Resolution by polarographic techniques of the ternary mixture of captan, captafol and folpet by using PLS calibration and artificial neuronal networks

A. Guiberteau , T. Galeano , N. Mora , F. Salinas , J.M. Ortı́z , J.C. Viré
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引用次数: 13

Abstract

The simultaneous polarographic determination of the ternary mixture of captan-captafol and folpet is studied. The polarographic signals of these compounds in their mixture show a high overlapping. For this reason different chemometric methods such as PLS, PCR and artificial neuronal network (ANN) have been utilized for the simultaneous determination of these compounds in mixtures. The calibration model is built from solutions containing river water of known pesticide concentrations and the signals obtained by Sampled DC and DPP (differential pulse polarography) have been used. The analysis of both synthetic and real samples (river water) has been carried out by PLS with satisfactory results in most cases. It is possible to determine 0.25 ppm of each pesticide in river water samples after a preconcentration step by extraction into diethyl ether. ANN has also been applied to improve the results obtained by the PLS tool when the sampled DC current is recorded or when liquid–solid extraction with C18 cartridges is performed.

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利用PLS校准和人工神经网络,用极谱技术对队长、队长醇和队长醇的三元混合物进行分辨
研究了用极谱法同时测定卡普-卡普醇和卡普醚三元混合物的方法。这些化合物在其混合物中的极谱信号显示出高度重叠。因此,不同的化学计量方法,如PLS、PCR和人工神经网络(ANN)已被用于同时测定混合物中的这些化合物。校准模型是由含有已知农药浓度的河水溶液建立的,并使用采样DC和DPP(差分脉冲极谱)获得的信号。PLS对合成样品和实际样品(河水)进行了分析,大多数情况下结果令人满意。通过提取到乙醚中的预浓缩步骤,可以确定河流水样中每种农药的0.25 ppm。ANN也被用于改善PLS工具在记录采样直流电流或用C18墨盒进行液固萃取时获得的结果。
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Instructions to authors Author Index Keyword Index Volume contents New molecular surface-based 3D-QSAR method using Kohonen neural network and 3-way PLS
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