English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/150725
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

An AFLP based method for the detection and identification of indigenous yeast in complex must samples without a microbiological culture

AuthorsRodríguez-Tarduchy, Gemma ; Santos, Cruz
KeywordsMolecular markers
Wine yeasts
Indigenous strains
AFLP database
Issue Date2017
CitationInternational Journal of Food Microbiology 241: 89-97 (2017)
AbstractRibera de Duero Spanish wines are appreciated worldwide for their organoleptic characteristics; however, the wine market is very competitive, and the demand for high quality natural wines has been increasing in recent years. The microbiology of the process, specifically the yeasts involved in the alcoholic fermentation, constitutes an essential element directly related to the complexity and quality of the wine. Our work has focused on the development of a procedure to identify the indigenous wine yeasts present in complex samples of must and wine, without requiring colony isolation or a microbiological culture. The procedure is based on the use of AFLP molecular markers. The AFLP allele profiles obtained from complex samples are compared with the species-specific ones previously determined and included in a database using a sorting algorithm. The system allows a fast and efficient identification of yeast species and strains present in complex must and wine samples. This information can then be used by the enologists during the fermentation process in order to obtain signed wines.
Identifiersdoi: 10.1016/j.ijfoodmicro.2016.09.014
e-issn: 1879-3460
issn: 0168-1605
Appears in Collections:(IIBM) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.