UGent-Woodlab, Laboratory of Wood Technology, Department of Environment, Ghent University, Gent, Belgium.
Ghent University Centre for X-ray Tomography (UGCT), Gent, Belgium.
Ann Bot. 2019 Nov 15;124(5):837-847. doi: 10.1093/aob/mcz126.
Tree rings, as archives of the past and biosensors of the present, offer unique opportunities to study influences of the fluctuating environment over decades to centuries. As such, tree-ring-based wood traits are capital input for global vegetation models. To contribute to earth system sciences, however, sufficient spatial coverage is required of detailed individual-based measurements, necessitating large amounts of data. X-ray computed tomography (CT) scanning is one of the few techniques that can deliver such data sets.
Increment cores of four different temperate tree species were scanned with a state-of-the-art X-ray CT system at resolutions ranging from 60 μm down to 4.5 μm, with an additional scan at a resolution of 0.8 μm of a splinter-sized sample using a second X-ray CT system to highlight the potential of cell-level scanning. Calibration-free densitometry, based on full scanner simulation of a third X-ray CT system, is illustrated on increment cores of a tropical tree species.
We show how multiscale scanning offers unprecedented potential for mapping tree rings and wood traits without sample manipulation and with limited operator intervention. Custom-designed sample holders enable simultaneous scanning of multiple increment cores at resolutions sufficient for tree ring analysis and densitometry as well as single core scanning enabling quantitative wood anatomy, thereby approaching the conventional thin section approach. Standardized X-ray CT volumes are, furthermore, ideal input imagery for automated pipelines with neural-based learning for tree ring detection and measurements of wood traits.
Advanced X-ray CT scanning for high-throughput processing of increment cores is within reach, generating pith-to-bark ring width series, density profiles and wood trait data. This would allow contribution to large-scale monitoring and modelling efforts with sufficient global coverage.
树木年轮作为过去的档案和当前的生物传感器，为研究几十年到几个世纪以来环境波动的影响提供了独特的机会。因此，基于树木年轮的木材特性是全球植被模型的重要投入。然而，为了为地球系统科学做出贡献，需要详细的个体测量具有足够的空间覆盖范围，这需要大量的数据。X 射线计算机断层扫描（CT）扫描是为数不多的可以提供此类数据集的技术之一。
使用最先进的 X 射线 CT 系统以 60μm 至 4.5μm 的分辨率扫描了四个不同温带树种的增量芯，并且使用第二个 X 射线 CT 系统以 0.8μm 的分辨率扫描了一个小块样本，以突出细胞级扫描的潜力。基于对第三个 X 射线 CT 系统的全扫描仪模拟的无标度密度测量法，在热带树种的增量芯上进行了说明。
我们展示了多尺度扫描如何在不进行样本处理和有限的操作人员干预的情况下，提供对树木年轮和木材特性进行映射的前所未有的潜力。定制设计的样品架能够以足够的分辨率同时扫描多个增量芯，以便进行树木年轮分析和密度测量，以及单个核心扫描，从而实现定量木材解剖学，从而接近传统的薄片方法。此外，标准化的 X 射线 CT 体是用于具有基于神经的学习的自动管道的理想输入图像，用于树木年轮检测和木材特性测量。
高级 X 射线 CT 扫描可实现增量芯的高通量处理，生成从髓心到树皮的宽度系列、密度分布和木材特性数据。这将允许为具有足够全球覆盖范围的大规模监测和建模工作做出贡献。
