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Integrative field scale phenotyping for investigating metabolic components of water stress within a vineyard

Overview of attention for article published in Plant Methods, October 2017
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Title
Integrative field scale phenotyping for investigating metabolic components of water stress within a vineyard
Published in
Plant Methods, October 2017
DOI 10.1186/s13007-017-0241-z
Pubmed ID
Authors

Jorge Gago, Alisdair R. Fernie, Zoran Nikoloski, Takayuki Tohge, Sebastiá Martorell, José Mariano Escalona, Miquel Ribas-Carbó, Jaume Flexas, Hipólito Medrano

Abstract

There is currently a high requirement for field phenotyping methodologies/technologies to determine quantitative traits related to crop yield and plant stress responses under field conditions. We employed an unmanned aerial vehicle equipped with a thermal camera as a high-throughput phenotyping platform to obtain canopy level data of the vines under three irrigation treatments. High-resolution imagery (< 2.5 cm/pixel) was employed to estimate the canopy conductance (gc ) via the leaf energy balance model. In parallel, physiological stress measurements at leaf and stem level as well as leaf sampling for primary and secondary metabolome analysis were performed. Aerial gc correlated significantly with leaf stomatal conductance (gs ) and stem sap flow, benchmarking the quality of our remote sensing technique. Metabolome profiles were subsequently linked with gc and gs via partial least square modelling. By this approach malate and flavonols, which have previously been implicated to play a role in stomatal function under controlled greenhouse conditions within model species, were demonstrated to also be relevant in field conditions. We propose an integrative methodology combining metabolomics, organ-level physiology and UAV-based remote sensing of the whole canopy responses to water stress within a vineyard. Finally, we discuss the general utility of this integrative methodology for broad field phenotyping.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 19%
Student > Master 15 15%
Researcher 14 14%
Student > Doctoral Student 8 8%
Professor 7 7%
Other 19 19%
Unknown 18 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 39%
Biochemistry, Genetics and Molecular Biology 11 11%
Engineering 4 4%
Environmental Science 4 4%
Computer Science 2 2%
Other 11 11%
Unknown 29 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 31 October 2017.
All research outputs
#20,451,228
of 23,007,053 outputs
Outputs from Plant Methods
#1,055
of 1,088 outputs
Outputs of similar age
#286,309
of 328,606 outputs
Outputs of similar age from Plant Methods
#39
of 39 outputs
Altmetric has tracked 23,007,053 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% 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 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.