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Cited by 542

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Methanogenesis and Sulfate Reduction: Competitive and Noncompetitive Substrates in Estuarine Sediments

Open access
Oremland, Ronald S., Polcin, Sandra·1982·Applied and Environmental Microbiology

Abstract

Sulfate ions did not inhibit methanogenesis in estuarine sediments supplemented with methanol, trimethylamine, or methionine. However, sulfate greatly retarded methanogenesis when hydrogen or acetate was the substrate. Sulfate reduction was stimulated by acetate, hydrogen, and acetate plus hydrogen, but not by methanol or trimethylamine. These results indicate that sulfate-reducing bacteria will outcompete methanogens for hydrogen, acetate, or both, but will not compete with methanogens for compounds like methanol, trimethylamine, or methionine, thereby allowing methanogenesis and sulfate reduction to operate simultaneously within anoxic, sulfate-containing sediments.

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Registry

Crossref · 10.1128/aem.44.6.1270-1276.1982

Cites

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Metadata

Authors
Oremland, R. S., & Polcin, S.
Venue
Applied and Environmental Microbiology
Published
1982-12
Volume
44
Issue
6
Pages
1270-1276
ISSN
  • 0099-2240 (ISSN-L)
  • 1098-5336
OpenAlex
W1541943161
Cited by
542
References
28
FWCI
10.45
Type
journal article
Language
en
Open access
green

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This page
CoChat. (2026). Citation check: Methanogenesis and Sulfate Reduction: Competitive and Noncompetitive Substrates in Estuarine Sediments. https://app.cochat.ai/papers/10.1128/aem.44.6.1270-1276.1982
The paper
Oremland, R. S., & Polcin, S. (1982). Methanogenesis and Sulfate Reduction: Competitive and Noncompetitive Substrates in Estuarine Sediments. Applied and Environmental Microbiology. https://doi.org/10.1128/aem.44.6.1270-1276.1982

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.