Principal component analysis as a tool for studying interdependences among trace metals in edible mussels from the Gulf of Trieste
Principal component analysis has been applied to analyze the correlation matrix obtained from a (6 X 44) data matrix. The 6 trace metals are Co, Ni, Cu, Cd, Hg, and Pb, which are contained in the soft part of edible mussels (Mytilus galloprovincialis Lamarck) from a hatchery on the gulf of Trieste....
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Veröffentlicht in: | Zeitschrift f r Lebensmittel-Untersuchung und -Forschung 1984-11, Vol.179 (5), p.377-380 |
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Sprache: | eng |
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Zusammenfassung: | Principal component analysis has been applied to analyze the correlation matrix obtained from a (6 X 44) data matrix. The 6 trace metals are Co, Ni, Cu, Cd, Hg, and Pb, which are contained in the soft part of edible mussels (Mytilus galloprovincialis Lamarck) from a hatchery on the gulf of Trieste. In the space of "eigenvectors", the dimensions are reduced to 3 principal axes, which account for about 77% of the total variance. The unrotated factor matrix obtained by the principal components shows that Co, Ni and Cu are bonded to the first principal component, Cd and Pb to the second, Hg to the third. This picture is also assessed by the Varimax-rotated matrix and it is tentatively explained, at least in part, by considering the associations of the trace metals from various geographical sources. |
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ISSN: | 0044-3026 1438-2385 |
DOI: | 10.1007/BF01043433 |