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PHIV-RootCell: a supervised image analysis tool for rice root anatomical parameter quantification

Overview of attention for article published in Frontiers in Plant Science, January 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

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1 blog
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52 Mendeley
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Title
PHIV-RootCell: a supervised image analysis tool for rice root anatomical parameter quantification
Published in
Frontiers in Plant Science, January 2015
DOI 10.3389/fpls.2014.00790
Pubmed ID
Authors

Marc Lartaud, Christophe Perin, Brigitte Courtois, Emilie Thomas, Sophia Henry, Mathilde Bettembourg, Fanchon Divol, Nadege Lanau, Florence Artus, Charlotte Bureau, Jean-Luc Verdeil, Gautier Sarah, Emmanuel Guiderdoni, Anne Dievart

Abstract

We developed the PHIV-RootCell software to quantify anatomical traits of rice roots transverse section images. Combined with an efficient root sample processing method for image acquisition, this program permits supervised measurements of areas (those of whole root section, stele, cortex, and central metaxylem vessels), number of cell layers and number of cells per cell layer. The PHIV-RootCell toolset runs under ImageJ, an independent operating system that has a license-free status. To demonstrate the usefulness of PHIV-RootCell, we conducted a genetic diversity study and an analysis of salt stress responses of root anatomical parameters in rice (Oryza sativa L.). Using 16 cultivars, we showed that we could discriminate between some of the varieties even at the 6 day-olds stage, and that tropical japonica varieties had larger root sections due to an increase in cell number. We observed, as described previously, that root sections become enlarged under salt stress. However, our results show an increase in cell number in ground tissues (endodermis and cortex) but a decrease in external (peripheral) tissues (sclerenchyma, exodermis, and epidermis). Thus, the PHIV-RootCell program is a user-friendly tool that will be helpful for future genetic and physiological studies that investigate root anatomical trait variations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 2%
United Kingdom 1 2%
Chile 1 2%
Unknown 49 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 27%
Student > Ph. D. Student 9 17%
Student > Bachelor 4 8%
Student > Master 3 6%
Student > Doctoral Student 3 6%
Other 10 19%
Unknown 9 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 60%
Biochemistry, Genetics and Molecular Biology 5 10%
Environmental Science 2 4%
Unspecified 1 2%
Neuroscience 1 2%
Other 1 2%
Unknown 11 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 18 February 2015.
All research outputs
#2,108,820
of 24,140,950 outputs
Outputs from Frontiers in Plant Science
#854
of 22,552 outputs
Outputs of similar age
#30,359
of 360,470 outputs
Outputs of similar age from Frontiers in Plant Science
#6
of 214 outputs
Altmetric has tracked 24,140,950 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,552 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 96% 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 360,470 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 91% of its contemporaries.
We're also able to compare this research output to 214 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.