dc.contributorRodinei Augusti
dc.contributorMarcelo Martins de Sena
dc.contributorRosineide Costa Simas
dc.contributorCleiton Antônio Nunes
dc.contributorLeticia Malta Costa
dc.contributorHelvecio Costa Menezes
dc.creatorJunia de Oliveira Alves
dc.date.accessioned2019-08-14T02:51:11Z
dc.date.accessioned2022-10-03T23:52:29Z
dc.date.available2019-08-14T02:51:11Z
dc.date.available2022-10-03T23:52:29Z
dc.date.created2019-08-14T02:51:11Z
dc.date.issued2014-09-25
dc.identifierhttp://hdl.handle.net/1843/SFSA-9RMGC8
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3829322
dc.description.abstractAiming at merging modern mass spectrometry techniques (electrospray ionization mass spectrometry - ESI-MS and easy ambient sonic-spray ionization mass spectrometry -EASI-MS) with chemometric methods (partial least squares -PLS and partial least squares discriminant analysis PLS-DA) the present work was developed forquality control of extra virgin olive oil and diesel b (blends diesel/biodiesel). The chapters were organized as following indicated:Chapter 4 was designed for quality control of extra virgin olive oil. A PLS2-DA model was developed basead on ESI-MS data, for classification of seven classes of olive oil (ordinary olive oil, extra virgin olive oil and adulterated with five adulterants oils). The best model was built with eight latent variables and showing good sensitivity (1.000) and specificity (0.967 1.000) values for the training and test sets. PLS models were also built, with seven models built with ESI-MS data, two models with data from a mass spectrometer for high resolution ESI-HRMS and a model constructed from data EASI (+)-MS. The 10 models were constructed for the quantification of adulterants oils( soybean, corn, sunflower and canola) in extra virgin olive oil. The models were validated by means of some figures of merit, was evaluated in models linearity, bias, accuracy, precision, selectivity, sensitivity and analytical sensitivity, limits of detection and quantification and Residual Prediction Deviation (RPD). Chapter 5 was intended for diesel b quality control ESI-MS data was used to construct a model for quantification of biodiesel in diesel. This model was also validated similarly as above mentioned. The proposed methods are promising because they are simple and fast. All models showed high efficiency and can be used in quality control of samples of extra virgin olive oil and biesel b.
dc.publisherUniversidade Federal de Minas Gerais
dc.publisherUFMG
dc.rightsAcesso Aberto
dc.subjectAdulteração
dc.subjectControle de qualidade
dc.subjectAzeite de Oliva extra virgem
dc.subjectPLS
dc.subjectDiesel b
dc.subjectESI-MS
dc.subjectPLS-DA
dc.subjectEASI-MS
dc.subjectValidação Multivariada
dc.titleControle de qualidade de azeite de oliva extra virgem e misturas diesel/biodiesel utilizando espectrometria de massas e validação multivariada
dc.typeTese de Doutorado


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