Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2010-1-29
pubmed:abstractText
Atmospheric pressure chemical ionization mass spectrometry was used to predict the oxidative status of virgin olive oils (VOO) during their storage. VOO samples, with and without phenolic compounds, were stored in the dark at 60 degrees C up to 7 weeks. The VOO samples were diluted in an alkaline propanol/methanol mixture and directly infused into an ion-trap mass spectrometer. The abundances of the [M-H](-) peaks of free fatty acids, oxidized fatty acids, tocopherols and phenolic compounds, jointly with their oxidized forms, were measured and used as predictors. Two linear discriminant analysis (LDA) models were constructed in order to classify samples according to their oxidative levels. The first model was constructed using both VOO samples (with and without phenols), considering as predictors only fatty acids and their oxidized products. The second LDA model was constructed with the VOO sample with phenolic compounds considering as predictors all the peaks measured. In both models, the samples divided in the eight different storage times were correctly classified (100%) by leave-one-out cross-validation with an excellent resolution among all the category pairs (for the first model Wilks' lambda, lambda(w) = 0.229 and for the second lambda(w) = 0.928). This method is a very fast tool for on-line monitoring of VOO oxidation status.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1618-2650
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
395
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1543-50
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Evaluation of the oxidative status of virgin olive oils with different phenolic content by direct infusion atmospheric pressure chemical ionization mass spectrometry.
pubmed:affiliation
Departamento de Química Analítica, Universidad de Valencia, C. Doctor Moliner 50, 46100 Burjassot, Valencia, Spain.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't