Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Ave. Fuentenueva s/n, E-18071 Granada, Spain.
Food Chem. 2013 Dec 15;141(4):3492-503. doi: 10.1016/j.foodchem.2013.06.007. Epub 2013 Jun 12.
Herein we present the development of a powerful CE-UV method able to detect and quantify an important number of phenolic acids in 13 varieties of avocado fruits at 2 ripening stages. All the variables involved in CE separation were exhaustively optimized and the best results were obtained with a capillary of 50 μm i.d. × 50 cm effective length, sodium tetraborate 40 mM at a pH of 9.4, 30 kV, 25 °C, 10s of hydrodynamic injection (0.5 psi) and UV detection at 254 nm. This optimal methodology was fully validated and then applied to different avocado samples. The number of phenolic acids determined varied from 8 to 14 compounds; in general, they were in concentrations ranging from 0.13 ppm to 3.82 ppm, except p-coumaric, benzoic and protocatechuic acids, which were found at higher concentrations. Principal component analysis (PCA) was applied to highlight the differences between varieties and ripening degrees, looking for the most influential analytes.
本文介绍了一种强大的 CE-UV 方法的发展，该方法能够在 2 个成熟阶段检测和定量分析 13 种鳄梨果实中的多种酚酸。CE 分离中涉及的所有变量都进行了详尽的优化，内径为 50μm×50cm 有效长度的毛细管、40mM 硼酸钠在 pH 值为 9.4、30kV、25°C、10s 的水力进样（0.5psi）和 254nm 处的紫外检测可获得最佳结果。该最佳方法经过充分验证后，应用于不同的鳄梨样品。所测定的酚酸数量从 8 到 14 种化合物不等；一般来说，它们的浓度范围从 0.13ppm 到 3.82ppm，除了 p-香豆酸、苯甲酸和原儿茶酸，它们的浓度较高。主成分分析（PCA）用于突出品种和成熟度之间的差异，寻找最有影响力的分析物。
