347
Views
0
CrossRef citations to date
0
Altmetric
Review

Overview of in vitro digestion methods to evaluate bioaccessibility of lipophilic compounds in foods

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 7126-7147 | Published online: 27 Nov 2022
 

ABSTRACT

In vitro digestion models for assessing the bioaccessibility of lipophilic compounds from foodstuffs can either be static or dynamic. Carotenoids are the most widely studied compounds, while there is hardly any information on sterols and fat-soluble vitamins available, nor on the use of dynamic methods. There is a large variability in the parameters of static methods, which makes data comparison difficult. To harmonize digestion conditions and compare bioaccessibility, INFOGEST model has been established. This review assesses the most relevant digestion methods (non-INFOGEST, INFOGEST and dynamic) applied to carotenoids, sterols, and fat-soluble vitamins in food matrices in the last ten years.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work is part of the project PID2019-104167RB-I00 funded by the Ministry of Science and Innovation (Spain) under grant MCIN/AEI/10.13039/501100011033. Nerea Faubel holds a grant under INVEST/2022/36 program (Ref. CPI-22-458, Generalitat Valenciana, Spain).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,043.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.