Department of Electrical Engineering & Electronics, University of Liverpool, Liverpool, UK.
Department of Biostatistics, University of Liverpool, Liverpool, UK.
Sci Rep. 2019 May 29;9(1):7994. doi: 10.1038/s41598-019-44456-0.
Whisky, as a high value product, is often adulterated, with adverse economic effects for both producers and consumers as well as potential public health impacts. Here we report the use of DAPCI-MS to analyse and chemically profile both genuine and counterfeit whisky samples employing a novel 'direct from the bottle' methodology with zero sample pre-treatment, zero solvent requirement and almost no sample usage. 25 samples have been analysed from a collection of blended Scotch whisky (n = 15) and known counterfeit whisky products (n = 10). Principal component analysis has been applied to dimensionally reduce the data and discriminate between sample groups. Additional chemometric modelling, a partial least squares regression, has correctly classified samples with 92% success rate. DAPCI-MS shows promise for simple, fast and accurate counterfeit detection with potential for generic aroma profiling and process quality monitoring applications.
威士忌作为一种高价值产品,经常被掺假,这对生产者和消费者都有不利的经济影响,也可能对公众健康产生影响。在这里,我们报告了使用 DAPCI-MS 分析和化学分析真正和假冒威士忌样品,采用了一种新颖的“直接从瓶子”的方法,无需样品预处理、零溶剂要求和几乎不使用样品。我们对来自混合苏格兰威士忌(n=15)和已知假冒威士忌产品(n=10)的收藏进行了 25 个样品的分析。主成分分析已被应用于降维数据并区分样品组。额外的化学计量建模,部分最小二乘回归,正确地对 92%的成功率进行了分类。DAPCI-MS 显示出在简单、快速和准确的假冒检测方面的前景,具有潜在的通用香气分析和过程质量监测应用。