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Cited by 264

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Remediation of metalliferous soils through the heavy metal resistant plant growth promoting bacteria: Paradigms and prospects

Open access
Ahemad, Munees·2019·Arabian Journal of Chemistry

Abstract

Various industrial, agricultural and military operations have released huge amounts of toxic heavy metals into the environment with deleterious effects on soils, water and air. Under metal stress, soil microorganisms including plant growth promoting bacteria (PGPB) have developed many strategies to evade the toxicity generated by the various heavy metals. Such metal resistant PGPB, when used as bioinoculant or biofertilizers, significantly improved the growth of plants in heavy metal contaminated/stressed soils. Application of bacteria possessing metal detoxifying traits along with plant-beneficial properties is a cost effective and environmental friendly metal bioremediation approach. This review highlights the different mechanisms of metal resistance and plant growth promotion of metal resistant PGPB as well as the recent development in exploitation of these bacteria in bioremediation of heavy metals in different agroecosystems.

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Metadata

Authors
Ahemad, M.
Venue
Arabian Journal of Chemistry
Published
2019-11
Volume
12
Issue
7
Pages
1365-1377
ISSN
1878-5352 (ISSN-L)
OpenAlex
W2027873010
Cited by
264
References
3
FWCI
4.69
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Remediation of metalliferous soils through the heavy metal resistant plant growth promoting bacteria: Paradigms and prospects. https://app.cochat.ai/papers/10.1016/j.arabjc.2014.11.020
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Ahemad, M. (2019). Remediation of metalliferous soils through the heavy metal resistant plant growth promoting bacteria: Paradigms and prospects. Arabian Journal of Chemistry. https://doi.org/10.1016/j.arabjc.2014.11.020

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.