Spectrophotometric simultaneous determination of ceratine, creatinine, and uric acid in real samples by orthogonal signal correction–partial least squares regression

Abstract

This work describes a quantitative spectroscopic method for the analysis of ternary mixtures of ceratine (CER), creatinine (CRE), and uric acid (UA) using multivariate data models based upon ultraviolet spectroscopy. By multivariate calibration methods, such as partial least squares regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. In this study, the calibration model is based on absorption spectra in the 200–260 nm range for 36 different mixtures of CER, CRE, and UA. The unrelated information was removed by the orthogonal signal correction (OSC) method and the results were proved. Evaluation of the prediction errors for the prediction set reveals the OSC-treated data give substantially lower root mean square error of prediction (RMSEP) values than original data. The RMSEP for CER, CRE, and UA with OSC were 1.1686, 0.2195, and 0.3726, and without OSC were 1.9057, 0.3482, and 0.6164, respectively. This procedure allows the simultaneous determination of CER, CRE, and UA in synthetic and real samples.