Determination of metal contents in aromatic herbs and spices from Algeria: Chemometric approach

Abstract Trace metals (As, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Sr, and Zn) in acid digests of some aromatic herbs and spices (basil, fennel, laurel, mint, oregano, rosemary, thyme, black pepper, cinnamon, coriander, and cumin) were determined quantitatively using ICP‐AES method. The highest concentrations (μg g −1 dry matter) of each of the 11 investigated metals were found as follows: As (0.42) and Pb (1.6) in rosemary samples; Cd (0.1) in basil; Co (0.62), Cu (12.13), and Zn (52.26) in oregano; Cr (2.95) and Mg (3110) in fennel, Fe (494) and Ni (7.61) in cumin; Mn (192) in black pepper; and finally Sr (60.68) in mint. Some chemometric techniques such as principal component analysis (PCA), hierarchical cluster analysis (HCA), and partial least square discriminant analysis (PLS‐DA) were used on metallic concentrations data in an attempt to classify these aromatic herbs and spices. The unsupervised pattern recognition PCA and HCA models gave the same result about similarities and differences between the studied plant samples, and five clusters of similar aromatic herbs and spices samples were formed. In order to verify the results of this clustering, we used a supervised pattern recognition method called partial least square discriminant analysis (PLS‐DA). Classes were groups or clusters of similar plants obtained previously. A hierarchical model builder (HMB) based on four PLS‐DA models was used to simultaneous determination of the class of each sample. It was found that all samples were correctly classified by PLS‐DA in their original groups as determined by PCA and HCA.