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Cited by 474

The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.

Nanotechnology in food science: Functionality, applicability, and safety assessment

Open access
He, Xiaojia, Hwang, Huey-Min·2016·Journal of Food and Drug Analysis

Abstract

Rapid development of nanotechnology is expected to transform many areas of food science and food industry with increasing investment and market share. In this article, current applications of nanotechnology in food systems are briefly reviewed. Functionality and applicability of food-related nanotechnology are highlighted in order to provide a comprehensive view on the development and safety assessment of nanotechnology in the food industry. While food nanotechnology offers great potential benefits, there are emerging concerns arising from its novel physicochemical properties. Therefore, the safety concerns and regulatory policies on its manufacturing, processing, packaging, and consumption are briefly addressed. At the end of this article, the perspectives of nanotechnology in active and intelligent packaging applications are highlighted.

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Metadata

Authors
He, X., & Hwang, H.-M.
Venue
Journal of Food and Drug Analysis
Published
2016-10
Volume
24
Issue
4
Pages
671-681
ISSN
1021-9498 (ISSN-L)
OpenAlex
W2490600996
Cited by
474
References
101
FWCI
19.00
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Nanotechnology in food science: Functionality, applicability, and safety assessment. https://app.cochat.ai/papers/10.1016/j.jfda.2016.06.001
The paper
He, X., & Hwang, H.-M. (2016). Nanotechnology in food science: Functionality, applicability, and safety assessment. Journal of Food and Drug Analysis. https://doi.org/10.1016/j.jfda.2016.06.001

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.