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Rapid determination of leaf area and plant height by using light curtain arrays in four species with contrasting shoot architecture

Overview of attention for article published in Plant Methods, April 2014
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Title
Rapid determination of leaf area and plant height by using light curtain arrays in four species with contrasting shoot architecture
Published in
Plant Methods, April 2014
DOI 10.1186/1746-4811-10-9
Pubmed ID
Authors

Dimitrios Fanourakis, Christoph Briese, Johannes FJ Max, Silke Kleinen, Alexander Putz, Fabio Fiorani, Andreas Ulbrich, Ulrich Schurr

Abstract

Light curtain arrays (LC), a recently introduced phenotyping method, yield a binary data matrix from which a shoot silhouette is reconstructed. We addressed the accuracy and applicability of LC in assessing leaf area and maximum height (base to the highest leaf tip) in a phenotyping platform. LC were integrated to an automated routine for positioning, allowing in situ measurements. Two dicotyledonous (rapeseed, tomato) and two monocotyledonous (maize, barley) species with contrasting shoot architecture were investigated. To evaluate if averaging multiple view angles helps in resolving self-overlaps, we acquired a data set by rotating plants every 10° for 170°. To test how rapid these measurements can be without loss of information, we evaluated nine scanning speeds. Leaf area of overlapping plants was also estimated to assess the possibility to scale this method for plant stands.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 2 2%
Japan 1 1%
Germany 1 1%
France 1 1%
Unknown 91 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 28%
Student > Ph. D. Student 21 22%
Student > Master 13 14%
Student > Bachelor 8 8%
Student > Postgraduate 5 5%
Other 8 8%
Unknown 14 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 49 51%
Engineering 9 9%
Environmental Science 6 6%
Biochemistry, Genetics and Molecular Biology 4 4%
Computer Science 3 3%
Other 5 5%
Unknown 20 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 April 2014.
All research outputs
#14,779,591
of 22,753,345 outputs
Outputs from Plant Methods
#776
of 1,080 outputs
Outputs of similar age
#128,222
of 226,967 outputs
Outputs of similar age from Plant Methods
#6
of 6 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,080 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 23rd percentile – i.e., 23% 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 226,967 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.