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Diel leaf growth of soybean: a novel method to analyze two-dimensional leaf expansion in high temporal resolution based on a marker tracking approach (Martrack Leaf)

Overview of attention for article published in Plant Methods, July 2013
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
52 Mendeley
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Title
Diel leaf growth of soybean: a novel method to analyze two-dimensional leaf expansion in high temporal resolution based on a marker tracking approach (Martrack Leaf)
Published in
Plant Methods, July 2013
DOI 10.1186/1746-4811-9-30
Pubmed ID
Authors

Michael Mielewczik, Michael Friedli, Norbert Kirchgessner, Achim Walter

Abstract

We present a novel method for quantitative analysis of dicot leaf expansion at high temporal resolution. Image sequences of growing leaves were assessed using a marker tracking algorithm. An important feature of the method is the attachment of dark beads that serve as artificial landmarks to the leaf margin. The beads are mechanically constricted to the focal plane of a camera. Leaf expansion is approximated by the increase in area of the polygon defined by the centers of mass of the beads surrounding the leaf. Fluctuating illumination conditions often pose serious problems for tracking natural structures of a leaf; this problem is circumvented here by the use of the beads.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 3 6%
India 1 2%
France 1 2%
Paraguay 1 2%
Germany 1 2%
Japan 1 2%
Unknown 44 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 27%
Student > Master 12 23%
Student > Ph. D. Student 11 21%
Other 2 4%
Professor 2 4%
Other 5 10%
Unknown 6 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 58%
Engineering 4 8%
Computer Science 3 6%
Environmental Science 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 2 4%
Unknown 10 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 07 June 2014.
All research outputs
#9,352,008
of 17,351,915 outputs
Outputs from Plant Methods
#425
of 835 outputs
Outputs of similar age
#73,930
of 166,096 outputs
Outputs of similar age from Plant Methods
#5
of 9 outputs
Altmetric has tracked 17,351,915 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 835 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 166,096 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 54% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.