COMBINATION UV-VIS SPECTROSCOPY AND PARTIAL LEAST SQUARE FOR DETECTING ADULTERATION PARACETAMOL AND PIROXICAM IN TRADITIONAL MEDICINES

Abstract

An analytical method based on combination UV-Vis spectroscopy and chemometric was developed for detecting commonly listed adulterants such as paracetamol and piroxicam simultaneously in traditional medicines. No complex sample preparation and separation are required except grinding, dissolving, and filtering. The spectral interferences were resolved by multivariate techniques. Wavelengths selection and number of components optimization were performed by a combination of Genetic Algorithm and Partial Least Square (GA-PLS) followed by backward elimination through Jack-Knife Partial Least Square Regression (JK-PLSR). The capability PLSR model for quantitative analysis was assessed from the coefficient of determination (R²) and root mean square of error prediction/cross-validation (RMSEP/RMSECV) dan predicted residual sum of square (PRESS). Classification performance of PLS Discriminant Analysis (PLS-DA) was evaluated from the area under the receiver operating characteristic curve (AUROCC). For ensuring the sensitivity of the method, the detection limits from the two pseudo-univariate lines were estimated. The R², RMSEP, RMSECV, AUROCC, and detection limit obtained from the selected models of paracetamol and piroxicam were >0.999, <0.25 mg/L, <0.15 mg/L, 100%, and <0.4 mg/L respectively. Therefore, the proposed method is suitable for the rapid screening of adulterated herbal medicine.