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Comparison of visible imaging, thermography and spectrometry methods to evaluate the effect of Heterodera schachtii inoculation on sugar beets

Overview of attention for article published in Plant Methods, September 2017
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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Title
Comparison of visible imaging, thermography and spectrometry methods to evaluate the effect of Heterodera schachtii inoculation on sugar beets
Published in
Plant Methods, September 2017
DOI 10.1186/s13007-017-0223-1
Pubmed ID
Authors

Samuel Joalland, Claudio Screpanti, Frank Liebisch, Hubert Vincent Varella, Alain Gaume, Achim Walter

Abstract

Phenotyping technologies are expected to provide predictive power for a range of applications in plant and crop sciences. Here, we use the disease pressure of Beet Cyst Nematodes (BCN) on sugar beet as an illustrative example to test the specific capabilities of different methods. Strong links between the above and belowground parts of sugar beet plants have made BCN suitable targets for use of non-destructive phenotyping methods. We compared the ability of visible light imaging, thermography and spectrometry to evaluate the effect of BCN on the growth of sugar beet plants. Two microplot experiments were sown with the nematode susceptible cultivar Aimanta and the nematode tolerant cultivar BlueFox under semi-field conditions. Visible imaging, thermal imaging and spectrometry were carried out on BCN infested and non-infested plants at different times during the plant development. Effects of a chemical nematicide were also evaluated using the three phenotyping methods. Leaf and beet biomass were measured at harvest. For both susceptible and tolerant cultivar, canopy area extracted from visible images was the earliest nematode stress indicator. Using such canopy area parameter, delay in leaf growth as well as benefit from a chemical nematicide could be detected already 15 days after sowing. Spectrometry was suitable to identify the stress even when the canopy reached full coverage. Thermography could only detect stress on the susceptible cultivar. Spectral Vegetation Indices related to canopy cover (NDVI and MCARI2) and chlorophyll content (CHLG) were correlated with the final yield (R = 0.69 on average for the susceptible cultivar) and the final nematode population in the soil (R = 0.78 on average for the susceptible cultivar). In this paper we compare the use of visible imaging, thermography and spectrometry over two cultivars and 2 years under outdoor conditions. The three different techniques have their specific strengths in identifying BCN symptoms according to the type of cultivars and the growth stages of the sugar beet plants. Early detection of nematicide benefit and high yield predictability using visible imaging and spectrometry suggests promising applications for agricultural research and precision agriculture.

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The data shown below were collected from the profiles of 9 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 18%
Researcher 9 15%
Student > Ph. D. Student 7 12%
Student > Postgraduate 4 7%
Other 4 7%
Other 8 13%
Unknown 17 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 47%
Engineering 5 8%
Computer Science 3 5%
Business, Management and Accounting 1 2%
Linguistics 1 2%
Other 3 5%
Unknown 19 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 September 2017.
All research outputs
#6,867,768
of 25,703,943 outputs
Outputs from Plant Methods
#398
of 1,284 outputs
Outputs of similar age
#98,276
of 324,459 outputs
Outputs of similar age from Plant Methods
#9
of 23 outputs
Altmetric has tracked 25,703,943 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,284 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 68% 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 324,459 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 69% of its contemporaries.
We're also able to compare this research output to 23 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 60% of its contemporaries.