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High-Throughput Plant Phenotyping for Developing Novel Biostimulants: From Lab to Field or From Field to Lab?

Overview of attention for article published in Frontiers in Plant Science, August 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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21 X users
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270 Mendeley
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Title
High-Throughput Plant Phenotyping for Developing Novel Biostimulants: From Lab to Field or From Field to Lab?
Published in
Frontiers in Plant Science, August 2018
DOI 10.3389/fpls.2018.01197
Pubmed ID
Authors

Youssef Rouphael, Lukáš Spíchal, Klára Panzarová, Raffaele Casa, Giuseppe Colla

Abstract

Plant biostimulants which include bioactive substances (humic acids, protein hydrolysates and seaweed extracts) and microorganisms (mycorrhizal fungi and plant growth promoting rhizobacteria of strains belonging to the genera Azospirillum, Azotobacter, and Rhizobium spp.) are gaining prominence in agricultural systems because of their potential for improving nutrient use efficiency, tolerance to abiotic stressors, and crop quality. Highly accurate non-destructive phenotyping techniques have attracted the interest of scientists and the biostimulant industry as an efficient means for elucidating the mode of biostimulant activity. High-throughput phenotyping technologies successfully employed in plant breeding and precision agriculture, could prove extremely useful in unraveling biostimulant-mediated modulation of key quantitative traits and would also facilitate the screening process for development of effective biostimulant products in controlled environments and field conditions. This perspective article provides an innovative discussion on how small, medium, and large high-throughput phenotyping platforms can accelerate efforts for screening numerous biostimulants and understanding their mode of action thanks to pioneering sensor and image-based phenotyping techniques. Potentiality and constraints of small-, medium-, and large-scale screening platforms are also discussed. Finally, the perspective addresses two screening approaches, "lab to field" and "field to lab," used, respectively, by small/medium and large companies for developing novel and effective second generation biostimulant products.

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 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 270 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 270 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 16%
Student > Ph. D. Student 32 12%
Student > Master 31 11%
Student > Bachelor 22 8%
Student > Doctoral Student 18 7%
Other 51 19%
Unknown 73 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 115 43%
Biochemistry, Genetics and Molecular Biology 19 7%
Engineering 10 4%
Environmental Science 6 2%
Social Sciences 4 1%
Other 21 8%
Unknown 95 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 19 September 2018.
All research outputs
#2,627,406
of 23,100,534 outputs
Outputs from Frontiers in Plant Science
#1,201
of 20,728 outputs
Outputs of similar age
#54,892
of 331,095 outputs
Outputs of similar age from Frontiers in Plant Science
#44
of 470 outputs
Altmetric has tracked 23,100,534 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 20,728 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 94% 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 331,095 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 470 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 90% of its contemporaries.