Item request has been placed!
×
Item request cannot be made.
×

Processing Request
Assessing Food Safety Risks in Homemade Fermented Beverages: A Case Study with Quinoa Rejuvelac.
Item request has been placed!
×
Item request cannot be made.
×

Processing Request
- Additional Information
- Abstract:
Spontaneous fermentation processes can promote uncontrolled microbial growth and increase the risk of foodborne contamination, making the characterization of artisanal beverages essential for consumer safety. This study investigated the microbial composition of quinoa-based rejuvelac, a homemade fermented drink often perceived as a functional food, with the objective of identifying potential microbiological hazards associated with its preparation. High-throughput sequencing of the 16S rRNA V3–V4 region was combined with shotgun metagenomics to profile bacterial communities and recover metagenome-assembled genomes. The analysis revealed a strong dominance of Pseudomonadales, mainly Pseudomonas, Acinetobacter, Enterobacter and Burkholderiales, while lactic acid bacteria typically responsible for stable and safe fermentations were not detected. Shotgun metagenomics recovered medium- to high-quality genomes from Burkholderiaceae and Clostridiales, supporting the overrepresentation of non-beneficial taxa and indicating deviations from expected fermentation microbiota. These results show that the spontaneous preparation of rejuvelac may favor bacterial groups associated with environmental contamination rather than fermentative pathways, underscoring the importance of hygiene practices, controlled starter cultures and monitoring strategies to mitigate microbiological risk. The study highlights the need for improved safety standards in artisanal fermented foods to prevent unintended microbial contamination and protect consumers. [ABSTRACT FROM AUTHOR]
- Abstract:
Copyright of Life (2075-1729) is the property of MDPI 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.)
No Comments.