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RootBot: High-throughput root stress phenotyping robot.
Ruppel, Mia; Nelson, Sven K; Sidberry, Grace; Mitchell, Madison; Kick, Daniel; Thomas, Shawn K; Guill, Katherine E; Oliver, Melvin J; Washburn, Jacob D.
Afiliación
  • Ruppel M; Department of Biomedical, Biological, and Chemical Engineering University of Missouri Columbia Missouri USA.
  • Nelson SK; Director of Plant Science Heliponix, LLC Evansville Indiana USA.
  • Sidberry G; Plant Genetics Research Unit USDA-ARS Columbia Missouri USA.
  • Mitchell M; Division of Plant Science and Technology University of Missouri Columbia Missouri USA.
  • Kick D; Division of Plant Science and Technology University of Missouri Columbia Missouri USA.
  • Thomas SK; Plant Genetics Research Unit USDA-ARS Columbia Missouri USA.
  • Guill KE; Division of Biological Sciences University of Missouri Columbia Missouri USA.
  • Oliver MJ; Division of Plant Science and Technology University of Missouri Columbia Missouri USA.
  • Washburn JD; Division of Plant Science and Technology University of Missouri Columbia Missouri USA.
Appl Plant Sci ; 11(6): e11541, 2023.
Article en En | MEDLINE | ID: mdl-38106535
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Appl Plant Sci Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Appl Plant Sci Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos