Pardo-Mates Naiara, Vera Alex, Barbosa Sergio, Hidalgo-Serrano Míriam, Núñez Oscar, Saurina Javier, Hernández-Cassou Santiago, Puignou Lluis
Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain.
Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), E-08921 Santa Coloma de Gramenet, Barcelona, Spain; Serra Húnter Fellow, Generalitat de Catalunya, Spain.
Food Chem. 2017 Apr 15;221:29-38. doi: 10.1016/j.foodchem.2016.10.033. Epub 2016 Oct 11.
HPLC-UV was applied to the analysis and characterization of fruit-based and fruit-processed products. A Kinetex C18 reversed-phase column was proposed under gradient elution for the determination of 17 polyphenols. Acceptable sensitivity (LODs below 0.16mg/L), and good linearity (r higher than 0.995), precision (RSD below 6.8%), and method trueness (relative errors below 11%) were obtained. Data corresponding to polyphenolic peak areas and HPLC-UV chromatographic fingerprints were then analyzed by exploratory principal component analysis (PCA) to extract information of the most significant variables contributing to characterization and classification of analyzed samples regarding the fruit of origin. HPLC-UV chromatographic data was further treated by partial least square (PLS) regression to determine the percentages of adulteration in cranberry-fruit extracts. It was found that even mixture samples containing low percentages of adulterants could be distinguished from genuine cranberry extracts. Highly satisfactory results were obtained, with overall errors in the quantification of adulterations below 4.3%.
高效液相色谱 - 紫外检测法（HPLC - UV）用于水果基及水果加工产品的分析和表征。采用Kinetex C18反相柱，在梯度洗脱条件下测定17种多酚。该方法具有可接受的灵敏度（检测限低于0.16mg/L）、良好的线性（r高于0.995）、精密度（相对标准偏差低于6.8%）和方法准确性（相对误差低于11%）。然后，通过探索性主成分分析（PCA）对多酚峰面积和HPLC - UV色谱指纹图谱数据进行分析，以提取有助于分析样品按原产水果进行表征和分类的最显著变量的信息。通过偏最小二乘法（PLS）回归进一步处理HPLC - UV色谱数据，以确定蔓越莓果实提取物中的掺假百分比。结果发现，即使是含有低百分比掺假物的混合样品也能与纯正的蔓越莓提取物区分开来。获得了高度满意的结果，掺假物定量的总体误差低于4.3%。
