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Cited by 317

The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.

A Review on Acrylamide in Food: Occurrence, Toxicity, and Mitigation Strategies

Rifai, Lubna, Saleh, Fatima A.·2020·International Journal of Toxicology

Abstract

Acrylamide (AA) is a food contaminant present in a wide range of frequently consumed foods, which makes human exposure to this toxicant unfortunately unavoidable. However, efforts to reduce the formation of AA in food have resulted in some success. This review aims to summarize the occurrence of AA and the potential mitigation strategies of its formation in foods. Formation of AA in foods is mainly linked to Maillard reaction, which is the first feasible route that can be manipulated to reduce AA formation. Furthermore, manipulating processing conditions such as time and temperature of the heating process, and including certain preheating treatments such as soaking and blanching, can further reduce AA formation. Due to the high exposure to AA, recognition of its toxic effect is necessary, especially in developing countries where awareness about AA health risks is still very low. Therefore, this review also focuses on the different toxic effects of AA exposure, including neurotoxicity, genotoxicity, carcinogenicity, reproductive toxicity, hepatotoxicity, and immunotoxicity.

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Metadata

Authors
Rifai, L., & Saleh, F. A.
Venue
International Journal of Toxicology
Published
2020-02-04
Volume
39
Issue
2
Pages
93-102
ISSN
  • 1091-5818 (ISSN-L)
  • 1092-874X
OpenAlex
W3005501152
Cited by
317
References
70
FWCI
21.89
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Review on Acrylamide in Food: Occurrence, Toxicity, and Mitigation Strategies. https://app.cochat.ai/papers/10.1177/1091581820902405
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Rifai, L., & Saleh, F. A. (2020). A Review on Acrylamide in Food: Occurrence, Toxicity, and Mitigation Strategies. International Journal of Toxicology. https://doi.org/10.1177/1091581820902405

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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.