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Interpretation of heavy metal data from mussel by use of multivariate classification techniques
L Machado Mesa1, E Peña Méndez, M Sánchez Sánchez
1Dpt. Analytical Chemistry, Nutrition and Food Science, University of La Laguna, Tenerife, Spain.
Abstract:
Different strategies of multivariate analysis of metals concentrations (Mn, Fe, Ni, V, Co, Cu, Cd, Hg, Pb, Na, K) in mussel samples from different spanish markets are used to interpret a data base and identify differences between species and origin of the samples. Principal Component Analysis and Potential curves are applied to properly classify unknown samples from representative mussels samples (Mytilus edulis and Perna canaliculus). Also, Principal Components Analysis is used as display method to visualize the relation between the variables and objects of interest.

