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Characterizing bourbon whiskey via the combination of LC-MS and GC-MS based molecular fingerprinting
Rui Xu1, Li Chen1, Huan Zhang2
1Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, United States; Human Nutrition Program, Department of Human Sciences, The Ohio State University, Columbus, OH 43210, United States.
Abstract:
To discover molecular fingerprints that vary by bourbon's age or color, 121 commercial bourbon samples were analyzed using both gas chromatography and liquid chromatography combined with mass spectrometry. In total, 81 non-volatile compounds and 102 volatile compounds were identified. A subset of samples containing age information was divided into training (n = 70) and testing (n = 12) groups to build and validate the Partial Least Square - Discriminant Analysis models for age-based classification. After internal and external validation, our models showed that 8 molecular markers unitedly provided up to 100% accuracy of prediction in distinguishing unaged (0 years), younger (0-4 years), and older (>4 years) bourbons. Additional efforts were also made to detect molecular signatures that contributed to the color differences in bourbon. Overall, our study provided a powerful strategy for the confident identification of high-quality products and robust evaluation of their commercial values.
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