Evidence map›Paper›PMID 34357339›Full record

ReviewMetabolites2021

Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview.

Morena M Tinte, Kekeletso H Chele, Justin J J van der Hooft, Fidele Tugizimana

Abstract readReview
In one paragraph

Review in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  16. Providing metabolomics education and training: pedagogy and considerations.Metabolomics : Official journal of the Metabolomic Society · 2022
    Review
  17. Article
  18. 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

4 authors.

Morena M TinteDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.
Kekeletso H CheleDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.
Justin J J van der HooftBioinformatics Group, Wageningen University, 6708 PB Wageningen, The Netherlands.ORCID 0000-0002-9340-5511
Fidele TugizimanaDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.ORCID 0000-0001-8172-6599

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.

Indexed as

4IR technologiesabiotic stressautomationmachine learningmetabolomics

Identifiers

PMID34357339
PMCPMC8305945

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.