Evidence map›Paper›PMID 34435244›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2021

Systematic selection of competing metabolomics methods in a metabolite-sensory relationship study.

Naser Davarzani, Carmen Diez-Simon, Justus L Großmann, Doris M Jacobs, Rudi van Doorn, Marco A van den Berg, Age K Smilde, Roland Mumm, Robert D Hall, Johan A Westerhuis

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Naser Davarzani *Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands.
Carmen Diez-Simon *Laboratory of Plant Physiology, Wageningen University and Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, The Netherlands.
Justus L GroßmannSwammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands.
Doris M JacobsUnilever Foods Innovation Centre, Bronland 14, Wageningen, 6708 WH, The Netherlands.
Rudi van DoornDSM Food Specialties, Biotech Campus Delft, Alexander Fleminglaan 1, Delft, 2613 AX, The Netherlands.
Marco A van den BergDSM Food Specialties, Biotech Campus Delft, Alexander Fleminglaan 1, Delft, 2613 AX, The Netherlands.
Age K SmildeSwammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands.
Roland MummNetherlands Metabolomics Centre, Einsteinweg 55, Leiden, 2333 CC, The Netherlands.
Robert D HallLaboratory of Plant Physiology, Wageningen University and Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, The Netherlands.
Johan A WesterhuisSwammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands. j.a.westerhuis@uva.nl.ORCID 0000-0002-6747-9779

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe relationship between the chemical composition of food products and their sensory profile is a complex association confronting many challenges. However, new untargeted methodologies are helping correlate metabolites with sensory characteristics in a simpler manner. Nevertheless, in the pilot phase of a project, where only a small set of products are used to explore the relationships, choices have to be made about the most appropriate untargeted metabolomics methodology.

objectiveTo provide a framework for selecting a metabolite-sensory methodology based on: the quality of measurements, the relevance of the detected metabolites in terms of distinguishing between products or in terms of whether they can be related to the sensory attributes of the products.

methodsIn this paper we introduce a systematic approach to explore all these different aspects driving the choice for the most appropriate metabolomics method.

resultsAs an example we have used a tomato soup project where the choice between two sampling methods (SPME and SBSE) had to be made. The results are not always consistently pointing to the same method as being the best. SPME was able to detect metabolites with a better precision, SBSE seemed to be able to provide a better distinction between the soups.

conclusionThe three levels of comparison provide information on how the methods could perform in a follow up study and will help the researcher to make a final selection for the most appropriate method based on their strengths and weaknesses.

Indexed as

MetabolomicsFollow-Up StudiesMetabolite-sensory relationshipMetabolomicsSensory attributes

Identifiers

PMID34435244
PMCPMC8387272

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Registered trials

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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.