Interpretation of heavy metal data from mussel by use of mutivariate classification techniques

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 origen 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.