Affiliation:
1. University of Belgrade ‐ Faculty of Chemistry Belgrade Serbia
2. Laboratory for Testing, Quality Control and Certification Profilab Belgrade Serbia
3. Innovative Centre of the Faculty of Chemistry Ltd. University of Belgrade Belgrade Serbia
Abstract
AbstractAccording to the study carried out at the University of Bristol, 60% of oregano spices present on the European Union (EU) market are adulterated with olive, myrtle, cistus, and hazelnut leaves. According to the same authors, the sage products are adulterated by similar bulking agents. The aim of this study was to assess possibilities for detection of sage adulteration by olive leaves using high‐performance thin‐layer chromatography (HPTLC) coupled with digital image analysis and multivariate linear regression/classification (partial least squares and partial least squares discriminant analysis). Twenty‐four samples (4 pure sage leaves, 4 pure olive leaves, and 16 mixtures of olive and sage leaves with content of added olive leaves varying in 5%, 10%, 20%, and 50%) have been prepared, extracted, and analyzed under normal‐phase conditions. Several derivatization methods were tested, and derivatized HPTLC plates were inspected under visible or ultraviolet light. Digital images of chromatograms were recorded. In order to minimize effects of intraplate and interplate peak shifts, background changes, and baseline drifts, correlation‐optimized warping, standard normal variate, and mean centering were applied to acquired signals. Partial least squares and partial least squares discriminant analysis models with moderate complexity (two to four latent variables) based on chromatographic signals obtained after derivatization by FeCl3, anisaldehyde–sulfuric acid, and 2,2‐diphenyl‐1‐picrylhydrazyl demonstrated good statistical performances with R2 ranging 0.894–0.998 and relative prediction error of 4–12%. Misclassification error <4% was obtained in the case of 2,2‐diphenyl‐1‐picrylhydrazyl and anisaldehyde–sulfuric acid derivatization. Therefore, HPTLC combined with multivariate image analysis, signal processing, and linear modeling proved to be promising, cost‐effective chromatographic tool for assessment of sage adulteration by olive leaves.
Subject
Applied Mathematics,Analytical Chemistry