首页> 外文期刊>Analytica chimica acta >Novel combination of non-aqueous capillary electrophoresis and multivariate curve resolution-alternating least squares to determine phenolic acids in virgin olive oil
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Novel combination of non-aqueous capillary electrophoresis and multivariate curve resolution-alternating least squares to determine phenolic acids in virgin olive oil

机译:非水毛细管电泳和多元曲线分辨率(交替最小二乘法)的新颖组合,用于测定初榨橄榄油中的酚酸

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摘要

This paper presents the development of a non-aqueous capillary electrophoresis method coupled to UV detection combined with multivariate curve resolution-alternating least-squares (MCR-ALS) to carry out the resolution and quantitation of a mixture of six phenolic acids in virgin olive oil samples, p-Coumaric, caffeic, ferulic, 3,4-dihydroxyphenylacetic, vanillic and 4-hydroxyphenilacetic acids have been the analytes under study. All of them present different absorption spectra and overlapped time profiles with the olive oil matrix interferences and between them. The modeling strategy involves the building of a single MCR-ALS model composed of matrices augmented in the temporal mode, namely spectra remain invariant while time profiles may change from sample to sample. So MCR-ALS was used to cope with the coeluting interferences, on accounting the second order advantage inherent to this algorithm which, in addition, is able to handle data sets deviating from trilinearity, like the data herein analyzed. The method was firstly applied to resolve standard mixtures of the analytes randomly prepared in 1-propanol and, secondly, in real virgin olive oil samples, getting recovery values near to 100% in all cases. The importance and novelty of this methodology relies on the combination of non-aqueous capillary electrophoresis second-order data and MCR-ALS algorithm which allows performing the resolution of these compounds simplifying the previous sample pretreatment stages.
机译:本文介绍了结合UV检测和多元曲线分辨率交替最小二乘(MCR-ALS)进行非水毛细管电泳方法的开发,以进行纯橄榄油中六种酚酸混合物的分离和定量分析样品中,对香豆酸,咖啡酸,阿魏酸,3,4-二羟基苯乙酸,香草酸和4-羟基苯乙酸是研究对象。它们都呈现出不同的吸收光谱,并且在橄榄油基质之间以及它们之间存在重叠的时间分布。建模策略涉及建立由以时间模式增强的矩阵组成的单个MCR-ALS模型,即频谱保持不变,而时间轮廓可能因样本而异。因此,考虑到该算法固有的二阶优势,MCR-ALS用于应对共洗脱干扰,此外,该算法还能够处理偏离三线性的数据集,如本文分析的数据。该方法首先用于解析在1-丙醇中随机制备的分析物的标准混合物,其次在真实的橄榄油样品中,所有情况下的回收率均接近100%。该方法的重要性和新颖性取决于非水毛细管电泳二级数据和MCR-ALS算法的结合,该算法可对这些化合物进行分离,从而简化了先前的样品预处理步骤。

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