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主成分分析作为研究的里雅斯特湾食用贻贝中痕量金属之间相互依存关系的工具。

Principal component analysis as a tool for studying interdependences among trace metals in edible mussels from the Gulf of Trieste.

作者信息

Favretto L, Favretto L G

出版信息

Z Lebensm Unters Forsch. 1984 Nov;179(5):377-80. doi: 10.1007/BF01043433.

Abstract

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.

摘要

主成分分析已被用于分析从一个(6×44)数据矩阵得到的相关矩阵。这6种痕量金属为钴(Co)、镍(Ni)、铜(Cu)、镉(Cd)、汞(Hg)和铅(Pb),它们存在于的里雅斯特湾一个孵化场的食用贻贝(Mytilus galloprovincialis Lamarck)的软组织中。在“特征向量”空间中,维度被缩减为3个主轴,它们约占总方差的77%。主成分得到的未旋转因子矩阵表明,Co、Ni和Cu与第一主成分相关,Cd和Pb与第二主成分相关,Hg与第三主成分相关。这一情况也通过方差最大化旋转矩阵进行了评估,并且至少部分地通过考虑来自不同地理来源的痕量金属的关联进行了初步解释。

相似文献

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Multivariate data analysis of sea waters and mussels in relation to pollution sources of trace elements.
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