RESUMO
Second-order based calibration methods have been widely investigated capitalizing on the inherent benefits of the data structure and the decomposition models, demonstrating that second-order advantage is a property that conspires to a high likelihood success in the resolution of systems of varying complexity. This work aims to demonstrate the applicability of a combined chemometric strategy to solve non-linear multivariate calibration systems in the presence of non-multilinear multi-way data. The determination of histamine by differential pulse voltammetry at different pH is presented as case study. The experimental system has the outstanding difficulty arisen from the large displacement along the potential axis by the pH, which was successfully overcome by implementation of the presented combined strategy. For data modeling, MCR-ALS, U-PLS/RBL and U-PCA/RBL-RBF were used. MCR-ALS allowed unraveling the non-linear behavior between the signal and the concentration, and extracting the underlying profiles of the constituent. Quantitative analysis was performed through the three models, and a comparative evaluation of the predictive performance was done. The best results were achieved with U-PCA/RBL-RBF (mean recovery = 101%) whereas, MCR-ALS yield the lowest mean recovery for all samples (70%).
RESUMO
Nalidixic acid (NA) and its main metabolite, 7-hydroxymethylnalidixic acid (OH-NA), are simultaneously determined by applying artificial neural networks (ANNs), to their square wave voltammetric signals. The scores of a PCR model, built with the voltammetric data of a set of standard samples, recorded between -0.70 and -1.0V, are used as training set for the net for each compound. The trained nets (ANNs) are used for the simultaneous determination of NA and OH-NA in urine. The recovery values are comprised between 91 and 109% for NA and between 82 and 112% for OH-NA, being these results better than the results obtained by application of partial least squares (PLS) multivariate calibration.
RESUMO
A simple procedure for the determination of piromidic acid by square wave adsorptive stripping voltammetry (SW-AdSV) at a hanging mercury drop electrode has been developed. The variables affecting to accumulation process such as concentration of perchloric acid, accumulation potential and accumulation time have been optimised (0.025 mol L(-1), -0.25 V and 140 s, respectively) by using response surface methodology. A linear relationship between concentration of piromidic acid and peak intensity has been found in the range 2.22 x 10(-9) to 3.33 x 10(-8) mol L(-1). The detection limit (1.65 x 10(-9) mol L(-1)) has been calculated by the method proposed by Clayton et al. so that protection against both false positive and false negative errors is assured. The procedure was successfully applied to determine piromidic acid in spiked urine samples. The obtained recovery values were in the range 97.3-103.3% at different levels of concentration of piromidic acid.
