最近，科学家利用高通量CT发表了题为““Chamber #8” – a holistic approach of high-throughput non-destructive assessment of plant roots”的文章，科学家开发了植物根系的无损成像与高度自动化和标准化的中通量方法相结合的方法。 

“Chamber #8” – 一种对植物根系进行高通量无损评估的整体方法

简介：在过去几年中，人们观察到植物的育种变得更具挑战性，因为表型数据的可见差异比几十年前要小得多。随着气候变化的持续，有必要培育能够应对不断变化的气候条件的作物。要为将来选择良好的候选育种品种，可以在气候受控条件下进行表型实验。地上性状可以用不同的光学传感器进行评估，但对于根系生长，获得非破坏性测量的性状更具挑战性。尽管MRI或CT成像技术在过去几年中已经建立起来，但它们依赖于足够的基础设施来自动处理花盆以及控制气候。

方法：为了同时应对这两个挑战，将植物根系的无损成像与高度自动化和标准化的中通量方法相结合，我们开发了一个工作流程和一个集成扫描设施来研究根系生长。我们的“室#8”包含一个气候室、一个物料流控制、一个灌溉系统、一个 X 射线系统、一个用于自动数据收集和后处理的数据库。这种方法的目标是一方面将人与设施各个组件的交互减少到最低限度，另一方面实现从植物护理到测量到根系性状计算的整个过程的自动化和标准化。用户收到客观收集的标准化表型性状和特性。

“Chamber #8” – a holistic approach of high-throughput non-destructive assessment of plant roots

Introduction: In the past years, it has been observed that the breeding of plants has become more challenging, as the visible difference in phenotypic data is much smaller than decades ago. With the ongoing climate change, it is necessary to breed crops that can cope with shifting climatic conditions. To select good breeding candidates for the future, phenotypic experiments can be conducted under climate-controlled conditions. Above-ground traits can be assessed with different optical sensors, but for the root growth, access to non-destructively measured traits is much more challenging. Even though MRI or CT imaging techniques have been established in the past years, they rely on an adequate infrastructure for the automatic handling of the pots as well as the controlled climate.

Methods: To address both challenges simultaneously, the non-destructive imaging of plant roots combined with a highly automated and standardized mid-throughput approach, we developed a workflow and an integrated scanning facility to study root growth. Our “chamber #8” contains a climate chamber, a material flow control, an irrigation system, an X-ray system, a database for automatic data collection, and post-processing. The goals of this approach are to reduce the human interaction with the various components of the facility to a minimum on one hand, and to automate and standardize the complete process from plant care via measurements to root trait calculation on the other. The user receives standardized phenotypic traits and properties that were collected objectively.

Results: The proposed holistic approach allows us to study root growth of plants in a field-like substrate non-destructively over a defined period and to calculate phenotypic traits of root architecture. For different crops, genotypic differences can be observed in response to climatic conditions which have already been applied to a wide variety of root structures, such as potatoes, cassava, or corn. 

Discussion: It enables breeders and scientists non-destructive access to root traits. Additionally, due to the non-destructive nature of X-ray computed tomography, the analysis of time series for root growing experiments is possible and enables the observation of kinetic traits. Furthermore, using this automation scheme for simultaneously controlled plant breeding and non-destructive testing reduces the involvement of human resources.