Using the extract of pomegranate peel as a natural indicator for colorimetric detection and simultaneous determination of Fe3+ and Fe2+ by partial least squares-artificial neural network

A simple, novel, biocompatible, and sensitive spectrophotometric method was developed for colorimetric detection and speciation of Fe3+ and Fe2+ ions. The method is based on the complex formation of Fe3+ and Fe2+ with organic constituents containing functional groups in pomegranate peel extract (PG). Developing of the color is specifically established in the presence of Fe3+ and Fe2+. Accordingly, in addition to direct detection of both cations, we carried out a quantitative multivariate model for their accurate determination in real matrix aqueous samples. Due to spectral interference, the simultaneous determination of Fe3+ and Fe2+ mixtures using spectrophotometry is a problematic issue. A combined multivariate as partial least squares (PLS)-artificial neural network (ANN) was used to create and adjust a model and predict said cations in test and real sample sets. In this context, the calibration model is based on absorption spectra in the 400-900 nm range for 98 different mixtures of Fe3+ and Fe2+. Calibration matrices contained 1-12 and 1-10 mu g ml(-1) of Fe3+ and Fe2+, respectively. The detection limits for Fe3+ and Fe2+ were 0.53 and 0.14 mu g ml(-1), respectively. The root mean square error of prediction (RMSEP) for Fe3+ and Fe2+ with PLS-ANN was 0.78, 1.65 and 1.062, 0.894 in Kalugan waterfall and Tehran tap water. This strategy can simultaneously determine Fe3+ and Fe2+ in real matrix samples, and the reliability of the determination is acceptable.