Application of multivariate statistical approach to identify element sources in parsley (Petroselinum crispum) |
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| Authors: | V Mitic V Stankov-Jovanovic J Cvetkovic M Dimitrijevic M Ilic S Nikolic-Mandic |
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| Institution: | 1. Department of Chemistry, Faculty of Science and Mathematics, University of Nis, Nis, Serbiavioletamitic@pmf.ni.ac.rs;3. Department of Chemistry, Faculty of Science and Mathematics, University of Nis, Nis, Serbia;4. Faculty of Chemistry, University of Belgrade, Belgrade, Serbia |
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| Abstract: | The aim of this study was to determine the content of elements in the parsley roots (Petroselinum crispum) of different geographic origin and estimate their possible sources applying chemometric analysis. The concentrations of 13 elements in parsley collected at 12 locations in five districts were examined. Cluster analysis (CA) separated elements into three statistical significant clusters: metalloids, heavy, and essential metals. Principal component analysis (PCA) permitted the reduction of 13 variables to three principal components explaining 82.3% of the total variance. The first component with 48.2% of variance comprises Al, Cu, Fe, Mn, Mo, Zn, and Co. Some of these metals are essential in low concentrations and their presence in plants is of lithogenic origin. Multivariate statistical analysis approach, such as PCA and CA can be used to assess the level of elements in vegetables. These methods can be used to identify sources of elements in plants too. |
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| Keywords: | elemental composition ICP OES principal component analysis cluster analysis parsley |
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