The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.
To against the increasing number of adulteration reports in herbal medicine products in Indonesia, specifically Jamu in powder dosage form, a rapid, efficient, inexpensive method is required. This study was aimed to develop an approach for quantification and classification of an unadulterated herbal medicine product with synthetic drug (prednisone and metamizole) by combining FTIR Spectroscopy and multivariate calibration (PLSR and PCR) as well as discriminant analysis (DA). The spectra data of three individual types of reducing herbal pain products were scanned and collected by FTIR-ATR in the mid-infrared region and further analyzed by two multivariate calibrations to exhibit the optimum mode for quantification analysis of each sample reducing herbal pain product. Based on statistical parameter value, PCR analysis of each model demonstrated the highest value of R2 in both calibration and validation and the lowest value of root mean square of calibration (RMSEC) and root mean square of prediction (RMSEP). The discriminant analysis (DA) was also performed in this study to classify pure reducing pain herbal medicine products without any drugs contaminant and adulterated with synthetic drugs. The outcome of DA was shown by Cooman’s plot and DA could discriminate adulterated and unadulterated reducing pain herbal medicine products with 100% accuracy level. FTIR-ATR spectroscopy in the mid-infrared region coupled with chemometrics could be a potential analytical technique to detect synthetic drugs contaminant in herbal products.
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