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Evaluation of the SeedCounter, A Mobile Application for Grain Phenotyping

Overview of attention for article published in Frontiers in Plant Science, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
1 blog
twitter
8 X users
facebook
2 Facebook pages

Citations

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73 Dimensions

Readers on

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85 Mendeley
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Title
Evaluation of the SeedCounter, A Mobile Application for Grain Phenotyping
Published in
Frontiers in Plant Science, January 2017
DOI 10.3389/fpls.2016.01990
Pubmed ID
Authors

Evgenii Komyshev, Mikhail Genaev, Dmitry Afonnikov

Abstract

Grain morphometry in cereals is an important step in selecting new high-yielding plants. Manual assessment of parameters such as the number of grains per ear and grain size is laborious. One solution to this problem is image-based analysis that can be performed using a desktop PC. Furthermore, the effectiveness of analysis performed in the field can be improved through the use of mobile devices. In this paper, we propose a method for the automated evaluation of phenotypic parameters of grains using mobile devices running the Android operational system. The experimental results show that this approach is efficient and sufficiently accurate for the large-scale analysis of phenotypic characteristics in wheat grains. Evaluation of our application under six different lighting conditions and three mobile devices demonstrated that the lighting of the paper has significant influence on the accuracy of our method, unlike the smartphone type.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 85 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 21%
Student > Master 9 11%
Student > Ph. D. Student 8 9%
Student > Bachelor 6 7%
Student > Postgraduate 6 7%
Other 16 19%
Unknown 22 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 42%
Engineering 6 7%
Biochemistry, Genetics and Molecular Biology 6 7%
Environmental Science 2 2%
Computer Science 2 2%
Other 7 8%
Unknown 26 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 25 April 2017.
All research outputs
#2,106,871
of 22,940,083 outputs
Outputs from Frontiers in Plant Science
#876
of 20,366 outputs
Outputs of similar age
#45,725
of 421,382 outputs
Outputs of similar age from Frontiers in Plant Science
#16
of 539 outputs
Altmetric has tracked 22,940,083 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 20,366 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 95% 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 421,382 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 539 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 97% of its contemporaries.