“Chamber #8” – a holistic approach of high-throughput non-destructive assessment of plant roots - Claussen, Joelle; Wittenberg, Thomas; Uhlmann, Norman; Gerth, Stefan (Frontiers in Plant Science, 2024)
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 the access to non-destructively measured traits is much more challenging. Even though MRI or CT imaging techniques have been established in the past years, it relies on an adequate infrastructure for the automatic handling of the pots as well as the controlled climate. 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. The proposed holistic approach allows us to study root growth of plants in 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 has already been applied to a wide variety of root structures, such as potatoes, cassava, or corn. It enables breeders and scientists non-destructive access to root traits. Additionally, due to the non-destructive nature of X-ray CT, 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.