Chemometrics chemometric techniques applied for classification and quantification of binary biodiesel/diesel blends

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorRocha, Werickson F. C.-
Autor(es): dc.creatorVaz, Boniek G.-
Autor(es): dc.creatorSarmanho, Gabriel F.-
Autor(es): dc.creatorLeal, Luiz H. C.-
Autor(es): dc.creatorNogueira, Raquel-
Autor(es): dc.creatorSilva, Viviane F.-
Autor(es): dc.creatorBorges, Cleber N.-
Data de aceite: dc.date.accessioned2026-02-09T11:55:53Z-
Data de disponibilização: dc.date.available2026-02-09T11:55:53Z-
Data de envio: dc.date.issued2017-07-14-
Data de envio: dc.date.issued2017-07-14-
Data de envio: dc.date.issued2012-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/13356-
Fonte completa do material: dc.identifierhttp://www.tandfonline.com/doi/abs/10.1080/00032719.2012.686135-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1150614-
Descrição: dc.descriptionIn this paper, three different types of biodiesel, which were synthesized from peanut, corn, and canola oils, were characterized by positive-ion electrospray ionization (ESI) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Different biodiesel/diesel blends containing 2–90% (V/V) of each biodiesel type were prepared and analyzed by near infrared spectroscopy (NIR). In the next step, the chemometric methods of hierarchical clusters analysis (HCA), principal component analysis (PCA), and support vector machines (SVM) were used for exploratory analysis of the different biodiesel samples, and the SVM was able to give the best classification results (correct classification of 50 peanut and 50 corn samples, and only one misclassification out of 49 canola samples). Then, partial least squares (PLS) and multivariate adaptive regression splines (MARS) models were evaluated for biodiesel quantification. Both methods were considered equivalent for quantification purposes based on the values smaller than 5% for the root mean square error of calibration (RMSEC) and root mean square of validation (RMSEP), as well as Pearson correlation coefficients of at least 0.969. The combination of NIR to the chemometric techniques of SVM and PLS/MARS was proven to be appropriate to classify and quantify biodiesel from different origins.-
Idioma: dc.languageen-
Publicador: dc.publisherTaylor & Francis Group-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceAnalytical Letters-
Palavras-chave: dc.subjectBiodiesel-
Palavras-chave: dc.subjectChemometric techniques-
Palavras-chave: dc.subjectTécnicas quimiométricas-
Título: dc.titleChemometrics chemometric techniques applied for classification and quantification of binary biodiesel/diesel blends-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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