ABSTRACT
An orthogonal signal correction-partial least squares (OSC-PLS) method was developed for the simultaneous spectrophotometric determination of orotic acid (OA), creatinine (CRE), and uric acid (UA) in spiked real samples. By multivariate calibration methods, such as PLS regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. The effect of OSC used to remove the information unrelated to the target variables is studied. In this study, the calibration model is based on absorption spectra in the 220-320 nm rang for 36 different mixtures of OA, CRE and UA. Calibration matrices contained 1.74-47.00 of OA, 1.13-33.95 of CRE, and 1.68-28.58 of UA in µg/ml. The number of principal component for OA, CRE, and UA with OSC were 3, 4, and 4, and 4, 6, and 5, without OSC, respectively. The evaluation of the prediction errors for the prediction set reveals that the OSC-treated data give substantially lower root mean square error of prediction (RMSEP) values than the original data. The RMSEP for OA, CRE, and UA with OSC were 0.69, 0.20, and 0.53 and 0.80, 0.69, and 0.73 without OSC, respectively. The proposed method was applied for the simultaneous determination of OA, CRE, and UA in spiked biological fluids with satisfactory results.
