共 136 条
The role of chemometrics in single and sequential extraction assays: A review Part I. Extraction procedures, uni- and bivariate techniques and multivariate variable reduction techniques for pattern recognition
被引:78
作者:
Abollino, Ornella
[1
]
Malandrino, Mery
[1
]
Giacomino, Agnese
[1
]
Mentasti, Edoardo
[1
]
机构:
[1] Univ Turin, Dept Analyt Chem, I-10125 Turin, Italy
关键词:
Single extraction;
Sequential extraction;
Chemometrics;
Multivariate statistics;
Soil;
Sediment;
HEAVY-METAL CONTAMINATION;
SPATIAL VARIABILITY;
CHEMICAL FRACTIONATION;
SOIL PROPERTIES;
TRACE-ELEMENTS;
AGRICULTURAL SOILS;
RIVER SEDIMENTS;
POLLUTED SOILS;
PHOSPHORUS FRACTIONATION;
ARSENIC BIOACCESSIBILITY;
D O I:
10.1016/j.aca.2010.12.020
中图分类号:
O65 [分析化学];
学科分类号:
070302 [分析化学];
摘要:
Element mobility and availability in natural solid matrices can be studied with single and sequential extraction procedures; such procedures provide reliable and useful information only if the experiments are correctly planned and executed and the results are properly interpreted. Chemometrics can be a valuable tool for these aims, especially taking into account the large amounts of data generated with extraction essays and the complexity of the processes under investigation. This review deals with the application of chemometrics in research studies involving single and sequential extractions on soils or sediments, for several purposes: the development and optimization of the extraction conditions, the calculation of element fractionation, the visual illustration of the experimental results, the acquisition of different areas of information, including relationships among variables, similarities and differences among samples, causes of the observed behaviour (e.g. source identification), risk assessment, models and predictions of future events. In Part I of the review, following an overview on extraction procedures, the applications of univariate and bivariate chemometric methods are reported; then the principles of multivariate techniques for pattern recognition based on variable reduction, their applications and the main findings obtained are addressed. (C) 2011 Elsevier B.V. All rights reserved.
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页码:104 / 121
页数:18
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