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关联约束多元曲线分辨交替最小二乘法在利用近红外和紫外可见光谱数据测定生物柴油混合物中目标化合物的应用

Application of correlation constrained multivariate curve resolution alternating least-squares methods for determination of compounds of interest in biodiesel blends using NIR and UV-visible spectroscopic data.

作者信息

de Oliveira Rodrigo Rocha, de Lima Kássio Michell Gomes, Tauler Romà, de Juan Anna

机构信息

Grupo de Pesquisa em Quimiometria Aplicada, Instituto de Química, Universidade Federal do Rio Grande do Norte, Av. Senador Salgado Filho 3000, Natal, CEP 59078-970, Brazil; Chemometrics Group, Department of Analytical Chemistry, Universitat de Barcelona, Diagonal 645, Barcelona 08028, Spain.

Grupo de Pesquisa em Quimiometria Aplicada, Instituto de Química, Universidade Federal do Rio Grande do Norte, Av. Senador Salgado Filho 3000, Natal, CEP 59078-970, Brazil.

出版信息

Talanta. 2014 Jul;125:233-41. doi: 10.1016/j.talanta.2014.02.073. Epub 2014 Mar 7.

Abstract

This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein.

摘要

本研究描述了一种具有相关性约束的多元曲线分辨交替最小二乘法(MCR-ALS)变体的两种应用。第一种应用描述了使用MCR-ALS通过近红外(NIR)光谱数据测定生物柴油混合物中的生物柴油浓度。在第二种应用中,所提出的方法能够使用紫外-可见光谱法测定来自不同植物来源的生物柴油混合物中存在的合成抗氧化剂N,N'-二仲丁基对苯二胺(PDA)。为了比较在这两种应用中开发的模型的定量性能,计算了成熟的多元回归算法偏最小二乘法(PLS)。相关性约束已被调整以处理由于老化效应导致的批次间基质效应的存在,在第一种应用中,当使用不同组的样品建立校准模型时可能会出现这种情况。探索了不同的数据集配置和相关性约束的不同应用模式,并给出了应对不同类型分析问题的指导方针,例如生物柴油样品之间基质效应的校正,在第一种应用中,MCR-ALS的表现优于PLS,将预测相对误差RE(%)从9.82%降低到4.85%;或者测定具有重叠弱光谱信号的微量化合物,与PLS(RE(%)=1.99%)相比,MCR-ALS在预测PDA时给出的相对误差更高(RE(%)=3.16%),但具有恢复分析物和干扰物相关纯光谱轮廓的优势。所得结果表明,具有相关性约束的MCR-ALS方法有潜力适用于与生物柴油混合物及其所含添加化合物测定相关的各种数据集配置和分析问题。

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