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High-throughput phenotyping of plant resistance to aphids by automated video tracking

Overview of attention for article published in Plant Methods, January 2015
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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5 X users
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1 Google+ user

Citations

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32 Dimensions

Readers on

mendeley
113 Mendeley
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1 CiteULike
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Title
High-throughput phenotyping of plant resistance to aphids by automated video tracking
Published in
Plant Methods, January 2015
DOI 10.1186/s13007-015-0044-z
Pubmed ID
Authors

Karen J Kloth, Cindy JM ten Broeke, Manus PM Thoen, Marianne Hanhart-van den Brink, Gerrie L Wiegers, Olga E Krips, Lucas PJJ Noldus, Marcel Dicke, Maarten A Jongsma

Abstract

Piercing-sucking insects are major vectors of plant viruses causing significant yield losses in crops. Functional genomics of plant resistance to these insects would greatly benefit from the availability of high-throughput, quantitative phenotyping methods.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Netherlands 2 2%
France 1 <1%
Unknown 108 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 22%
Student > Ph. D. Student 20 18%
Student > Master 15 13%
Student > Bachelor 10 9%
Student > Doctoral Student 3 3%
Other 12 11%
Unknown 28 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 68 60%
Biochemistry, Genetics and Molecular Biology 4 4%
Engineering 3 3%
Computer Science 3 3%
Environmental Science 2 2%
Other 3 3%
Unknown 30 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 27 September 2016.
All research outputs
#7,356,550
of 25,374,917 outputs
Outputs from Plant Methods
#465
of 1,262 outputs
Outputs of similar age
#93,668
of 361,486 outputs
Outputs of similar age from Plant Methods
#11
of 18 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 62% 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 361,486 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.