Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production

Detalhes bibliográficos
Autor(a) principal: Mueller, Daniela
Data de Publicação: 2013
Outros Autores: Ferrão, Marco Flôres, Marder, Luciano, Costa, Adilson Ben da, Schneider, Rosana de Cassia de Souza
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/83595
Resumo: The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.
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spelling Mueller, DanielaFerrão, Marco FlôresMarder, LucianoCosta, Adilson Ben daSchneider, Rosana de Cassia de Souza2013-12-12T01:49:52Z20131424-8220http://hdl.handle.net/10183/83595000877187The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.application/pdfengSensors [recurso eletrônico]. Basel. Vol. 13, no. 4 (Apr. 2013), p. 4258-4271Espectroscopia : Infravermelho : Transformada de fourierAnálise multivariadaÓleos vegetaisBiodieselHCAiPCASIMCAUATR sensorRaw materialQuality controlFourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel productionEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000877187.pdf000877187.pdfTexto completo (inglês)application/pdf632704http://www.lume.ufrgs.br/bitstream/10183/83595/1/000877187.pdfdde88ba7c88e0781f157b24b8f321aadMD51TEXT000877187.pdf.txt000877187.pdf.txtExtracted Texttext/plain33412http://www.lume.ufrgs.br/bitstream/10183/83595/2/000877187.pdf.txt329287390740a64e2168919cb1683179MD52THUMBNAIL000877187.pdf.jpg000877187.pdf.jpgGenerated Thumbnailimage/jpeg2096http://www.lume.ufrgs.br/bitstream/10183/83595/3/000877187.pdf.jpgad1c735cf4451bd968e469b125ef97d5MD5310183/835952018-10-09 08:45:05.766oai:www.lume.ufrgs.br:10183/83595Repositório InstitucionalPUBhttps://lume.ufrgs.br/oai/requestlume@ufrgs.bropendoar:2018-10-09T11:45:05Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
title Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
spellingShingle Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
Mueller, Daniela
Espectroscopia : Infravermelho : Transformada de fourier
Análise multivariada
Óleos vegetais
Biodiesel
HCA
iPCA
SIMCA
UATR sensor
Raw material
Quality control
title_short Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
title_full Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
title_fullStr Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
title_full_unstemmed Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
title_sort Fourier transform infrared spectroscopy (FTIR) and multivariative analysis for identification of defferent vegetable oils used in biodiesel production
author Mueller, Daniela
author_facet Mueller, Daniela
Ferrão, Marco Flôres
Marder, Luciano
Costa, Adilson Ben da
Schneider, Rosana de Cassia de Souza
author_role author
author2 Ferrão, Marco Flôres
Marder, Luciano
Costa, Adilson Ben da
Schneider, Rosana de Cassia de Souza
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Mueller, Daniela
Ferrão, Marco Flôres
Marder, Luciano
Costa, Adilson Ben da
Schneider, Rosana de Cassia de Souza
dc.subject.por.fl_str_mv Espectroscopia : Infravermelho : Transformada de fourier
Análise multivariada
Óleos vegetais
Biodiesel
topic Espectroscopia : Infravermelho : Transformada de fourier
Análise multivariada
Óleos vegetais
Biodiesel
HCA
iPCA
SIMCA
UATR sensor
Raw material
Quality control
dc.subject.eng.fl_str_mv HCA
iPCA
SIMCA
UATR sensor
Raw material
Quality control
description The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.
publishDate 2013
dc.date.accessioned.fl_str_mv 2013-12-12T01:49:52Z
dc.date.issued.fl_str_mv 2013
dc.type.driver.fl_str_mv Estrangeiro
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/83595
dc.identifier.issn.pt_BR.fl_str_mv 1424-8220
dc.identifier.nrb.pt_BR.fl_str_mv 000877187
identifier_str_mv 1424-8220
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url http://hdl.handle.net/10183/83595
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Sensors [recurso eletrônico]. Basel. Vol. 13, no. 4 (Apr. 2013), p. 4258-4271
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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instname:Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
instname_str Universidade Federal do Rio Grande do Sul (UFRGS)
instacron_str UFRGS
institution UFRGS
reponame_str Repositório Institucional da UFRGS
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