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

作者：Gordon Russell; Chapman James; Power Aoife; Chandra Shaneel; Roberts Jessica; Cozzolino Daniel^*

来源：Food Analytical Methods, 2018, 11(9): 2360-2367.

DOI：10.1007/s12161-018-1225-y

• Beer
• Mid-infrared
• ATR
• Partial least squares
• Classification

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.

• 出版日期2018-9