JOURNAL ARTICLE

Resistant starch in common beans: Concentration, characteristics, uses and health effects. A systematic map and review of the studies from 1962 to 2023.

  • Published In: International Journal of Food Science & Technology, 2023, v. 58, n. 8. P. 4088 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Bozkır, Eda; Santamarina, Chiara; Mariotti, Marco; Saia, Sergio 3 of 3

Abstract

This article systematically reviews the concentration, variability, and health effects of resistant starch (RS)—a starch fraction resistant to digestive enzymes and acting as dietary fiber—in common bean (Phaseolus vulgaris) seeds. Analysis of 108 relevant studies revealed a wide range of RS content in raw common beans, averaging 16.4%, influenced by factors such as genotype, cultivation conditions, processing, and cooking methods. RS in beans contributes to gut health by supporting beneficial bacterial growth and short-chain fatty acid production, and it may aid in regulating glucose and lipid metabolism. Despite its nutritional importance, research on the agronomic, environmental, genetic determinants, and industrial applications of bean RS remains limited. The findings suggest that breeding for variable RS levels could address differing dietary fiber needs across regions, with high-RS beans benefiting fiber-deficient populations and low-RS beans enhancing caloric intake where food scarcity exists.

Additional Information

  • Source:International Journal of Food Science & Technology. 2023/08, Vol. 58, Issue 8, p4088
  • Document Type:Article
  • Subject Area:Agriculture and Agribusiness
  • Publication Date:2023
  • ISSN:0950-5423
  • DOI:10.1111/ijfs.16522
  • Accession Number:164936754
  • Copyright Statement:Copyright of International Journal of Food Science & Technology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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