Pfeifer Johannes, Kirchgessner Norbert, Colombi Tino, Walter Achim
Institute of Agricultural Sciences, Swiss Federal Institute of Technology in Zurich (ETH Zürich), Universitätstrasse 2, 8092 Zurich, Switzerland.
Plant Methods. 2015 Aug 28;11:41. doi: 10.1186/s13007-015-0084-4. eCollection 2015.
X-ray computed tomography (CT) has become a powerful tool for root phenotyping. Compared to rather classical, destructive methods, CT encompasses various advantages. In pot experiments the growth and development of the same individual root can be followed over time and in addition the unaltered configuration of the 3D root system architecture (RSA) interacting with a real field soil matrix can be studied. Yet, the throughput, which is essential for a more widespread application of CT for basic research or breeding programs, suffers from the bottleneck of rapid and standardized segmentation methods to extract root structures. Using available methods, root segmentation is done to a large extent manually, as it requires a lot of interactive parameter optimization and interpretation and therefore needs a lot of time.
Based on commercially available software, this paper presents a protocol that is faster, more standardized and more versatile compared to existing segmentation methods, particularly if used to analyse field samples collected in situ. To the knowledge of the authors this is the first study approaching to develop a comprehensive segmentation method suitable for comparatively large columns sampled in situ which contain complex, not necessarily connected root systems from multiple plants grown in undisturbed field soil. Root systems from several crops were sampled in situ and CT-volumes determined with the presented method were compared to root dry matter of washed root samples. A highly significant (P < 0.01) and strong correlation (R(2) = 0.84) was found, demonstrating the value of the presented method in the context of field research. Subsequent to segmentation, a method for the measurement of root thickness distribution has been used. Root thickness is a central RSA trait for various physiological research questions such as root growth in compacted soil or under oxygen deficient soil conditions, but hardly assessable in high throughput until today, due to a lack of available protocols.
Application of the presented protocol helps to overcome the segmentation bottleneck and can be considered a step forward to high throughput root phenotyping facilitating appropriate sample sizes desired by science and breeding.
X射线计算机断层扫描（CT）已成为根系表型分析的有力工具。与较为传统的破坏性方法相比，CT具有多种优势。在盆栽实验中，可以随时间跟踪同一根系个体的生长发育，此外，还可以研究与真实田间土壤基质相互作用的三维根系结构（RSA）的未改变构型。然而，对于CT在基础研究或育种计划中的更广泛应用至关重要的通量，却受到快速且标准化的分割方法以提取根系结构这一瓶颈的限制。使用现有方法时，根系分割在很大程度上是手动完成的，因为这需要大量的交互式参数优化和解释，因此需要大量时间。
基于商业软件，本文提出了一种与现有分割方法相比更快、更标准化且更通用的方案，特别是用于分析原位采集的田间样本时。据作者所知，这是第一项致力于开发一种适用于原位采集的相对较大柱体样本的综合分割方法的研究，这些样本包含在未扰动田间土壤中生长的多株植物的复杂且不一定相连的根系。对几种作物的根系进行了原位采样，并将用本文提出的方法确定的CT体积与洗净根系样本的根干物质进行了比较。发现两者具有极显著相关性（P < 0.01）且相关性很强（R² = 0.84），这证明了本文提出的方法在田间研究中的价值。分割之后，采用了一种测量根厚度分布的方法。根厚度是各种生理研究问题（如紧实土壤或缺氧土壤条件下的根系生长）的核心RSA性状，但由于缺乏可用方案，迄今为止很难进行高通量评估。
本文提出的方案的应用有助于克服分割瓶颈，可以被视为向高通量根系表型分析迈出的一步，促进了科学和育种所需的合适样本量的实现。
