Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain.
Research Institute in Food Nutrition and Food Safety, University of Barcelona, Barcelona, Spain.
J Sci Food Agric. 2021 Jan 15;101(1):65-73. doi: 10.1002/jsfa.10615. Epub 2020 Jul 24.
Coffee is one of the most popular beverages around the world, consumed as an infusion of ground roasting coffee beans with a characteristic taste and flavor. Two main varieties, Arabica and Robusta, are produced worldwide. Furthermore, interest of consumers in quality attributes related to coffee production region and varieties is increasing. Thus, it is necessary to encourage the development of simple methodologies to authenticate and guarantee the coffee origin, variety and roasting degree, aiming to prevent fraudulent practices.
C18 high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprints obtained after brewing coffees without any sample treatment other than filtration (i.e. considerably reducing sample manipulation) were employed as sample chemical descriptors for subsequent coffee characterization and classification by principal component analysis (PCA) and partial least squares regression-discriminant analysis (PLS-DA). PLS-DA showed good classification capabilities regarding coffee origin, variety and roasting degree when employing HPLC-FLD fingerprints, although overlapping occurred for some sample groups. However, the discrimination power increased when selecting HPLC-FLD fingerprinting segments richer in discriminant features, which were deduced from PLS-DA loading plots. In this case, excellent separation was observed and 100% classification rates for both PLS-DA calibrations and predictions were obtained (all samples were correctly classified within their corresponding groups).
HPLC-FLD fingerprinting segments were3 found to be suitable chemical descriptors for discriminating the origin (country of production), variety (Arabica and Robusta) and roasting degree of coffee. Therefore, HPLC-FLD fingerprinting can be proposed as a feasible, simple and cheap methodology to address coffee authentication, especially for developing coffee production countries. © 2020 Society of Chemical Industry.
咖啡是全球最受欢迎的饮料之一,是将烘焙咖啡豆磨碎后冲泡而成,具有独特的口感和风味。全球主要生产两种咖啡,即阿拉比卡(Arabica)和罗布斯塔(Robusta)。此外,消费者对与咖啡生产地区和品种相关的质量属性的兴趣日益增加。因此,有必要鼓励开发简单的方法来对咖啡的原产地、品种和烘焙程度进行鉴定和保证,以防止欺诈行为。
通过对未经任何处理(即大大减少了样品处理)仅经过过滤的咖啡进行 C18 高效液相色谱法(HPLC)-荧光检测(FLD)指纹分析,将所得 HPLC-FLD 指纹图谱用作样品化学描述符,用于后续的主成分分析(PCA)和偏最小二乘回归判别分析(PLS-DA)咖啡特征分析和分类。当使用 HPLC-FLD 指纹图谱时,PLS-DA 显示出对咖啡原产地、品种和烘焙程度的良好分类能力,尽管某些样品组存在重叠。然而,当选择更富判别特征的 HPLC-FLD 指纹图谱段时,判别能力增加,这些特征是从 PLS-DA 载荷图中推断出来的。在这种情况下,观察到了极好的分离效果,并且获得了 100%的 PLS-DA 校准和预测分类率(所有样品均正确地分类到其相应的组中)。
发现 HPLC-FLD 指纹图谱段适合用于区分咖啡的原产地(生产国)、品种(阿拉比卡和罗布斯塔)和烘焙程度。因此,HPLC-FLD 指纹图谱可作为一种可行、简单且廉价的方法来解决咖啡鉴定问题,特别是对于发展中国家的咖啡生产。 © 2020 英国化学学会。