Evidence map›Paper›PMID 30929085›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2019

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers.

Olivier Fernandez, Maria Urrutia, Thierry Berton, Stéphane Bernillon, Catherine Deborde, Daniel Jacob, Mickaël Maucourt, Pierre Maury, Harold Duruflé, Yves Gibon and 2 more

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Sunflower (Antioxidants (Basel, Switzerland) · 2020
    Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Olivier FernandezUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France. olivier.fernandez@univ-reims.fr.ORCID 0000-0002-4432-976X
Maria UrrutiaUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Thierry BertonUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Stéphane BernillonUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Catherine DebordeUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Daniel JacobUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Mickaël MaucourtUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Pierre MauryUMR LIPM, INRA, CNRS, Université de Toulouse, 31326, Castanet-Tolosan, France.
Harold DurufléUMR LIPM, INRA, CNRS, Université de Toulouse, 31326, Castanet-Tolosan, France.
Yves GibonUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Nicolas B LangladeUMR LIPM, INRA, CNRS, Université de Toulouse, 31326, Castanet-Tolosan, France.
Annick MoingUMR1332 Biologie du Fruit et Pathologie, INRA, Centre INRA de Bordeaux, 71 av Edouard Bourlaux, 33140, Villenave d'Ornon, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPlant and crop metabolomic analyses may be used to study metabolism across genetic and environmental diversity. Complementary analytical strategies are useful for investigating metabolic changes and searching for biomarkers of response or performance. METHODS AND

objectivesThe experimental material consisted in eight sunflower lines with two line status, four restorers (R, used as males) and four maintainers (B, corresponding to females) routinely used for sunflower hybrid varietal production, respectively to complement or maintain the cytoplasmic male sterility PET1. These lines were either irrigated at full soil capacity (WW) or submitted to drought stress (DS). Our aim was to combine targeted and non-targeted metabolomics to characterize sunflower leaf composition in order to investigate the effect of line status genotypes and environmental conditions and to find the best and smallest set of biomarkers for line status and stress response using a custom-made process of variables selection.

resultsFive hundred and eighty-eight metabolic variables were measured by using complementary analytical methods such as

conclusionThis study underlines the potential of metabolic markers for discriminating genotype groups and environmental conditions. Their potential use for prediction is discussed.

Indexed as

BiomarkersDroughtsGene Expression Regulation, PlantGenotypeHelianthusMetabolomicsPlant LeavesStress, PhysiologicalBiomarkersMaintainer–restorer linesMetabolic markersMetabolomicsSunflowerWater stress

Identifiers

PMID30929085
PMCPMC6441456

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.