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

Overview of attention for article published in Plant Methods, March 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#32 of 1,184)
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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66 X users
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1 Facebook page

Citations

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18 Dimensions

Readers on

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92 Mendeley
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Title
The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology
Published in
Plant Methods, March 2017
DOI 10.1186/s13007-017-0158-6
Pubmed ID
Authors

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

Abstract

Chemical 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. The 'Microphenotron' platform uses 96-well microtitre plates to deliver chemical treatments to seedlings of Arabidopsis thaliana L. and is based around four components: (a) the 'Phytostrip', a novel seedling growth device that enables chemical treatments to be combined with the automated capture of images of developing roots and shoots; (b) an illuminated robotic platform that uses a commercially available robotic manipulator to capture images of developing shoots and roots; (c) software to control the sequence of robotic movements and integrate these with the image capture process; (d) purpose-made image analysis software for automated extraction of quantitative phenotypic data. Imaging of each plate (representing 80 separate assays) takes 4 min and can easily be performed daily for time-course studies. As currently configured, the Microphenotron has a capacity of 54 microtitre plates in a growth room footprint of 2.1 m(2), giving a potential throughput of up to 4320 chemical treatments in a typical 10 days experiment. The Microphenotron has been validated by using it to screen a collection of 800 natural compounds for qualitative effects on root development and to perform a quantitative analysis of the effects of a range of concentrations of nitrate and ammonium on seedling development. The 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 66 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 1 1%
Unknown 91 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 32%
Researcher 20 22%
Student > Master 7 8%
Professor 4 4%
Student > Doctoral Student 4 4%
Other 8 9%
Unknown 20 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 48%
Biochemistry, Genetics and Molecular Biology 14 15%
Engineering 3 3%
Environmental Science 2 2%
Computer Science 2 2%
Other 4 4%
Unknown 23 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 39. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 June 2019.
All research outputs
#997,935
of 24,590,593 outputs
Outputs from Plant Methods
#32
of 1,184 outputs
Outputs of similar age
#20,758
of 315,825 outputs
Outputs of similar age from Plant Methods
#3
of 20 outputs
Altmetric has tracked 24,590,593 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,184 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,825 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.