Evidence map›Paper›PMID 38106535›Full record

ArticleApplications in plant sciences

RootBot: High-throughput root stress phenotyping robot.

Mia Ruppel, Sven K Nelson, Grace Sidberry, Madison Mitchell, Daniel Kick, Shawn K Thomas, Katherine E Guill, Melvin J Oliver, Jacob D Washburn

Open access · goldAbstract read
In one paragraph

Article in Applications in plant sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Mia RuppelDepartment of Biomedical, Biological, and Chemical Engineering University of Missouri Columbia Missouri USA.
Sven K NelsonDirector of Plant Science Heliponix, LLC Evansville Indiana USA.ORCID 0000-0002-2409-1176
Grace SidberryDivision of Plant Science and Technology University of Missouri Columbia Missouri USA.
Madison MitchellDivision of Plant Science and Technology University of Missouri Columbia Missouri USA.
Daniel KickPlant Genetics Research Unit USDA-ARS Columbia Missouri USA.ORCID 0000-0002-9002-1862
Shawn K ThomasDivision of Biological Sciences University of Missouri Columbia Missouri USA.ORCID 0000-0002-6198-8847
Katherine E GuillDivision of Plant Science and Technology University of Missouri Columbia Missouri USA.
Melvin J OliverDivision of Plant Science and Technology University of Missouri Columbia Missouri USA.ORCID 0000-0002-5991-5788
Jacob D WashburnPlant Genetics Research Unit USDA-ARS Columbia Missouri USA.ORCID 0000-0003-0185-7105
University of Missouri · USAgricultural Research Service · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

automationdrought stressphenotypingroots

Identifiers

PMID38106535
PMCPMC10719875
OpenAlexW4386253944

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.