Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses

• Published in: The Plant journal : for cell and molecular biology Vol. 107; no. 6; pp. 1837 - 1853
• Main Authors: Xiang, Lirong, Nolan, Trevor M., Bao, Yin, Elmore, Mitch, Tuel, Taylor, Gai, Jingyao, Shah, Dylan, Wang, Ping, Huser, Nicole M., Hurd, Ashley M., McLaughlin, Sean A., Howell, Stephen H., Walley, Justin W., Yin, Yanhai, Tang, Lie
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01-09-2021
• Subjects: 2D and 3D imaging; Algorithms; Arabidopsis; Arabidopsis - drug effects; Arabidopsis - physiology; Arabidopsis Proteins - genetics; Arabidopsis thaliana; Assaying; Automation; Biosynthesis; Brassinosteroid; Brassinosteroids; Brassinosteroids - metabolism; Corn; Drought; Droughts; Equipment Design; Experiments; Hormones; Image processing; Image Processing, Computer-Assisted - methods; Image segmentation; leaf segmentation; Learning algorithms; Leaves; Machine Learning; Parameter identification; Phenotype; phenotypic traits; Phenotyping; Plant extracts; Plant growth; Plants; Profilometers; Propiconazole; Protein Kinases - genetics; Roads; Robot arms; Robotics; Robotics - instrumentation; Robotics - methods; Seedlings - physiology; Soil - chemistry; Steroid hormones; technical advance; Triazoles - pharmacology; Zea mays; Zea mays - physiology; Arabidopsis thaliana; plant growth; Brassinosteroid; phenotypic traits; 2D and 3D imaging; drought; technical advance; leaf segmentation
• ISSN: 0960-7412; 1365-313X
• DOI: 10.1111/tpj.15401

Summary
Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, development, and stress responses. Many components of the BR pathway have previously been identified and characterized. However, BR phenotyping experiments are typically performed in a low‐throughput manner, such as on Petri plates. Additionally, the BR pathway affects drought responses, but drought experiments are time consuming and difficult to control. To mitigate these issues and increase throughput, we developed the Robotic Assay for Drought (RoAD) system to perform BR and drought response experiments in soil‐grown Arabidopsis plants. RoAD is equipped with a robotic arm, a rover, a bench scale, a precisely controlled watering system, an RGB camera, and a laser profilometer. It performs daily weighing, watering, and imaging tasks and is capable of administering BR response assays by watering plants with Propiconazole (PCZ), a BR biosynthesis inhibitor. We developed image processing algorithms for both plant segmentation and phenotypic trait extraction to accurately measure traits including plant area, plant volume, leaf length, and leaf width. We then applied machine learning algorithms that utilize the extracted phenotypic parameters to identify image‐derived traits that can distinguish control, drought‐treated, and PCZ‐treated plants. We carried out PCZ and drought experiments on a set of BR mutants and Arabidopsis accessions with altered BR responses. Finally, we extended the RoAD assays to perform BR response assays using PCZ in Zea mays (maize) plants. This study establishes an automated and non‐invasive robotic imaging system as a tool to accurately measure morphological and growth‐related traits of Arabidopsis and maize plants in 3D, providing insights into the BR‐mediated control of plant growth and stress responses.
Significance Statement
RoAD is an automated phenotyping system for assessing brassinosteroid and drought responses in soil‐grown Arabidopsis plants. The system performs daily weighing, watering, and imaging tasks and is capable of accurately measuring morphological and growth‐related traits of Arabidopsis in 3D.