Chamsaz M, Safavi A, Fadaee J
Department of Chemistry, Faculty of Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
Anal Chim Acta. 2007 Nov 12;603(2):140-6. doi: 10.1016/j.aca.2007.09.006. Epub 2007 Sep 14.
The kinetic methodology based on the difference of reaction rates, is based on the reaction between a common oxidizing agents such as tris(1,10-phenanthroline) and iron(III) complex (ferriin, [Fe (phen)3]3+) in the presence of citrate and spectrophotometrically, monitoring the changes of absorbance at the maximum wavelength of 511 nm. Experimental conditions such as pH, reagents and citrate concentrations were optimized, and the data obtained from the experiments were processed by several chemometric approaches, such as artificial neural network (ANN) and partial least squares (PLS). A set of synthetic mixtures of carbidopa (CD), levodopa (LD) and methyldopa (MD) was evaluated and the results obtained by the applications of these chemometric approaches were discussed and compared. It was found that the back propagation artificial neural network (BP-ANN) method afforded better precision relatively than those of radial basis function artificial neural networks (RBF-ANN) and PLS. The proposed method was also applied satisfactorily to the determination of carbidopa, levodopa and methyldopa in real samples.
基于反应速率差异的动力学方法,是基于在柠檬酸盐存在下,常见氧化剂如三(1,10 - 菲咯啉)与铁(III)配合物(亚铁菲咯啉,[Fe (phen)3]3+)之间的反应,并通过分光光度法监测在511 nm最大波长处吸光度的变化。对pH、试剂和柠檬酸盐浓度等实验条件进行了优化,从实验中获得的数据通过几种化学计量学方法进行处理,如人工神经网络(ANN)和偏最小二乘法(PLS)。对一组卡比多巴(CD)、左旋多巴(LD)和甲基多巴(MD)的合成混合物进行了评估,并对应用这些化学计量学方法获得的结果进行了讨论和比较。发现反向传播人工神经网络(BP - ANN)方法相对径向基函数人工神经网络(RBF - ANN)和PLS具有更高的精度。所提出的方法也令人满意地应用于实际样品中卡比多巴、左旋多巴和甲基多巴的测定。