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Cited by 319

The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.

Green technologies for the extraction of bioactive compounds in fruits and vegetables

Open access
Soquetta, Marcela Bromberger, Terra, Lisiane de Marsillac, Bastos, Caroline Peixoto·2018·CyTA - Journal of Food

Abstract

Bioactive compounds are extracted from natural sources and they have beneficial effects on human health. Fruits and vegetables are rich in carotenoids, phenolic compounds, Vitamin C, among others. Extraction processes for these compounds depend on several factors such as the technique that is used, the raw material, and the organic solvent. Conventional techniques generally require large amounts of organic solvents, high energy expenditure, and are time consuming, which has generated interest in new technologies that are referred to as clean or green technologies. These can reduce or eliminate the use of toxic solvents, and thus preserve the natural environment and its resources. The aim of this review is to discuss recent techniques used to extract bioactive compounds from natural sources, in order to reduce the economic and ecological impact of these processes.

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Crossref · 10.1080/19476337.2017.1411978

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Metadata

Authors
Soquetta, M. B., Terra, L. D. M., & Bastos, C. P.
Venue
CyTA - Journal of Food
Published
2018-01
Volume
16
Issue
1
Pages
400-412
ISSN
  • 1947-6337 (ISSN-L)
  • 1947-6345
OpenAlex
W2792990174
Cited by
319
References
106
FWCI
13.24
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Green technologies for the extraction of bioactive compounds in fruits and vegetables. https://app.cochat.ai/papers/10.1080/19476337.2017.1411978
The paper
Soquetta, M. B., Terra, L. D. M., & Bastos, C. P. (2018). Green technologies for the extraction of bioactive compounds in fruits and vegetables. CyTA - Journal of Food. https://doi.org/10.1080/19476337.2017.1411978

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.