的根结构（ 鼠尾heterolepis）标本用XCT成像。根被重建，并且使用许可和开源软件的组合从数据萃取主根结构。等值面多边形网格然后为便于分析创建。我们已经开发Ť他独立的应用程序imeshJ，在MATLAB 1中产生，以计算从网格根体积和表面积。 imeshJ的输出是表面积（以mm 2）和体积（毫米3）。的过程中，利用从成像定量根分析的工具的独特的组合，进行说明。证明了XCT的结合，开源软件是一个强大的组合，以非侵入性的图像植物根系样品，段根数据，并从中提取三维数据的定量信息。处理三维数据的这种方法应适用于在有相似的X射线衰减的部件和困难之间具有分割产生连接的其他材料/样品的系统。

由两个试样茎天然草大草原dropseed（ 鼠尾heterolepis）和原土围绕它是从一个住宅区取和放置在如图1所示的小管形夹持器的该重构的数据的体素尺寸为约31微米×31微米×31微米。重构的卷文件被用于使用开源图像处理程序的ImageJ 1.6 11从一个选定的方向（顶视图）创建图像的堆叠。该卷的数据也亮堂这个计划，以增加根系与土壤值之间的​​对比。?...

Watch this Scientific Journal Video about Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data at JoVE.com

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

从在土X射线计算机断层扫描数据量和表面分析:提取指标三维根系

一种用于获得从土壤获得的X射线计算机断层扫描数据的视觉和定量根部结构信息的方法，提出。

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to ...

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Research

JoVE Journal

Environment

8.5K 次观看.  Environmental Molecular Sciences Laboratory. 一种用于获得从土壤获得的X射线计算机断层扫描数据的视觉和定量根部结构信息的方法，提出。 

视频: Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Better understanding of plant root dynamics is essential to improve resource use efficiency of agricultural systems and increase the resistance of crop cultivars against environmental stresses. An experimental protocol is presented for RGB and hyperspectral imaging of root systems. The approach uses rhizoboxes where plants grow in natural soil over a longer time to observe fully developed root systems. Experimental settings are exemplified for assessing rhizobox plants under water stress and studying the role of roots. An RGB imaging setup is described for cheap and quick quantification of root development over time. Hyperspectral imaging improves root segmentation from the soil background compared to RGB color based thresholding. The particular strength of hyperspectral imaging is the acquisition of chemometric information on the root-soil system for functional understanding. This is demonstrated with high resolution water content mapping. Spectral imaging however is more complex in image acquisition, processing and analysis compared to the RGB approach. A combination of both methods can optimize a comprehensive assessment of the root system. Application examples integrating root and aboveground traits are given for the context of plant phenotyping and plant physiological research. Further improvement of root imaging can be obtained by optimizing RGB image quality with better illumination using different light sources and by extension of image analysis methods to infer on root zone properties from spectral data.

An experimental protocol is presented for assessment of soil grown plant root systems with RGB and hyperspectral imaging. Combination of RGB image time series with chemometric information from hyperspectral scans optimizes insights into plant root dynamics.

RGB 和光谱根成像植物表型和生理研究: 实验装置和成像协议

Better understanding of plant root dynamics is essential to improve resource use efficiency of agricultural systems and increase the resistance of crop ...

科研

环境科学

Measuring Stolons and Rhizomes of Turfgrasses Using a Digital Image Analysis System

Length and diameter of stolons or rhizomes are usually measured using simple rulers and calipers. This procedure is slow and laborious, so it is often used on a limited number of stolons or rhizomes. For this reason, these traits are limited in their use for morphological characterization of plants. The use of digital image analysis software technology may overcome measurement errors due to human mistakes, which tend to increase as the number and size of samples also increase. The protocol can be used for any kind of crop but is particularly suitable for forage or grasses, where plants are small and numerous. Turf samples consist of aboveground biomass and an upper soil layer to the depth of maximum rhizome development, depending on the species of interest. In studies, samples are washed from the soil, and stolons/rhizomes are cleaned by hand before analysis by digital image analysis software. The samples are further dried in a laboratory heating oven to measure dry weight; therefore, for each sample, the resultant data are total length, total dry weight, and average diameter. Scanned images can be corrected before analysis by excluding visible extraneous parts, such as remaining roots or leaves not removed with the cleaning process. Indeed, these fragments normally have much smaller diameters than stolons or rhizomes, so they can be easily excluded from analysis by fixing the minimum diameter below which objects are not considered. Stolon or rhizome density per unit area can then be calculated based on sample size. The advantage of this method is quick and efficient measurement of the length and average diameter of large sample numbers of stolons or rhizomes.

A software-based image analysis system provides an alternative method to study the morphology of stoloniferous and rhizomatous species. This protocol permits measurement of the length and diameter of stolons and rhizomes and can be applied to samples with a large amount of biomass and to a wide variety of species.

利用数字图像分析系统测量草坪的茎和根状茎

Length and diameter of stolons or rhizomes are usually measured using simple rulers and calipers. This procedure is slow and laborious, so it is often ...

An Optimized Rhizobox Protocol to Visualize Root Growth and Responsiveness to Localized Nutrients

Roots are notoriously difficult to study. Soil is both a visual and mechanical barrier, making it difficult to track roots in situ without destructive harvest or expensive equipment. We present a customizable and affordable rhizobox method that allows the non-destructive visualization of root growth over time and is particularly well-suited to studying root plasticity in response to localized resource patches. The method was validated by assessing maize genotypic variation in plasticity responses to patches containing 15N-labeled legume residue. Methods are described to obtain representative developmental measurements over time, measure root length density in resource-containing and control patches, calculate root growth rates, and determine 15N recovery by plant roots and shoots. Advantages, caveats, and potential future applications of the method are also discussed. Although care must be taken to ensure that experimental conditions do not bias root growth data, the rhizobox protocol presented here yields reliable results if carried out with sufficient attention to detail.

Visualizing and measuring root growth in situ is extremely challenging. We present a customizable rhizobox method to track root development and proliferation over time in response to nutrient enrichment. This method is used to analyze maize genotypic differences in root plasticity in response to an organic nitrogen source.

一种优化的 Rhizobox 协议, 用于可视化根系生长和对局部营养素的响应

Roots are notoriously difficult to study. Soil is both a visual and mechanical barrier, making it difficult to track roots in situ without destructive ...

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

We describe a method for two-dimensional (2D) visualization and quantification of the distribution of labile (i.e., reversibly adsorbed) inorganic nutrient (e.g., P, Fe, Mn) and contaminant (e.g., As, Cd, Pb) solute species in the soil adjacent to plant roots (the &#8216;rhizosphere&#8217;) at sub-millimeter (~100 &#181;m) spatial resolution. The method combines sink-based solute sampling by the diffusive gradients in thin films (DGT) technique with spatially resolved chemical analysis by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The DGT technique is based on thin hydrogels with homogeneously distributed analyte-selective binding phases. The variety of available binding phases allows for the preparation of different DGT gel types following simple gel fabrication procedures. For DGT gel deployment in the rhizosphere, plants are grown in flat, transparent growth containers (rhizotrons), which enable minimal invasive access to a soil-grown root system. After a pre-growth period, DGT gels are applied to selected regions of interest for in situ solute sampling in the rhizosphere. Afterwards, DGT gels are retrieved and prepared for subsequent chemical analysis of the bound solutes using LA-ICP-MS line-scan imaging. Application of internal normalization using 13C and external calibration using matrix-matched gel standards further allows for the quantification of the 2D solute fluxes. This method is unique in its capability to generate quantitative, sub-mm scale 2D images of multi-element solute fluxes in soil-plant environments, exceeding the achievable spatial resolution of other methods for measuring solute gradients in the rhizosphere substantially. We present the application and evaluation of the method for imaging multiple cationic and anionic solute species in the rhizosphere of terrestrial plants and highlight the possibility of combining this method with complementary solute imaging techniques.

This protocol presents a workflow for sub-mm 2D visualization of multiple labile inorganic nutrient and contaminant solute species using diffusive gradients in thin films (DGT) combined with mass spectrometry imaging. Solute sampling and high-resolution chemical analysis are described in detail for quantitative mapping of solutes in the rhizosphere of terrestrial plants.

土壤中实验室、无机植物养分和污染物的二维可视化和量化

We describe a method for two-dimensional (2D) visualization and quantification of the distribution of labile (i.e., reversibly adsorbed) inorganic ...

Leveraging Micro-CT Scanning to Analyze Parasitic Plant-Host Interactions

Micro-CT scanning has become an established tool in investigating plant structure and function. Its non-destructive nature, combined with the possibility of three-dimensional visualization and virtual sectioning, has allowed novel and increasingly detailed analysis of complex plant organs. Interactions among plants, including between parasitic plants and their hosts, can also be explored. However, sample preparation before scanning becomes crucial due to the interaction between these plants, which often differ in tissue organization and composition. Furthermore, the broad diversity of parasitic flowering plants, ranging from highly reduced vegetative bodies to trees, herbs, and shrubs, must be considered during the sampling, treatment, and preparation of parasite-host material. Here two different approaches are described for introducing contrast solutions into the parasite and/or host plants, focusing on analyzing the haustorium. This organ promotes connection and communication between the two plants. Following a simple approach, details of haustorium tissue organization can be explored three-dimensionally, as shown here for&#160;euphytoid, vine, and mistletoe parasitic species. Selecting specific contrasting agents and application approaches also allow detailed observation of endoparasite spread within the host body and detection of direct vessel-to-vessel connection between parasite and host, as shown here for an obligate root parasite. Thus, the protocol discussed here can be applied to the broad diversity of parasitic flowering plants to advance the understanding of their development, structure, and functioning.

Micro-CT is a non-destructive tool that can analyze plant structures in three dimensions. The present protocol describes the sample preparation to leverage micro-CT to analyze parasitic plant structure and function. Different species are used to highlight the advantages of this method when coupled with specific preparations.

利用显微CT扫描分析寄生植物与宿主的相互作用

Micro-CT scanning has become an established tool in investigating plant structure and function. Its non-destructive nature, combined with the possibility ...

高通量树木年轮分析和密度估计

Tree Core Analysis with X-ray Computed Tomography

An X-ray computed tomography (CT) toolchain is presented to obtain tree-ring width (TRW), maximum latewood density (MXD), other density parameters, and quantitative wood anatomy (QWA) data without the need for labor-intensive surface treatment or any physical sample preparation. The focus here is on increment cores and scanning procedures at resolutions ranging from 60 &#181;m down to 4 &#181;m. Three scales are defined at which wood should be looked at: (i) inter-ring scale, (ii) ring scale, i.e., tree-ring analysis and densitometry scale, as well as (iii) anatomical scale, the latter approaching the conventional thin-section quality. Custom-designed sample holders for each of these scales enable high-throughput scanning of multiple increment cores. A series of software routines were specifically developed to efficiently treat three-dimensional X-ray CT images of the tree cores for TRW and densitometry. This work briefly explains the basic principles of CT, which are needed for a proper understanding of the protocol. The protocol is presented for some known species that are commonly used in dendrochronology. The combination of rough density estimates, TRW and MXD data, as well as quantitative anatomy data, allows us to broaden and deepen current analyses for climate reconstructions or tree response, as well as further develop the field of dendroecology/climatology and archeology.

作者聚焦：用于树芯分析的 X 射线 CT 工具链的进步

Here we show how to process tree cores with an X-ray computed tomography toolchain. Except for chemical extraction for some purposes, no further physical lab treatment is needed. The toolchain can be used for biomass estimations, for obtaining MXD/tree-ring width data as well as for obtaining quantitative wood anatomy data.

使用 X 射线计算机断层扫描进行树芯分析

An X-ray computed tomography (CT) toolchain is presented to obtain tree-ring width (TRW), maximum latewood density (MXD), other density parameters, and ...

Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography

The rapid development of X-ray imaging techniques with image processing and analysis skills has enabled the acquisition of CT images of granular soils with high-spatial resolutions. Based on such CT images, grain-scale mechanical behavior such as particle kinematics (i.e., particle translations and particle rotations), strain localization and inter-particle contact evolution of granular soils can be quantitatively investigated. However, this is inaccessible using conventional experimental methods. This study demonstrates the exploration of the grain-scale mechanical behavior of a granular soil sample under triaxial compression using synchrotron X-ray micro-tomography (&#956;CT). With this method, a specially fabricated miniature loading apparatus is used to apply confining and axial stresses to the sample during the triaxial test. The apparatus is fitted into a synchrotron X-ray tomography setup so that high-spatial resolution CT images of the sample can be collected at different loading stages of the test without any disturbance to the sample. With the capability of extracting information at the macro scale (e.g., sample boundary stresses and strains from the triaxial apparatus setup) and the grain scale (e.g., grain movements and contact interactions from the CT images), this procedure provides an effective methodology to investigate the multi-scale mechanics of granular soils.

The protocol describes procedures to acquire high-spatial resolution computed tomography (CT) images of a granular soil during triaxial compression, and to apply image processing techniques to these CT images to explore the grain-scale mechanical behavior of the soil under loading.

使用同步加速器 X 射线微断层扫描技术，在剪切下对颗粒土壤的故障和相关的颗粒级机械性能进行可视化

The rapid development of X-ray imaging techniques with image processing and analysis skills has enabled the acquisition of CT images of granular soils ...

工程学

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique with sub-micron resolution capability that is now being used to evaluate the structure and function of plant xylem network in three dimensions (3D) (e.g. Brodersen et al. 2010; 2011; 2012a,b). HRCT imaging is based on the same principles as medical CT systems, but a high intensity synchrotron x-ray source results in higher spatial resolution and decreased image acquisition time. Here, we demonstrate in detail how synchrotron-based HRCT (performed at the Advanced Light Source-LBNL Berkeley, CA, USA) in combination with Avizo software (VSG Inc., Burlington, MA, USA) is being used to explore plant xylem in excised tissue and living plants. This new imaging tool allows users to move beyond traditional static, 2D light or electron micrographs and study samples using virtual serial sections in any plane. An infinite number of slices in any orientation can be made on the same sample, a feature that is physically impossible using traditional microscopy methods.
Results demonstrate that HRCT can be applied to both herbaceous and woody plant species, and a range of plant organs (i.e. leaves, petioles, stems, trunks, roots). Figures presented here help demonstrate both a range of representative plant vascular anatomy and the type of detail extracted from HRCT datasets, including scans for coast redwood (Sequoia sempervirens), walnut (Juglans spp.), oak (Quercus spp.), and maple (Acer spp.) tree saplings to sunflowers (Helianthus annuus), grapevines (Vitis spp.), and ferns (Pteridium aquilinum and Woodwardia fimbriata). Excised and dried samples from woody species are easiest to scan and typically yield the best images. However, recent improvements (i.e. more rapid scans and sample stabilization) have made it possible to use this visualization technique on green tissues (e.g. petioles) and in living plants. On occasion some shrinkage of hydrated green plant tissues will cause images to blur and methods to avoid these issues are described. These recent advances with HRCT provide promising new insights into plant vascular function.

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique that can be used to study the structure and function of plant vasculature in 3D. We demonstrate how HRCT facilitates exploration of xylem networks across a wide range of plant tissues and species.

使用高解析度电脑断层可视化的三维结构和功能的植物血管

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique with sub-micron resolution capability that is now being ...

从在土X射线计算机断层扫描数据量和表面分析:提取指标三维根系

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此视频中的章节

RGB 和光谱根成像植物表型和生理研究: 实验装置和成像协议

利用数字图像分析系统测量草坪的茎和根状茎

一种优化的 Rhizobox 协议, 用于可视化根系生长和对局部营养素的响应

土壤中实验室、无机植物养分和污染物的二维可视化和量化

利用显微CT扫描分析寄生植物与宿主的相互作用

使用 X 射线计算机断层扫描进行树芯分析

使用 X 射线计算机断层扫描进行树芯分析

使用 X 射线计算机断层扫描进行树芯分析

使用同步加速器 X 射线微断层扫描技术，在剪切下对颗粒土壤的故障和相关的颗粒级机械性能进行可视化

使用高解析度电脑断层可视化的三维结构和功能的植物血管