Evidence map›Paper›PMID 40361703›Full record

ArticleFoods (Basel, Switzerland)2025

Weiss or Wit: Chemical Profiling of Wheat Beers via NMR-Based Metabolomics.

Plamen Chorbadzhiev, Dessislava Gerginova, Svetlana Simova

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Plamen ChorbadzhievBulgarian NMR Centre, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 9, 1113 Sofia, Bulgaria.ORCID 0009-0000-3906-9281
Dessislava GerginovaBulgarian NMR Centre, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 9, 1113 Sofia, Bulgaria.ORCID 0000-0002-1194-0925
Svetlana SimovaBulgarian NMR Centre, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 9, 1113 Sofia, Bulgaria.ORCID 0000-0002-9565-3850

Funding

Bulgarian Science Fund KP-06-М79/2
6 · The paper itself

Abstract

Wheat beers, including Witbier, Hefeweizen, and Weizenbock, are known for their unique sensory profiles, which are shaped by the combination of ingredients, fermentation conditions, and brewing methods. In this study, we used nuclear magnetic resonance (NMR) spectroscopy to explore the metabolomic signatures of various wheat beer styles and substyles. By analyzing 39 beer samples from 17 countries, we identified and quantified 50 metabolites, ranging from alcohols and saccharides to amino acids and organic acids. Ethanol and maltodextrin were the most abundant compounds, while higher contents of alcohols and organic acids played a key role in flavor variation. Through orthogonal partial least squares discriminant analysis (OPLS-DA), we achieved an impressive 97.44% accuracy in distinguishing between Witbier, Hefeweizen, and Weizenbock based on their metabolic profiles. The analysis also revealed notable compositional differences between craft and commercial beers, with craft beers showing higher concentrations of alcohols and amino acids. These results underscore the significant impact of raw materials, fermentation parameters, and brewing techniques on the chemistry of wheat beer. Furthermore, this study highlights the potential of NMR spectroscopy as a powerful tool for beer authentication and quality control.

Indexed as

chemometricscraft and commercial beerNMR metabolomicswheat beer

Identifiers

PMID40361703
PMCPMC12072173

What OpenQuestion holds

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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.