Department of Chemistry, Faculty of Sciences, Persian Gulf University, Bushehr 75169, Iran.
J Agric Food Chem. 2013 Jul 17;61(28):6832-40. doi: 10.1021/jf402186y. Epub 2013 Jul 3.
A multicomponent analysis method for the simultaneous spectrophotometric determination of the Cd(2+), Cu(2+), and Zn(2+) based on complex formation with dimethyl-spiro[isobenzofurane-1,6'-pyrorolo[2,3-d]pyrimidine]-2',3,4,5'(1'H,3'H,7'H)tetraone using wavelet transformation-feed forward neural network is proposed. The analytical data showed that metal to ligand ratios in all metal complexes was 1:1. The absorption spectra were evaluated with respect to synthetic ligand concentration and pH. It was found that, at pH 6.7, the complexation reactions were completed. Spectral data were reduced using continuous wavelet transformation (CWT) and subjected to artificial neural networks. The presence of nonlinearities was confirmed by a partial response plot. The structures of the CWT-feed forward neural networks (WT-FFNN) were simplified using the corresponding wavelet coefficients of mother wavelets. Once the optimal wavelet coefficients are selected, different ANN models can be employed for the calculation of the final calibration model. The proposed methods were successfully applied to the simultaneous determination of Cd(2+), Cu(2+), and Zn(2+) in rice, dill, tomato, and lettuce samples.
基于二甲亚砜-螺环[异苯并呋喃-1,6'-吡咯并[2,3-d]嘧啶]-2',3,4,5'(1'H,3'H,7'H)四酮与 Cd(2+)、Cu(2+)和 Zn(2+)形成配合物的多组分分析方法,采用小波变换-前馈神经网络同时分光光度法测定。分析数据表明,所有金属配合物中金属与配体的比例均为 1:1。在合成配体浓度和 pH 值方面评估了吸收光谱。结果发现,在 pH 6.7 时,完成了络合反应。使用连续小波变换(CWT)对光谱数据进行了简化,并应用人工神经网络进行了处理。通过部分响应图证实了存在非线性关系。通过使用母波的相应小波系数简化了 CWT-前馈神经网络(WT-FFNN)的结构。一旦选择了最佳的小波系数,就可以使用不同的 ANN 模型来计算最终的校准模型。该方法成功应用于大米、莳萝、番茄和生菜样品中 Cd(2+)、Cu(2+)和 Zn(2+)的同时测定。