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Improved non-destructive 2D and 3D X-ray imaging of leaf venation

Overview of attention for article published in Plant Methods, January 2018
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
Improved non-destructive 2D and 3D X-ray imaging of leaf venation
Published in
Plant Methods, January 2018
DOI 10.1186/s13007-018-0274-y
Pubmed ID
Authors

Julio V. Schneider, Renate Rabenstein, Jens Wesenberg, Karsten Wesche, Georg Zizka, Jörg Habersetzer

Abstract

Leaf venation traits are important for many research fields such as systematics and evolutionary biology, plant physiology, climate change, and paleoecology. In spite of an increasing demand for vein trait data, studies are often still data-limited because the development of methods that allow rapid generation of large sets of vein data has lagged behind. Recently, non-destructive X-ray technology has proven useful as an alternative to traditional slow and destructive chemical-based methods. Non-destructive techniques more readily allow the use of herbarium specimens, which provide an invaluable but underexploited resource of vein data and related environmental information. The utility of 2D X-ray technology and microfocus X-ray computed tomography, however, has been compromised by insufficient image resolution. Here, we advanced X-ray technology by increasing image resolution and throughput without the application of contrast agents. For 2D contact microradiography, we developed a method which allowed us to achieve image resolutions of up to 7 µm, i.e. a 3.6-fold increase compared to the industrial standard (25 µm resolution). Vein tracing was further optimized with our image processing standards that were specifically adjusted for different types of leaf structure and the needs of higher imaging throughput. Based on a test dataset, in 91% of the samples the 7 µm approach led to a significant improvement in estimations of minor vein density compared to the industrial standard. Using microfocus X-ray computed tomography, very high-resolution images were obtained from a virtual 3D-2D transformation process, which was superior to that of 3D images. Our 2D X-ray method with a significantly improved resolution advances rapid non-destructive bulk scanning at a quality that in many cases is sufficient to determine key venation traits. Together with our high-resolution microfocus X-ray computed tomography method, both non-destructive approaches will help in vein trait data mining from museum collections, which provide an underexploited resource of historical and recent data on environmental and evolutionary change. In spite of the significant increase in effective image resolution, a combination of high-throughput and full visibility of the vein network (including the smallest veins and their connectivity) remains challenging, however.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 25%
Student > Ph. D. Student 10 18%
Student > Bachelor 6 11%
Student > Master 4 7%
Lecturer 3 5%
Other 12 21%
Unknown 8 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 44%
Engineering 7 12%
Earth and Planetary Sciences 3 5%
Computer Science 3 5%
Physics and Astronomy 2 4%
Other 9 16%
Unknown 8 14%
Attention Score in Context

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 03 June 2020.
All research outputs
#12,768,437
of 23,016,919 outputs
Outputs from Plant Methods
#539
of 1,088 outputs
Outputs of similar age
#199,671
of 441,339 outputs
Outputs of similar age from Plant Methods
#9
of 29 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,088 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 49th percentile – i.e., 49% 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 441,339 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 29 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.