Evidence map›Paper›PMID 28265297›Full record

ArticlePlant methods2017

The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology.

Thomas Burrell, Susan Fozard, Geoff H Holroyd, Andrew P French, Michael P Pound, Christopher J Bigley, C James Taylor, Brian G Forde

Open access · goldAbstract read
In one paragraph

Article in Plant methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
5.6field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Plant Leaf Position Estimation with Computer Vision.Sensors (Basel, Switzerland) · 2020
    Article
  7. The platformPlant methods · 2020
    Article
  8. Article
  9. 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

8 authors at 2 institutions in 1 country.

Thomas BurrellEngineering Department, Lancaster University, Lancaster, LA1 4YR UK.
Susan FozardLancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ UK.
Geoff H HolroydLancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ UK.
Andrew P FrenchThe Centre for Plant Integrative Biology, School of Biosciences, Sutton Bonington Campus, University of Nottingham, Nottingham, LE12 5RD UK.
Michael P PoundThe Centre for Plant Integrative Biology, School of Biosciences, Sutton Bonington Campus, University of Nottingham, Nottingham, LE12 5RD UK.
Christopher J BigleyLancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ UK.
C James TaylorEngineering Department, Lancaster University, Lancaster, LA1 4YR UK.
Brian G FordeLancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ UK.ORCID 0000-0001-7973-7280
Lancaster University · GBUniversity of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChemical genetics provides a powerful alternative to conventional genetics for understanding gene function. However, its application to plants has been limited by the lack of a technology that allows detailed phenotyping of whole-seedling development in the context of a high-throughput chemical screen. We have therefore sought to develop an automated micro-phenotyping platform that would allow both root and shoot development to be monitored under conditions where the phenotypic effects of large numbers of small molecules can be assessed.

resultsThe 'Microphenotron' platform uses 96-well microtitre plates to deliver chemical treatments to seedlings of

conclusionsThe Microphenotron is an automated screening platform that for the first time is able to combine large numbers of individual chemical treatments with a detailed analysis of whole-seedling development, and particularly root system development. The Microphenotron should provide a powerful new tool for chemical genetics and for wider chemical biology applications, including the development of natural and synthetic chemical products for improved agricultural sustainability.

Indexed as

Arabidopsis thalianaAutomatedBiostimulantsChemical biologyChemical geneticsEragrostis tefPlant phenotypingRoboticRoot system architectureShoot development

Identifiers

PMID28265297
PMCPMC5333401
OpenAlexW2593702528

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.