English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/214794
Share/Impact:
Statistics
logo share SHARE   Add this article to your Mendeley library MendeleyBASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Title

Olive oil mixtures. Part two: Detection of soft deodorized oil in extra virgin olive oil through diacylglycerol determination. Relationship with free acidity

AuthorsGómez-Coca, R. B. ; Pérez Camino, María del Carmen ; Bendini, Alessandra; Gallina Toschi, Tullia; Moreda, Wenceslao
KeywordsDiacylglycerols
Free acidity
OLEUM Project
Olive oil fraud
Olive oil illegal blends
Soft deodorization
Issue Date15-Nov-2020
PublisherElsevier
CitationFood Chemistry 330: 127226 (2020)
AbstractThe detection of soft deodorized olive oils in extra virgin olive oil (EVOO) has become a challenging task ever since it was demonstrated that: 1. The process does not form the typical refining markers, e.g. stigmastadienes, and 2. The determination of the fatty acid alkyl esters renders useful only when the deodorized matrix comes from oils with fermentative defects. Recently researchers have developed strategies to detect such kind of blends, being one of them based on the fact that both diacylglycerol (DAG) and free fatty acids are not interdependent after mild refining activities. Presently, we propose two factors to confirm the absence of soft deodorized oils in EVOO: R1 (10 × free acidity/DAGexp) ≥ 0.23 and R2 (DAGexp-DAGtheor) < 0, in genuine EVOO. We demonstrate that such approach is useful to detect the presence of soft deodorized olive oil when this is at least at 30% in the mixture.
Description3 Tablas
Publisher version (URL)http://dx.doi.org/10.1016/j.foodchem.2020.127226
URIhttp://hdl.handle.net/10261/214794
ISSN0308-8146
Appears in Collections:(IG) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf14,71 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 


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