↓ Skip to main content

Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform

Overview of attention for article published in Plant Methods, June 2018
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

dimensions_citation
79 Dimensions

Readers on

mendeley
102 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform
Published in
Plant Methods, June 2018
DOI 10.1186/s13007-018-0313-8
Pubmed ID
Authors

Stefan Thomas, Jan Behmann, Angelina Steier, Thorsten Kraska, Onno Muller, Uwe Rascher, Anne-Katrin Mahlein

Abstract

Phenotyping is a bottleneck for the development of new plant cultivars. This study introduces a new hyperspectral phenotyping system, which combines the high throughput of canopy scale measurements with the advantages of high spatial resolution and a controlled measurement environment. Furthermore, the measured barley canopies were grown in large containers (called Mini-Plots), which allow plants to develop field-like phenotypes in greenhouse experiments, without being hindered by pot size. Six barley cultivars have been investigated via hyperspectral imaging up to 30 days after inoculation with powdery mildew. With a high spatial resolution and stable measurement conditions, it was possible to automatically quantify powdery mildew symptoms through a combination of Simplex Volume Maximization and Support Vector Machines. Detection was feasible as soon as the first symptoms were visible for the human eye during manual rating. An accurate assessment of the disease severity for all cultivars at each measurement day over the course of the experiment was realized. Furthermore, powdery mildew resistance based necrosis of one cultivar was detected as well. The hyperspectral phenotyping system combines the advantages of field based canopy level measurement systems (high throughput, automatization, low manual workload) with those of laboratory based leaf level measurement systems (high spatial resolution, controlled environment, stable conditions for time series measurements). This allows an accurate and objective disease severity assessment without the need for trained experts, who perform visual rating, as well as detection of disease symptoms in early stages. Therefore, it is a promising tool for plant resistance breeding.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 16%
Student > Ph. D. Student 14 14%
Student > Master 10 10%
Student > Bachelor 9 9%
Student > Doctoral Student 7 7%
Other 13 13%
Unknown 33 32%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 34%
Engineering 9 9%
Biochemistry, Genetics and Molecular Biology 5 5%
Environmental Science 3 3%
Computer Science 3 3%
Other 8 8%
Unknown 39 38%
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 20 August 2020.
All research outputs
#13,040,318
of 23,088,369 outputs
Outputs from Plant Methods
#572
of 1,094 outputs
Outputs of similar age
#157,672
of 328,957 outputs
Outputs of similar age from Plant Methods
#17
of 29 outputs
Altmetric has tracked 23,088,369 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,094 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 46th percentile – i.e., 46% 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 328,957 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 51% 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 is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.