Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 May 3;14(9):1621.
doi: 10.3390/foods14091621.

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

Affiliations

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

Plamen Chorbadzhiev et al. Foods. .

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.

Keywords: NMR metabolomics; chemometrics; craft and commercial beer; wheat beer.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Comparative 1H NMR spectra of Hefeweizen (hw15, blue), Weizenbock (wb3, red), and Witbier (wt10, yellow), highlighting key metabolite signals: AA—acetic acid, Ado—adenosine, Ala—alanine, Bet—betaine, Cho—choline, CitA—citric acid, EtOH—ethanol, FoA—formic acid, FumA—fumaric acid, GABA—gamma-aminobutyric acid, GalA—gallic acid, GlycOH—glycerol, Guo—guanosine, HMF—5-hydroxymethylfurfural, iAmA—isoamyl acetate, Ino—inosine, LA—lactic acid, Md—maltodextrin, MeCHO—acetaldehyde, MelA—maleic acid, PA—pyruvic acid, SA—succinic acid, Tri—trigonelline, Trp—tryptophan, Tyr—tyrosine, 2,3BdOH—2,3-butanediol, 2PhEt—2-phenylethanol, and Urc—uracil.
Figure 2
Figure 2
OPLS-DA score plot illustrating compositional differences between the three classes: Hefeweizen (blue), Weizenbock (red), and Witbier (yellow).
Figure 3
Figure 3
Nightingale diagrams comparing metabolite levels in commercial (Comm) and craft (Craft) samples of (a) Hefeweizen and (b) Witbier.
Figure 4
Figure 4
OPLS-DA score plot illustrating significant compositional differences between Dunkelweizen (brown), Kristallweizen (purple), and Hefeweizen (blue).

References

    1. Statista, Global Beer Production 1998–2023. Benchmark International; Tampa, FL, USA: 2024.
    1. Dineley M. Barley, Malt And Ale in the Neolithic. Oxbow Books; Oxford, UK: 2004.
    1. Wang J., Liu L., Ball T., Yu L., Li Y., Xing F. Revealing a 5000-year-old beer recipe in China. Proc. Natl. Acad. Sci. USA. 2016;113:6444–6448. doi: 10.1073/pnas.1601465113. - DOI - PMC - PubMed
    1. Verberg S. The Rise and Fall of Gruit. Brew. Hist. 2018;174:46–78.
    1. Anderson H.E., Liden T., Berger B.K., Zanella D., Ho Manh L., Wang S., Schug K.A. Profiling of Contemporary Beer Styles Using Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry, Multivariate Analysis, and Machine Learning Techniques. Anal. Chim. Acta. 2021;1172:338668. doi: 10.1016/j.aca.2021.338668. - DOI - PubMed

LinkOut - more resources