Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL) , University of Almería , Agrifood Campus of International Excellence, ceiA3, E-04120 Almería , Spain.
J Agric Food Chem. 2019 Jan 30;67(4):1302-1311. doi: 10.1021/acs.jafc.8b05622. Epub 2019 Jan 22.
A comprehensive fingerprinting strategy for golden rum classification considering different categories such as fermentation barrel, raw material, and aging is provided, using a metabolomic fingerprinting approach. A nontarget fingerprinting of 30 different rums using liquid chromatography coupled to high-resolution mass spectrometry (Exactive Orbitrap mass analyzer, LC-HRMS) was applied. Principal component analysis (PCA) was used to assess the overall structure of the data and to identify potential outliers. Different chemometric analyses such as partial least-squares discriminant analysis (PLS-DA) were used. A variable importance in projection (VIP) selection method was applied to identify the most significant markers that allow group separation. Compounds related to aging and fermentation processes such as furfural derivates (e.g., hydroxymethylfurfural) and sugars (e.g., glucose, mannitol) were found as the most discriminant compounds (VIP threshold value >1.5). Suitable separation according to selected categories was achieved, and a classification ability of the models of close to 100% was achieved.
提供了一种综合的指纹图谱策略，用于考虑不同类别（如发酵桶、原料和陈酿）的金朗姆酒分类，采用代谢组指纹图谱方法。使用液质联用（Exactive Orbitrap 质量分析仪，LC-HRMS）对 30 种不同朗姆酒进行了非靶向指纹图谱分析。主成分分析（PCA）用于评估数据的整体结构，并识别潜在的异常值。采用偏最小二乘判别分析（PLS-DA）等不同的化学计量学分析方法。应用变量重要性投影（VIP）选择方法来识别允许分组分离的最显著标志物。与老化和发酵过程相关的化合物，如糠醛衍生物（如羟甲基糠醛）和糖（如葡萄糖、甘露醇），被发现是最具判别力的化合物（VIP 值>1.5）。根据选定的类别实现了合适的分离，模型的分类能力接近 100%。
