QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Química Nova (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422020000600723 |
Resumo: | Mid-Infrared absorption spectroscopy associate with the Partial Least Squares regression is the official method to monitor Brazilian commercial diesel quality. This method, however, uses solvents and a large number of samples for the construction of the calibration curves, which generates waste and increases the time needed for the analysis. In order to develop a non-destructive method, being possible to recover the sample after its quantification, decrease the quantity of samples and make use of a single calibration curve, in this study we used the oilseed crambe, which is not used in human food, for the methyl biodiesel production and PLS analysis for their content determination in mixtures with diesel at a concentration range of 1.00 to 30.00 (% v/v). The global model for crambe methyl biodiesel obatined RMSEC = 0.26 (% v/v), RMSECV = 0.35 (% v/v) and RMSEP = 0.41 (% v/v). Complementary, variable selection method iPLS was applied in the global model in order to reduce the spectral range required to regression construction and to improve the RMSEP, RMSECV and RMSEC values. |
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QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEISbiofuelsmultivariate calibrationselection of IntervalsiPLSMid-Infrared absorption spectroscopy associate with the Partial Least Squares regression is the official method to monitor Brazilian commercial diesel quality. This method, however, uses solvents and a large number of samples for the construction of the calibration curves, which generates waste and increases the time needed for the analysis. In order to develop a non-destructive method, being possible to recover the sample after its quantification, decrease the quantity of samples and make use of a single calibration curve, in this study we used the oilseed crambe, which is not used in human food, for the methyl biodiesel production and PLS analysis for their content determination in mixtures with diesel at a concentration range of 1.00 to 30.00 (% v/v). The global model for crambe methyl biodiesel obatined RMSEC = 0.26 (% v/v), RMSECV = 0.35 (% v/v) and RMSEP = 0.41 (% v/v). Complementary, variable selection method iPLS was applied in the global model in order to reduce the spectral range required to regression construction and to improve the RMSEP, RMSECV and RMSEC values.Sociedade Brasileira de Química2020-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422020000600723Química Nova v.43 n.6 2020reponame:Química Nova (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.21577/0100-4042.20170554info:eu-repo/semantics/openAccessCosta,Lucas G. daSitoe,Baltazar V.Santos,Douglas Q.Borges Neto,Waldomiropor2020-07-20T00:00:00Zoai:scielo:S0100-40422020000600723Revistahttps://www.scielo.br/j/qn/ONGhttps://old.scielo.br/oai/scielo-oai.phpquimicanova@sbq.org.br1678-70640100-4042opendoar:2020-07-20T00:00Química Nova (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
title |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
spellingShingle |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS Costa,Lucas G. da biofuels multivariate calibration selection of Intervals iPLS |
title_short |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
title_full |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
title_fullStr |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
title_full_unstemmed |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
title_sort |
QUANTIFICAÇÃO DO TEOR DE BIODIESEL DE CRAMBE EM MISTURAS COM DIESEL UTILIZANDO ESPECTROSCOPIA MIR E SELEÇÃO DE VARIÁVEIS |
author |
Costa,Lucas G. da |
author_facet |
Costa,Lucas G. da Sitoe,Baltazar V. Santos,Douglas Q. Borges Neto,Waldomiro |
author_role |
author |
author2 |
Sitoe,Baltazar V. Santos,Douglas Q. Borges Neto,Waldomiro |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Costa,Lucas G. da Sitoe,Baltazar V. Santos,Douglas Q. Borges Neto,Waldomiro |
dc.subject.por.fl_str_mv |
biofuels multivariate calibration selection of Intervals iPLS |
topic |
biofuels multivariate calibration selection of Intervals iPLS |
description |
Mid-Infrared absorption spectroscopy associate with the Partial Least Squares regression is the official method to monitor Brazilian commercial diesel quality. This method, however, uses solvents and a large number of samples for the construction of the calibration curves, which generates waste and increases the time needed for the analysis. In order to develop a non-destructive method, being possible to recover the sample after its quantification, decrease the quantity of samples and make use of a single calibration curve, in this study we used the oilseed crambe, which is not used in human food, for the methyl biodiesel production and PLS analysis for their content determination in mixtures with diesel at a concentration range of 1.00 to 30.00 (% v/v). The global model for crambe methyl biodiesel obatined RMSEC = 0.26 (% v/v), RMSECV = 0.35 (% v/v) and RMSEP = 0.41 (% v/v). Complementary, variable selection method iPLS was applied in the global model in order to reduce the spectral range required to regression construction and to improve the RMSEP, RMSECV and RMSEC values. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422020000600723 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422020000600723 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
10.21577/0100-4042.20170554 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
dc.source.none.fl_str_mv |
Química Nova v.43 n.6 2020 reponame:Química Nova (Online) instname:Sociedade Brasileira de Química (SBQ) instacron:SBQ |
instname_str |
Sociedade Brasileira de Química (SBQ) |
instacron_str |
SBQ |
institution |
SBQ |
reponame_str |
Química Nova (Online) |
collection |
Química Nova (Online) |
repository.name.fl_str_mv |
Química Nova (Online) - Sociedade Brasileira de Química (SBQ) |
repository.mail.fl_str_mv |
quimicanova@sbq.org.br |
_version_ |
1750318120523792384 |