Location: Plant Genetics ResearchTitle: RootBot: high-throughput root stress phenotyping robot
|RUPPEL, MIA - University Of Missouri|
|NELSON, SVEN - Heliponix, Llc|
|SIDBERRY, GRACE - University Of Missouri|
|MITCHELL, MADISON - University Of Missouri|
|THOMAS, SHAWN - University Of Missouri|
|GUILL, KATHERINE - University Of Missouri|
|OLIVER, MELVIN - University Of Missouri|
Submitted to: Applications in Plant Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/5/2023
Publication Date: 8/29/2023
Citation: Ruppel, M., Nelson, S., Sidberry, G., Mitchell, M., Kick, D.R., Thomas, S., Guill, K., Oliver, M., Washburn, J.D. 2023. RootBot: high-throughput root stress phenotyping robot. Applications in Plant Sciences. 11(6): Article e11541. https://doi.org/10.1002/aps3.11541.
Interpretive Summary: Phenotyping roots under drought stress is challenging both in the quantification of underground roots and the measurement and control of soil water content. RootBot is a robotic phenotyping system that overcomes some of these challenges by growing seeds in horizontal plates with clear sides and a gantry system for organizing and photographing roots as they grow in those plates.
Technical Abstract: Premise Higher temperatures across the globe are causing an increase in the frequency and severity of droughts. In agricultural crops, this results in reduced yields, financial losses, and increased food costs at the supermarket. Root growth maintenance in drying soils plays a major role in a plant's ability to survive and perform under drought, but phenotyping root growth is extremely difficult due to roots being under the soil. Methods and Results RootBot is an automated high-throughput phenotyping robot that eliminates many of the difficulties and reduces the time required for performing drought-stress studies on primary roots. RootBot simulates root growth conditions using transparent plates to create a gap that is filled with soil and polyethylene glycol (PEG) to simulate low soil moisture. RootBot has a gantry system with vertical slots to hold the transparent plates, which theoretically allows for evaluating more than 50 plates at a time. Software pipelines were also co-opted, developed, tested, and extensively refined for running the RootBot imaging process, storing and organizing the images, and analyzing and extracting data. Conclusions The RootBot platform and the lessons learned from its design and testing represent a valuable resource for better understanding drought tolerance mechanisms in roots, as well as for identifying breeding and genetic engineering targets for crop plants.