Study on the influential biochemical indices of Cd(II) on Eisenia fetida in oxidative stress by principal component analysis in the natural soil

Study on the influential biochemical indices of Cd(II) on Eisenia fetida in oxidative stress by... With the aggravation of heavy metal pollution in soil, the individual heavy metal content monitoring cannot predict the true effects of harmful substances on the ecosystems. Thus, the effective biological evaluation system should be established to assess the pollution risk caused by heavy metal. Earthworms are widely distributed in the soil, and at the bottom of the food chain, the changes of biochemical indices play an important role in the early warning for heavy metal pollution. Principal component analysis (PCA) is a statistical method that derives several independent principal components from the original variable based on retaining the information as much as possible. This paper is aimed at finding out and analyzing the key monitoring factors related to Cd2+ on the earthworm Eisenia fetida in oxidative stress. The Cd2+ stress concentrations were set at 0, 1, 10, 20, 100, 200, 400, and 800 mg kg−1, and the post-clitellum segment of earthworm was chosen to determine TP, POD, SOD, GST, GPX, CAT, MDA, VE, and AChE. The results showed that the main bioindicators associated with oxidative stress reaction were GST, POD, and MDA at the exposure time of 10 days; at 20 days GPX, MDA, and AChE; at 30 days CAT, TP, and GPX; CAT, MDA, and SOD at 40th day. These results indicated that PCA can quickly, effectively, directly, and scientifically select biomarkers of oxidative stress induced by Cd and improve the accuracy and scientificity of earthworm as a biomarker in monitoring and early warning for heavy metal-contaminated soil. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Science and Pollution Research Springer Journals

Study on the influential biochemical indices of Cd(II) on Eisenia fetida in oxidative stress by principal component analysis in the natural soil

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Environment; Environment, general; Environmental Chemistry; Ecotoxicology; Environmental Health; Atmospheric Protection/Air Quality Control/Air Pollution; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
ISSN
0944-1344
eISSN
1614-7499
D.O.I.
10.1007/s11356-017-0807-3
Publisher site
See Article on Publisher Site

Abstract

With the aggravation of heavy metal pollution in soil, the individual heavy metal content monitoring cannot predict the true effects of harmful substances on the ecosystems. Thus, the effective biological evaluation system should be established to assess the pollution risk caused by heavy metal. Earthworms are widely distributed in the soil, and at the bottom of the food chain, the changes of biochemical indices play an important role in the early warning for heavy metal pollution. Principal component analysis (PCA) is a statistical method that derives several independent principal components from the original variable based on retaining the information as much as possible. This paper is aimed at finding out and analyzing the key monitoring factors related to Cd2+ on the earthworm Eisenia fetida in oxidative stress. The Cd2+ stress concentrations were set at 0, 1, 10, 20, 100, 200, 400, and 800 mg kg−1, and the post-clitellum segment of earthworm was chosen to determine TP, POD, SOD, GST, GPX, CAT, MDA, VE, and AChE. The results showed that the main bioindicators associated with oxidative stress reaction were GST, POD, and MDA at the exposure time of 10 days; at 20 days GPX, MDA, and AChE; at 30 days CAT, TP, and GPX; CAT, MDA, and SOD at 40th day. These results indicated that PCA can quickly, effectively, directly, and scientifically select biomarkers of oxidative stress induced by Cd and improve the accuracy and scientificity of earthworm as a biomarker in monitoring and early warning for heavy metal-contaminated soil.

Journal

Environmental Science and Pollution ResearchSpringer Journals

Published: Nov 27, 2017

References

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