SinS - Abstract

Abstract Title: Statistical differentiation of the Chinese liquor ‘Baijiu’ using SPME-GC×GC-TOFMS
Presenter Name: Mr Alan Griffiths
Co-authors:Dr Lena Dubois
Dr Sebastiano Panto
Mr Nick Jones
Company/Organisation: LECO
Country: United Kingdom

Abstract Information :

Baijiu is a traditional Chinese spirit with a complex pattern of volatile organic compounds (VOCs). The rich aroma results from the relatively complex and multilayered manufacturing process, including fermentation and various technological processing steps. In general, Baijiu can be classified according to the aroma type (e.g., strong, light, rice, sauce) which is associated with a distinct taste. Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) was used to differentiate Baijiu samples in terms of their aroma type and origin (region). In total, 10 Baijiu samples were investigated: VOCs were extracted by head-space solid phase micro-extraction (HS-SPME) followed by GC×GC-TOFMS analysis. The characteristic Baijiu profiles displayed a wide range of concentration levels, which challenge the accurate detection and identification of compounds of very low abundance using classical one-dimensional GC. In this study, we evaluate the use of comprehensive two-dimensional GC×GC-TOFMS to significantly improve the separation, detection, and therefore identification of species in Baijiu to provide a significantly higher quality and more informative characterization ability. The optimized analytical parameters allowed for a comprehensive characterization of the individual Baijiu samples, but beyond that, a non-targeted differentiative analysis to determine trends and patterns among the different Baijiu types was realized. The comparison of the aroma profiles and the data analysis was facilitated by the means of a supervised statistical analysis tool, called ChromaTOF® Tile. Group type separation according to their respective class in terms of aroma-type and origin was obtained and statistically significant differences were easily highlighted.