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Application of multivariate statistical approach to identify element sources in parsley ( Petroselinum crispum ).

Authors :
Mitic, V.
Stankov-Jovanovic, V.
Cvetkovic, J.
Dimitrijevic, M.
Ilic, M.
Nikolic-Mandic, S.
Source :
Toxicological & Environmental Chemistry; Jul2015, Vol. 97 Issue 6, p754-765, 12p
Publication Year :
2015

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02772248
Volume :
97
Issue :
6
Database :
Complementary Index
Journal :
Toxicological & Environmental Chemistry
Publication Type :
Academic Journal
Accession number :
108697600
Full Text :
https://doi.org/10.1080/02772248.2015.1068315