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Fortune telling: metabolic markers of plant performance

Overview of attention for article published in Metabolomics, September 2016
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155 Mendeley
Title
Fortune telling: metabolic markers of plant performance
Published in
Metabolomics, September 2016
DOI 10.1007/s11306-016-1099-1
Pubmed ID
Authors

Olivier Fernandez, Maria Urrutia, Stéphane Bernillon, Catherine Giauffret, François Tardieu, Jacques Le Gouis, Nicolas Langlade, Alain Charcosset, Annick Moing, Yves Gibon

Abstract

In the last decade, metabolomics has emerged as a powerful diagnostic and predictive tool in many branches of science. Researchers in microbes, animal, food, medical and plant science have generated a large number of targeted or non-targeted metabolic profiles by using a vast array of analytical methods (GC-MS, LC-MS, (1)H-NMR….). Comprehensive analysis of such profiles using adapted statistical methods and modeling has opened up the possibility of using single or combinations of metabolites as markers. Metabolic markers have been proposed as proxy, diagnostic or predictors of key traits in a range of model species and accurate predictions of disease outbreak frequency, developmental stages, food sensory evaluation and crop yield have been obtained. (i) To provide a definition of plant performance and metabolic markers, (ii) to highlight recent key applications involving metabolic markers as tools for monitoring or predicting plant performance, and (iii) to propose a workable and cost-efficient pipeline to generate and use metabolic markers with a special focus on plant breeding. Using examples in other models and domains, the review proposes that metabolic markers are tending to complement and possibly replace traditional molecular markers in plant science as efficient estimators of performance.

X Demographics

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The data shown below were collected from the profiles of 4 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 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 155 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 22%
Researcher 28 18%
Student > Master 13 8%
Student > Doctoral Student 11 7%
Other 9 6%
Other 29 19%
Unknown 31 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 70 45%
Biochemistry, Genetics and Molecular Biology 16 10%
Engineering 6 4%
Environmental Science 3 2%
Computer Science 2 1%
Other 12 8%
Unknown 46 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 07 June 2022.
All research outputs
#14,275,152
of 22,893,031 outputs
Outputs from Metabolomics
#757
of 1,296 outputs
Outputs of similar age
#182,785
of 321,173 outputs
Outputs of similar age from Metabolomics
#20
of 38 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,296 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 36th percentile – i.e., 36% 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 321,173 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.