我们感谢三位匿名审稿人的反馈和建议。本研究由JVdB BOF专项研究基金（BOF Starting Grant BOF.STG.2018.0007.01），将UGCT作为专业中心（BOF.EXP.2017.0007）和作为核心设施（BOF.COR.2022.008），作者还感谢法兰德斯研究基金会（G019521N和G009720N）和UGent工业研究基金（IOF）通过赠款IOF对基础设施的财政支持。APP.2021.0005（项目FaCT F2021/IOF-Equip/021）。

高通量树木年轮分析和密度估计

作者没有要披露的利益冲突。

协议中的关键步骤 该协议中的关键步骤包括正确处理增量钻孔器以获得高质量的增量核心（步骤1.1.和参见39），以避免零碎。接下来，必须保持芯部未安装（但见26），以便插入样品架（图 5，见21），以及用于正确提取树脂50 和可能的未来分析。在扫描之前（步骤 2.2.2.），在扫描室中对样品进行调?...

木材密度是一个易于测量的变量1，它反映了木材2 的解剖学和化学性质。在对地上生物量进行生物量估算时，木材密度是一个重要的加权变量3,4,5，它与树木的尺寸相乘，并且是表示木材碳含量的因子。木材密度与木材的机械性能密切相关6 并反映了树木的生活史7.
细胞壁密度测量值约为 1500 kg/m³，被认为是相当恒定的8，但也应考虑环内细胞壁密度变化 8,9。木质细胞（通常是针叶树中的管胞、血管、薄壁组织和硬木中的纤维）以不同的方式定向/塑造，这些细胞的细胞壁厚度和管腔大小各不相同10。因此，树木之间、树内（轴向和横向）以及树木年轮内的短时间间隔内的木材密度各不相同11,12。在许多情况下，年轮尺度上的木材密度变化也划定了树木年轮边界13。根据研究目标（图1），木材密度和最终的组织分数被生成，在本文中，根据研究目标（图1），大致分为三类（即三种不同的分辨率尺度）。
环间刻度：通过测量木头片，获得该样品的单个值。这可以通过水浸或几何14 来完成。通过这种方式，可以获得一般的生物量或木材技术变量。为了包括髓到树皮的变化，这些木块可以进一步划分为块，这些块进行手动测量，以获得有关生活史策略的信息15.当切换到低分辨率 X 射线 CT 时，例如在医疗扫描仪17,18 中，可以在许多样本上以有效的方式获得中宽环上的 TRW 数据 18,19,20。这也是可用于评估温带和热带树木从髓到树皮的生物量的量表4,22，分辨率通常范围为50μm至200μm。
环形刻度：木材是过去环境条件的记录器。最广为人知的参数是树木年轮宽度 （TRW），但对于全球温度重建，最大晚材密度 （MXD） 记录被证明是温度22 的更好代表。MXD 是一个易于测量的变量23，是树木年轮最后一个细胞的细胞壁厚度和细胞大小的代理，并且位于树线和北方位置，与季节性气温呈正相关24：夏季越暖和，时间越长，细胞壁木质化就越多，从而增加了这些最后细胞的密度。传统的测量方法（如浸入和几何形状）在确定这种环级密度方面不太准确。之前的一项研究开发了一种工具链，用于在薄切样品上使用 X 射线胶片25。这在林业和后来的古气候学中引发了一场革命15,18，定义了最大晚材密度 （MXD），即通常位于环末端的峰值密度值，作为夏季温度的代理。基本原理是将样品（约 1.2 mm 至 7 mm13）锯切至完全平行于轴向，并将样品放在暴露于 X 射线源的敏感薄膜上。然后，这些射线照相胶片通过光源被读出，该光源检测强度并保存轮廓和年度树木年轮参数。然而，这些工具需要大量的样品制备和手动工作。最近，这已经以更标准化的方式或基于已安装的岩心26开发了用于X射线CT。这里的分辨率范围在 10 μm 到 20 μm 之间。TRW 也在这个尺度上测量，尤其是在处理较小的环时。
解剖尺度：在此尺度（分辨率< 4 μm）下，随着主要解剖特征的可视化并且可以测量其宽度和比例，平均密度水平变得不那么相关。通常，这是通过进行显微切片或高分辨率光学扫描或 μ-CT 扫描来完成的。当需要观察细胞壁的超微结构时，扫描电子显微镜是最常用的方法27。在解剖学尺度上，单个组织部分变得可见，因此可以从图像中得出生理参数。根据单个解剖参数和木材的细胞壁密度，可以得出解剖密度，以便与传统的木材密度估计器进行比较24。
由于改进了切片技术和图像软件 29,30，Dendro-Anatomy 30 已被开发出来，以更准确地记录木材，既能更接近估计针叶树中的 MXD，又能测量阔叶树的几个解剖变量。在这个尺度上，测量了实际的解剖参数并与环境参数相关31 。使用μCT，也可以获得该水平32,33。
由于木材本身具有吸湿性和各向异性，因此需要仔细定义木材密度，并需要指定测量条件，无论是烤箱干燥、调节（通常在 12% 的含水量下）还是绿色（在森林中砍伐）34。对于大样品和技术目的，木材密度定义为在给定条件下的重量除以其体积。然而，木材密度的值很大程度上取决于测量它的尺度，例如，从髓到树皮的木材密度可以翻倍，而在环尺度上（在针叶树中），早木到晚木的过渡也导致木材密度显着增加，在环边界处达到峰值。
在这里，提出了一种增量核心的 X 射线 CT 扫描协议，以便测量上述 3 个尺度的特征（图 1）。由于设置灵活，X 射线 CT 的最新发展可以覆盖这些量表中的大部分。研究目标将决定最终的扫描协议。
一个关键的限制因素（这与木材密度和一般木材的缩放性质有着内在的联系）是扫描所需的分辨率和时间。示例演示了如何：（i） 从刚果盆地获得用于估计 Terminalia superba 生物量的年轮间树间木材密度剖面，（ii） 根据 HECTOR 系统35 上的螺旋扫描从 Clanwilliam 雪松 （Widdringtonia cedarbergensis） 获取密度记录，以及 （iii） 在 Nanowood 系统上测量无柄橡树的容器参数。这两款扫描仪都是 UGent X 射线断层扫描中心（UGCT、
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65208/65208fig01.jpg"> 图 1：X 射线 CT 扫描的一般方法决策树。 这些行表示要采取的步骤，从研究目标开始，一直到最终的数据格式。白框是与此工具链相关的步骤。灰色框是可以使用其他软件或 R 包执行的步骤，例如用于树木年轮分析的 dplr47 和 Treeclim48 ，以及 ROXAS44 以及 ImageJ42 或其他（商业）应用程序，用于根据 CT 图像导出木材解剖参数。 <a href="https://www.jove.com/files/ftp_upload/65208/65208fig01large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
木材的X-CT研究 扫描仪的设置：标准 X 射线 CT 扫描仪由一个 X 射线管、一个 X 射线探测器、一个旋转台和一组电机组成，用于来回移动旋转台，在大多数情况下还包括探测器（图 2）。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65208/65208fig02.jpg"> 图2.HECTOR扫描系统。 系统35，显示源探测器距离（SDD）和源物体距离（SOD）。 <a href="https://www.jove.com/files/ftp_upload/65208/65208fig02large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
大多数基于实验室的系统都具有锥形束几何形状，这意味着产生的 X 射线以锥形束形状从管子的出射窗分布，这意味着通过改变物体与管之间的距离（SOD = 源-物体-距离）以及探测器与管之间的距离（SDD = 源-探测器-距离），可以控制放大倍率（参见关于分辨率的讨论）。由于 X 射线的穿透力，它们会穿过物体，衰减束的强度是 X 射线束的能量、物体的化学成分（存在的元素的原子序数）和材料密度的函数。鉴于木材具有恒定的能谱和恒定的材料成分，X射线束的衰减在很大程度上取决于材料的密度，这解释了其在密度测定中的用途。衰减（或传输）可以用 Beer-Lambert 定律表示：
<img alt="Equation 1" src="/files/ftp_upload/65208/65208eq01.jpg" style="margin: auto;">
当 I0 时，入射的 X 射线束呈指数增长，当穿过材料传播一段距离 d 时，它会衰减为透射的 X 射线束 Id。线性衰减系数μ取决于与物体材料的一系列相互作用。因此，投影是传输光束的记录。
实际上，将物体安装在旋转台上，选择适当的 SOD 和 SDD，选择一定的功率（与物体大小、密度和成分有关），并且物体旋转 360°，在旋转过程中进行多次投影。然后，这些投影用于重建物体的内部结构。有几种可用的重建算法，其中使用最多的仍然是基于几十年前开发的分析框架，依赖于Radon变换和傅里叶切片定理。有关更多详细信息，请向读者参考专业文献36。
分辨率、数据量和样本量的难题：分辨率是 X 射线 CT 扫描的关键。在具有逆几何形状或平行光束几何形状（如同步辐射光束线）的系统中，其他考虑因素也起作用。该协议仅讨论具有锥形束几何形状的标准基于实验室的 X 射线 CT 扫描。在这里，放大倍率、探测器像素大小和光斑大小的概念是必不可少的。放大倍率定义为 SDD/SOD 的比率。其次，探测器的像素大小显然也会影响分辨率：像素尺寸越小，分辨率越高，但在大多数情况下，视场（FoV）也与像素大小和探测器的大小直接相关（像素尺寸越小，相同像素数量的FoV越小）。此外，X射线束的光斑尺寸也很重要：光斑尺寸越大，分辨率越低，这意味着可以看到的细节较少。
重要的是要解决一个问题，即可以获得的分辨率高于根据上述限制可能获得的分辨率，因此最好使用术语体素大小（体素是体积像素）而不是分辨率。此外，还有其他因素在起作用，例如探测器的锐度，这进一步限制了扫描物体的真实分辨率。只有使用既定目标对系统进行真正的校准，才能提供真实的答案。
但是，在大多数情况下，可以扫描对象的体素大小主要受对象大小的限制。这意味着对象越大，体素大小就越小。如果物体在一定的体素大小下不适合探测器的FoV，则可以减小体素大小，例如，通过限制放大倍率。
在确定所需的体素大小时，扫描时间和数据量是重要的考虑因素。一般来说，体素越小意味着想要看到的细节越高，样本越小或一次可以扫描的样本越少，需要更多的时间，收集的数据量也就越大。想象一下以下理论示例：可以使用某个 X 射线 CT 系统一次扫描 10 cm x 10 cm x 10 cm 的样品，距离为 50 μm，并希望扫描 10 μm 的相同体积，适合 FoV 的体积仅为 2 cm x 2 cm x 2 cm， 假设这在物理上是可行的。这意味着需要 125 次扫描（5³ = 5 倍高分辨率，由于成像技术的体积特性，缩放到 3 的次方）才能覆盖整个体积，并且数据量也会同样增加。当然，这只是一个思想实验，人们需要考虑的不仅仅是分辨率。有关更多信息，请读者参阅扫描可能性的概述37。
用于扫描木制物体的仪器的灵活性：在过去的十年中，许多公司都提供了与 HECTOR35 组件相似的 X 射线 CT 系统。38 概述了几种 CT 系统，特别是对其时间分辨率的评估。
总而言之，X 射线 CT 系统的灵活性和用户友好性有了很大的提高。许多系统允许扫描各种物体，UGCT的系统也是如此。以下协议针对HECTOR系统进行了演示，该系统适用于树木年轮分析。但是，如果分辨率和数据格式允许，则该协议对任何其他可用系统都有效。
这些系统允许扫描各种物体。 图3给出了使用HECTOR系统扫描的不同木制物体的几张图片。正是这种灵活性构成了我们在 图 1 中展示的三种尺度，范围从粗略的分辨率到非常精细的分辨率。
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65208/65208fig03.jpg"> 图3.扫描设置示例。 （A） 一根日志，（B） 一把大提琴49，（C） 样品架（1 型），带有用于批量扫描的树形岩心，以及 （D） 样品架 2 型，带有用于螺旋扫描的增量岩心，安装在 HECTOR 的旋转台上。 <a href="https://www.jove.com/files/ftp_upload/65208/65208fig03large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>6 mm paper straws&#160;</td>
			<td>http://artstraws.com/education/product/artstraws-thick-asst-cols/</td>
			<td></td>
			<td>Coring</td>
		</tr>
		<tr>
			<td>Aluminium core holders</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>ASTM standard ASTM D 1107 &#8211; 96</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Cardboard postal tubes</td>
			<td>https://www.rajapack.co.uk/envelopes-mailing-bags/postal-tubes/1-5-2mm-brown-cardboard-postal-tubes_PDT05623.html</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Column drill</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Computer hardware for reconstruction and analysis</td>
			<td></td>
			<td></td>
			<td>X-ray CT scanning</td>
		</tr>
		<tr>
			<td>Cooling&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Drying oven</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Ethanol&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Flask for under soxhlet (2000 ml)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Floral foam</td>
			<td>https://www.oasisfloral.eu/</td>
			<td></td>
			<td>Sample holder type 1</td>
		</tr>
		<tr>
			<td>Glass beads to fill void volume of Soxhlet to save solvent</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Glue</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Hot water bath&#160;</td>
			<td>https://www.memmert.com/products/water-baths/water-bath/#!filters=%7B%7D</td>
			<td></td>
			<td>Soxhlet extraction</td>
		</tr>
		<tr>
			<td>Increment borer&#160;</td>
			<td>https://haglofsweden.com/project/increment-borers/</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Plastic cylinder&#160;</td>
			<td>Moonen et al. 2022&#160;</td>
			<td></td>
			<td>Sample holder type 2</td>
		</tr>
		<tr>
			<td>Plastic cylinders</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Reservoir</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Tailored soxhlet apparatus&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Toluene&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Water pump&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>X-ray CT scanner</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

tree core analysis with x-ray computed tomography

提出了一种 X 射线计算机断层扫描 （CT） 工具链，无需进行劳动密集型表面处理或任何物理样品制备，即可获得树木年轮宽度 （TRW）、最大晚材密度 （MXD）、其他密度参数和定量木材解剖学 （QWA） 数据。这里的重点是分辨率范围从 60 μm 到 4 μm 的增量岩心和扫描程序。定义了应观察木材的三个尺度：（i） 环间尺度，（ii） 环尺度，即树木年轮分析和密度测量尺度，以及 （iii） 解剖尺度，后者接近传统的薄片质量。为每种秤定制设计的样品架都可实现多个增量岩心的高通量扫描。专门开发了一系列软件程序，以有效地处理树芯的三维 X 射线 CT 图像，用于 TRW 和密度测定。这项工作简要解释了 CT 的基本原理，这些原理对于正确理解协议是必需的。该协议是针对树木年代学中常用的一些已知物种提出的。粗略密度估计、TRW 和 MXD 数据以及定量解剖学数据的结合，使我们能够扩大和深化当前对气候重建或树木响应的分析，并进一步发展树木生态学/气候学和考古学领域。

Wood density is an easy-to-measure variable1 that reflects both the anatomical and chemical properties of the wood2. In biomass estimations of aboveground biomass, wood density is an important weighing variable 3,4,5, that is multiplied with the dimensions of the tree and a factor representing the carbon content of the wood. Wood density is tightly linked to the mechanical properties of timber6 and reflects the life history of a tree7.
Cell wall density is measured as being approximately 1500 kg/m&#179; and is considered fairly constant8, however intra-ring cell wall density variations should be considered as well8,9.Woody cells (in general tracheids in conifers, vessels, parenchyma and fibers in hardwoods) are oriented/shaped in different ways and cell wall thickness and lumen size of these cells varies10. Therefore, wood density varies between trees, within a tree (axial and transversal) and within short intervals within a tree ring11,12. In many cases the wood density variation at the ring scale also delimits the tree ring boundary13. Wood density and ultimately tissue fractions are generated and in this paper are broadly put into three categories (i.e., three different resolution scales), depending on the study goal (Figure 1) as described below.
Inter-ring scale: By measuring pieces of wood, a single value is obtained for that sample. This can be done through water immersion or geometrically14. This way, general biomass or wood technological variables can be obtained. To include pith-to-bark variation, these pieces of wood can be further divided into blocks that are measured manually to obtain information on the life history strategy15. When switching to low-resolution X-ray CT such as in medical scanners17,18, TRW data on medium-to-wide rings can be made in an efficient way on many samples18,19,20. This is also the scale that can be used to assess biomass from pith-to-bark from both temperate and tropical trees4,22, typically ranging in resolutions from 50 &#181;m to 200 &#181;m.
Ring scale: Wood is a recorder of past environmental conditions. The best known parameter is tree-ring width (TRW), but for global temperature reconstructions, maximum latewood density (MXD) records are proven to be a better proxy for temperature22. MXD is an easy-to-measure variable23, and a proxy for cell wall thickness and cell size on the last cells of a tree ring, and are at tree line and boreal sites positively linked to seasonal air temperature24: the warmer and longer the summers, more cell wall lignification occurs which thus increases the density of these last cells. Traditional measurements such as immersion and geometry are less accurate to determine this ring-level density. A previous work developed a toolchain for using X-ray film on thin-cut samples25. This sparked a revolution in both forestry and later paleoclimatology15,18, defining maximum latewood density (MXD), i.e., the peak density value often at the end of a ring, as a proxy for summer temperature. The basic principle is that the samples are sawn (approximately 1.2 mm to 7 mm13) to be perfectly parallel to the axial direction, and the sample is put on a sensitive film exposed to an X-ray source. Then these radiography films are read out through a light source that detects the intensity and saves the profiles and the annual tree ring parameters. These tools, however, require a significant amount of sample preparation and manual work. Recently this has been developed for X-ray CT in a more standardized way or based on mounted cores26. Resolution here ranges between 10 &#181;m and 20 &#181;m. TRW is measured on this scale as well, especially when dealing with smaller rings.
Anatomical scale: At this scale (resolution &#60; 4 &#181;m), the average density levels become less relevant as the main anatomical features are visualized and their width and proportions can be measured. Typically, this is done through making microsections or high-resolution optical scans or &#181;-CT scans. When the ultrastructure of the cell walls needs to be visualized, scanning electron microscopy is the most commonly used method27. At the anatomical scale, the individual tissue fractions become visible so that physiological parameters can be derived from the images. Based on the individual anatomical parameters and the cell wall density of wood, anatomical density can be derived for comparison with conventional estimators of wood density24.
Due to improved sectioning techniques and image software29,30, dendro-anatomy30 has been developed to have a more accurate record of the wood, both to have a closer estimate of the MXD in conifers and to measure several anatomical variables from broadleaf trees. On this scale, actual anatomical parameters are measured and related to environmental parameters31 . With &#181;CT this level can be obtained as well32,33.
As wood is inherently hygroscopic and anisotropic, wood density needs to be carefully defined and the measurement conditions need to be specified, either as oven-dry, conditioned (typically at 12% moisture content) or green (as felled in the forest)34. For large samples and technical purposes, wood density is defined as the weight divided by its volume at given conditions. However, the value of wood density is strongly dependent on the scale at which it is measured, for instance from pith-to-bark wood density can double, and on a ring scale (in conifers) the transition of earlywood to latewood results in a significant rise in wood density as well, with a peak at the ring boundary.
Here, an X-ray CT scanning protocol of increment cores is presented in order to measure features at the aforenoted 3 scales (Figure 1). Recent developments in X-ray CT can cover most of these scales, due to a flexible set-up. The research goals will determine the eventual protocol for scanning.
A crucial limiting factor (which is inherently connected to the scaled nature of wood density and wood in general) is the resolution and time necessary for scanning. Examples demonstrate how to: (i) obtain inter-ring tree scale wood density profiles for biomass estimations in Terminalia superba from the Congo Basin, (ii) obtain density records from Clanwilliam cedar (Widdringtonia cedarbergensis) based on helical scanning on a HECTOR system35, and (iii) measure vessel parameters on sessile oak, on the Nanowood system.&#160;Both scanners are part of the suite of scanners at the UGent Center for X-ray Tomography (UGCT,
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65208/65208fig01.jpg" /> 
Figure 1: General methodological decision tree for X-ray CT scanning. The rows indicate the steps to take, starting from the research goal all the way to the final data format. White boxes are the steps that are relevant for this toolchain. Greyed-out boxes are steps that can be performed with other software or R packages, such as dplr47 and Treeclim48 for tree-ring analysis, and ROXAS44 as well as ImageJ42 or other (commercial) applications for deriving wood anatomical parameters based on the CT images. <a href="https://www.jove.com/files/ftp_upload/65208/65208fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
X-CT research on wood 
Set-up of a scanner: A standard X-ray CT scanner consists of an X-ray tube, an X-ray detector, a rotation stage, and a set of motors to move the rotation stage, and in most cases also the detector, back and forth (Figure 2).
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65208/65208fig02.jpg" /> 
Figure 2. The HECTOR scanning system. The system35, showing the source detector distance (SDD) and the source object distance (SOD). <a href="https://www.jove.com/files/ftp_upload/65208/65208fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Most lab-based systems have a cone-beam geometry, which means that the produced X-rays are distributed from the tube&#39;s exit window in a cone-beam shape, implying that by changing the distance between the object and the tube (SOD = Source-Object-Distance) and the detector and the tube (SDD = Source-Detector-Distance), the magnification is controlled (see the discussion on resolution). Due to the penetrating power of X-rays, they pass through the object, and the intensity of the attenuation beam is a function of the energy of the X-ray beam, the chemical composition of the object (the atomic number of the elements present) and the density of the material. Given a constant energy spectrum&#160;and a constant material composition of wood, the attenuation of the X-ray beam is highly dependent on the density of the material, which explains its use for densitometry. The attenuation (or transmission) can be expressed by the Beer-Lambert law:
<img alt="Equation 1" src="/files/ftp_upload/65208/65208eq01.jpg" style="margin: auto;" />
with I0 the incoming X-ray beam exponentially which decays to a transmitted X-ray beam Id when propagating through the material over a distance d. The linear attenuation coefficient &#181; depends on a series of interactions with the material of the object. The projections are thus recordings of the transmitted beam.
Practically, the object is mounted on the rotation stage, a proper SOD and SDD are selected, a certain power is selected as well (related to object size, density, and composition) and the object is rotated 360&#176; and during that rotation multiple projections are taken. These projections are then used to reconstruct the interior structure of the object. There are several reconstruction algorithms available, of which the most used ones are still based on the analytical framework developed decades ago, relying on the Radon transformation and the Fourier slice theorem. For more details, the reader is referred to specialized literature36.
Conundrum of resolution, data volume and sample size: Resolution is key in X-ray CT scanning. In systems with inverse geometry, or parallel beam geometry such as synchrotron beamlines, other considerations play a role. This protocol only discusses standard lab-based X-ray CT scanning with cone-beam geometry. Here, the concept of magnification, detector pixel size and spot size are essential. Magnification is defined as the ratio of SDD/SOD. Next, the pixel size of the detector obviously also impacts the resolution: the smaller the pixel size, the higher the resolution, but in most cases the field of view (FoV) is also directly related to pixel size and size of the detector (smaller pixel size, smaller FoV for the same number of pixels). Further, the spot size of the X-ray beam is also important: the larger the spot size, the lower the resolution, which means that less details can be seen.
It is important to address that one could obtain a resolution that is higher than what is possible according to the abovementioned limits, therefore it is better to use the term voxel size (a voxel is a volume pixel) instead of resolution. Moreover, there are other factors at play, such as detector sharpness, which further limit the true resolution at which an object is scanned. Only a true calibration of the system, using established targets, supplies the truthful answer.
In most cases, however, the voxel size at which an object can be scanned is mostly limited by the size of the object. This means that the larger the object, the lower the voxel size will be. If the object does not fit within the FoV of the detector for a certain voxel size, then the voxel size can be reduced, e.g., by limiting the magnification.
Scan time and data volume are important to consider when deciding the desired voxel size. In general, the smaller the voxel size means the higher the detail one wants to see, the smaller the sample or the fewer samples that can be scanned at once, more time is required and larger the data volumes will be collected. Imagine the following theoretical example: one can scan a sample measuring 10 cm x 10 cm x 10 cm at 50 &#181;m at once with a certain X-ray CT system and would like to scan that same volume at 10 &#181;m, the volume that fits within the FoV would only be 2 cm x 2 cm x 2 cm, assuming that this is physically possible. This means that 125 scans are needed (5&#179; = 5 times higher resolution, scales to the power of 3 due to the volumetric nature of the imaging technique) to cover the entire volume, and that the data volume would increase likewise. Of course, this is only a thought experiment, and one needs to consider much more than only resolution. For more information, the reader is referred to an overview of the scanning possibilities37.
Flexibility of instruments for scanning of wooden objects: In the last decade, many companies have delivered X-ray CT systems with a similar assembly as HECTOR35. An overview of several CT systems, especially assessed for their temporal resolution, is given in38.
In all, the flexibility and user-friendliness of X-ray CT systems has improved considerably. Many systems allow scanning of a diverse range of objects, which is also the case with the systems at UGCT. The protocol below is demonstrated for the HECTOR system, which is suitable for tree-ring analysis. The protocol however is valid for any other available system if resolution and data format allows for it.
These systems allow the scanning of a variety of objects. A few pictures of different wooden objects scanned with the HECTOR system are given in Figure 3. It is this flexibility that comprises the three scales we present in Figure 1, ranging from a coarse resolution to a very fine resolution.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65208/65208fig03.jpg" /> 
Figure 3.&#160;Scanning set-up examples. (A) A log, (B) a cello49, (C) sample holders (type 1) with tree cores for batch scanning and (D) sample holder type 2 with increment cores for helical scanning mounted on the rotation stage of HECTOR. <a href="https://www.jove.com/files/ftp_upload/65208/65208fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

作者聚焦：用于树芯分析的 X 射线 CT 工具链的进步

使用 X 射线计算机断层扫描进行树芯分析

The scope of my research is to study wood growth and its response to climate. The questions I'm trying to answer is, how can we reconstruct the climate of the past and what is the tree response to current climate change? So the current experimental challenges that we face are among others, the large data volumes that we obtain with x-ray CT scanning.So we need to find a proper balance between the number of samples that we want to scan and the required resolution. The X-ray CT techniques has allowed us to scan three core at an unprecedented rate. We have density profiles both from tropical and temperate regions.So the main advantages that we have with our technique is that we can do a lot of high throughput scanning and analysis, but also that all the indications and manipulations that we do are traceable along the entire tool chain, including the tree ring indications. This tool will allow us to update current to maximum later density chronologies, and also measure wood properties on tree course from all over the world, especially in regions where there's little data available.

如果目标是许多样品的生物量估计或树木生长增量，即环间尺度（图1），则使用样品架1（图5）扫描样品以获得密度分布（参见步骤5.4.3）和树木生长的估计，例如，对于具有大TRW的快速生长的树木，这允许更粗糙的分辨率。 图 12 显示了来自刚果盆地的 T. superba 的髓到树皮和轴向密度趋势的示例。这些图表基于在茎的不同...

Watch this Scientific Journal Video about Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis at JoVE.com

在这里，我们展示了如何使用 X 射线计算机断层扫描工具链处理树芯。除了用于某些目的的化学提取外，不需要进一步的物理实验室处理。该工具链可用于生物量估计、获取 MXD/树木年轮宽度数据以及获取定量木材解剖数据。

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

我的研究范围是研究木材生长及其对气候的反应。我想回答的问题是，我们如何重建过去的气候，树木对当前气候变化的反应是什么？因此，我们目前面临的实验挑战之一是我们通过X射线CT扫描获得的大量数据。因此，我们需要在想要扫描的样本数量和所需的分辨率之间找到适当的平衡。X 射线 CT 技术使我们能够以前所未有的速度扫描三个核心。我们有来自热带和温带地区的密度分布。因此，我们技术的主要优势是可以进行大量高吞吐量的扫描和分析，而且我们所做的所有指示和操作都可以在整个工具链上进行追踪，包括树木年轮指示。该工具将使我们能够将当前密度更新到最大以后的密度年表，还可以测量来自世界各地的树木路线上的木材特性，尤其是在可用数据很少的地区。

tree-core-analysis-with-x-ray-computed-tomography

Research

JoVE Journal

Environment

Tree Core Analysis with X-ray Computed Tomography

727 次观看.  University of Liège. 我的研究范围是研究木材生长及其对气候的反应。我想回答的问题是，我们如何重建过去的气候，树木对当前气候变化的反应是什么？因此，我们目前面临的实验挑战之一是我们通过X射线CT扫描获得的大量数据。因此，我们需要在想要扫描的样本数量和所需的分辨率之间找到适当的平衡。X 射线 CT 技术使我们能够以前所未有的速度扫描三个核心。我们有来自热带和温带?...

视频: 作者聚焦：用于树芯分析的 X 射线 CT 工具链的进步

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.

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.

科研

环境科学

Tree Core Sampling for X-ray Computed Tomography

To begin, core a tree using a Pressler borer. Put the tree cores, unglued, into six-millimeter paper straws and mark the straws using a pencil. Fill the round-bottom flask with solvent and place the straw onto a stainless steel support in the Soxhlet apparatus with a cooler on a laboratory heater.After siphoning, dry the cores for 24 hours in an oven at 103.5 degrees Celsius under exhaust ventilation. The next day, perform a hot-water Soxhlet extraction for 24 hours. Place the samples in the steel sample holders and dry them again for 24 hours.Then place the cores from the steel sample holder back in the straws.

用于 X 射线计算机断层扫描的树芯采样

Optimizing Scanning Techniques for Biomass Estimation, Tree Growth, and Anatomical Analysis at Different Scales

To begin core scanning, depending on the research purpose, select the proper sample holder type, load the tree cores in paper straws into the sample holder, and record the position of each core in the downloadable spreadsheet template. Perform X-ray micro CT scanning following proper settings and scanning protocol. To obtain density values, install CoreProcessor, RingIndicator, and CoreComparison toolboxes using the given link.Next for pre-processing the core volumes with the CoreProcessor, select the folder with the reconstructed 16-bit cross-sectional TIFF slices in the spreadsheet file. Select a couple of slices for inspection. Then select dark and white references as indicated in the spreadsheet file for wood density calculations.In a new popup window, following the information from the spreadsheet file, select every core separately by drawing a circle or ellipse around it. Then click on Mass core extraction to extract all the cores in a given cylinder. In the CoreProcessor toolbox, click on Manual TG correction then select the extracted folder and ensure proper orientation of the transversal and radial plane of every core volume.To visualize grain direction from the bottom right plot, observe the presented slice and draw a line indicating grain direction. Double click to automatically rotate the core. Then crop the core volume to get only wood and no other material.Open the RingIndicator toolbox and select a multi-page TIFF file. Then under a Volume tab, inspect the graphical user interface in the transverse and radial plane. For structural correction on the transverse and radial plane, click on the image to insert green bars starting with the pith and ending with the most recent ring.Once a green bar is placed on one plane, it automatically generates on other planes. Click Densitometry, then Densitometry plot to calculate the density profile. Create and plot a density profile by selecting Overlay plotting, and then Plot density profile.Once the density profile is visualized, indicate all tree rings. Move the nodes at the end of the bar to change the angle. Then change the bar position using the middle node and adjust the size of the nodes.Press Data, then Export. Press Rings followed by Export rings to ensure ring and fiber indications are written in the proper txt files. Change the felling date to the year when the cores were taken from the living trees, or choose an appropriate date.In Overlay plotting, select Plot rings to display the years. Also choose the plane to plot rings or the density profile. After indicating two cores, open the CoreComparison toolbox for comparing the ring width series.Select the txt files to compare. Then a screen displaying ring widths and cross dating and statistical parameters, such as glysophikite and spearman correlation between individual series will open. Open a ring indicator instance to adjust the green bars and export them again.Then maximize the core comparison screen and press the Refresh button to reevaluate the metrics. Next, select Plotting and exporting, then Ring width to visualize the tree ring width or TRW data. Click Clotting and exporting, then export RW data to export TRW data in a spreadsheet or Tucson format.Finally, select the Other plotting, then Export cluster data for obtaining mean density, MXD, MND, and quartile data per tree ring. This study demonstrates three levels of biomass estimation or tree growth increment at the inter ring, ring, and anatomical scale. Radial and axial wood density trends in Terminalia superba demonstrated an increasing density trend from pith to bark and a higher wood density in the upper stem.An example of chronology development with minimum density and maximum latewood density from Widdringtonia cedarbergensis is shown. A high resolution oak core scan demonstrated that earlywood and latewood vessels are segmented.