Title

What's in this Drink? Classification and Adulterant Detection in Irish Whiskey Samples Using Near Infrared Spectroscopy Combined with Chemometrics

Author ORCID Identifier

0000-0002-6984-2842

Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Analytical chemistry, Food and beverages, Forensic science

Publication Details

J Sci Food Agric 2021; 101: 5256–5263

Abstract

BACKGROUND: Near-infrared (NIR) spectroscopy coupled with principal component analysis (PCA) and partial least squares (PLS) regression was used to analyse a series of different Irish Whiskey samples in order to dene their spectral prole and to assess the capability of the NIR method to identify samples based on their origin and storage (e.g. distiller, method of mat- uration). The ability of NIR spectroscopy to quantify the level of potential chemical adulterants was also investigated. Samples were spiked with 0.1%, 0.5%, 1.0%, 1.5% and 2.0% v/v of each adulterant (e.g. methanol, ethyl acetate, etc.) prior to NIR analysis. RESULTS: The results of this study demonstrated the capability of NIR spectroscopy combined with PLS regression to classify the whiskey samples and to determine the level of adulteration. Moreover, the potential of NIR coupled with chemometric anal- ysis as a rapid, portable, and non-destructive screening tool for quality control, traceability, and food/beverage adulteration for customs and other regulatory agencies, to mitigate beverage fraud was illustrated. CONCLUSION: Given the non-specicity of the NIR technique, these positive preliminary results indicated that this method of analysis has the potential to be applied to identify the level of adulteration in distilled spirits. The rapid nature of the technique and lack of consumables or sample preparation required allows for a far more time and cost-effective analysis per sample.

DOI

https://doi.org/10.1002/jsfa.11174

Funder

This research received no external funding


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