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Unfrazzled by Fizziness: Identification of Beers Using Attenuated Total Reflectance Mid-infrared Spectroscopy and Multivariate Analysis

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Abstract

Mid-infrared (MIR) spectroscopy coupled with attenuated total reflectance (ATR) was used to analyse a series of different beer types in order to confirm their identity (e.g. ale vs lager, commercial vs craft beer). Multivariate data analyses such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse and to discriminate the beer samples analysed based on their infrared spectra. Correct classification rates of 100% were achieved in order to differentiate between ale and lager and also between commercial and craft beer sample types, respectively. Overall, the results of this study demonstrated the capability of MIR spectroscopy combined with PLS-DA to classify beer samples according to style (ale vs lager) and production (commercial vs craft). Furthermore, dissolved gases in the beer products were proven not to interfere as overlapping artefacts in the analysis. The benefits of using MIR-ATR for rapid and detailed analysis coupled with multivariate analysis can be considered a valuable tool for researchers and brewers interested in quality control, traceability and food adulteration. The novelty of this study is potentially far reaching, whereby customs and agencies can utilise these methods to mitigate beverage fraud.

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Funding

The study was funded by Central Queensland University.

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Authors and Affiliations

  1. The Agri-Chemistry Group, School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, Queensland, 4701, Australia

    Russell Gordon, James Chapman, Aoife Power, Shaneel Chandra, Jessica Roberts & Daniel Cozzolino

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  1. Russell Gordon
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  2. James Chapman
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  3. Aoife Power
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  4. Shaneel Chandra
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  5. Jessica Roberts
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  6. Daniel Cozzolino
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Correspondence to Daniel Cozzolino.

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Conflict of Interest

Russell Gordon declares that he has no conflict of interest. James Chapman declares that he has no conflict of interest. Aoife Power declares that she has no conflict of interest. Shaneel Chandra declares that he has no conflict of interest. Jessica Roberts declares that he has no conflict of interest. Daniel Cozzolino declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Gordon, R., Chapman, J., Power, A. et al. Unfrazzled by Fizziness: Identification of Beers Using Attenuated Total Reflectance Mid-infrared Spectroscopy and Multivariate Analysis. Food Anal. Methods 11, 2360–2367 (2018). https://doi.org/10.1007/s12161-018-1225-y

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  • DOI: https://doi.org/10.1007/s12161-018-1225-y

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