Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data model...

Autores
de Araújo Gomes, Adriano; Schenone, Agustina Violeta; Goicoechea, Hector Casimiro; Araújo, Mario Cesar
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM),when under inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. Inner filter effectcan originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods. The algorithm presented in this paper was named iSPA-U-PLS/RBL. Both simulated and experimental data sets were used to compare the prediction capability during: a) simulated EEM; and b) quantitation of phenylephrine (PHE) in the presence of paracetamol (PAR) (or acetaminophen) in water samples. Test sets containing unexpected components were built in both systems (a single interference was taken into account in the simulated data set, while water samples were added with varying amounts of ibuprofen (IBU), and acetyl salicylic acid (ASA)). The prediction results and figures of merit obtained with the new algorithm were compared with those obtained with U-PLS/RBL (without intervals selection), and with the well-known parallel factors analysis (PARAFAC). In all cases, U-PLS/RBL displayedbetter EEM handling capability in the presence of inner filter effectas compared to PARAFAC. In addition, iSPA improved the results obtained with U-PLS/RBL, in this case demonstrating the potential of variable selection.
Fil: de Araújo Gomes, Adriano. Departamento de Química, Universidad Federal de Paraíba;
Fil: Schenone, Agustina Violeta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina
Fil: Araújo, Mario Cesar. Departamento de Química, Universidad Federal de Paraíba;
Materia
Interval Selection
Successive Projections Algorithm
Unfolded-Partial Least Squares
Second Order Calibration
Inner Filter Effect
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/23071
Acceder
id CONICETDig_0a32c441c1d816f9527ca615eaddec1c
oai_identifier_str oai:ri.conicet.gov.ar:11336/23071
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effectde Araújo Gomes, AdrianoSchenone, Agustina VioletaGoicoechea, Hector CasimiroAraújo, Mario CesarInterval SelectionSuccessive Projections AlgorithmUnfolded-Partial Least SquaresSecond Order CalibrationInner Filter Effecthttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM),when under inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. Inner filter effectcan originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods. The algorithm presented in this paper was named iSPA-U-PLS/RBL. Both simulated and experimental data sets were used to compare the prediction capability during: a) simulated EEM; and b) quantitation of phenylephrine (PHE) in the presence of paracetamol (PAR) (or acetaminophen) in water samples. Test sets containing unexpected components were built in both systems (a single interference was taken into account in the simulated data set, while water samples were added with varying amounts of ibuprofen (IBU), and acetyl salicylic acid (ASA)). The prediction results and figures of merit obtained with the new algorithm were compared with those obtained with U-PLS/RBL (without intervals selection), and with the well-known parallel factors analysis (PARAFAC). In all cases, U-PLS/RBL displayedbetter EEM handling capability in the presence of inner filter effectas compared to PARAFAC. In addition, iSPA improved the results obtained with U-PLS/RBL, in this case demonstrating the potential of variable selection.Fil: de Araújo Gomes, Adriano. Departamento de Química, Universidad Federal de Paraíba;Fil: Schenone, Agustina Violeta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; ArgentinaFil: Araújo, Mario Cesar. Departamento de Química, Universidad Federal de Paraíba;Springer Heidelberg2015-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/23071de Araújo Gomes, Adriano; Schenone, Agustina Violeta; Goicoechea, Hector Casimiro; Araújo, Mario Cesar; Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect; Springer Heidelberg; Analytical and Bioanalytical Chemistry; 407; 19; 5-2015; 5649-56591618-2642CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007/s00216-015-8745-8info:eu-repo/semantics/altIdentifier/doi/10.1007/s00216-015-8745-8info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:39:47Zoai:ri.conicet.gov.ar:11336/23071instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:39:48.022CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
title Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
spellingShingle Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
de Araújo Gomes, Adriano
Interval Selection
Successive Projections Algorithm
Unfolded-Partial Least Squares
Second Order Calibration
Inner Filter Effect
title_short Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
title_full Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
title_fullStr Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
title_full_unstemmed Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
title_sort Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect
dc.creator.none.fl_str_mv de Araújo Gomes, Adriano
Schenone, Agustina Violeta
Goicoechea, Hector Casimiro
Araújo, Mario Cesar
author de Araújo Gomes, Adriano
author_facet de Araújo Gomes, Adriano
Schenone, Agustina Violeta
Goicoechea, Hector Casimiro
Araújo, Mario Cesar
author_role author
author2 Schenone, Agustina Violeta
Goicoechea, Hector Casimiro
Araújo, Mario Cesar
author2_role author
author
author
dc.subject.none.fl_str_mv Interval Selection
Successive Projections Algorithm
Unfolded-Partial Least Squares
Second Order Calibration
Inner Filter Effect
topic Interval Selection
Successive Projections Algorithm
Unfolded-Partial Least Squares
Second Order Calibration
Inner Filter Effect
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM),when under inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. Inner filter effectcan originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods. The algorithm presented in this paper was named iSPA-U-PLS/RBL. Both simulated and experimental data sets were used to compare the prediction capability during: a) simulated EEM; and b) quantitation of phenylephrine (PHE) in the presence of paracetamol (PAR) (or acetaminophen) in water samples. Test sets containing unexpected components were built in both systems (a single interference was taken into account in the simulated data set, while water samples were added with varying amounts of ibuprofen (IBU), and acetyl salicylic acid (ASA)). The prediction results and figures of merit obtained with the new algorithm were compared with those obtained with U-PLS/RBL (without intervals selection), and with the well-known parallel factors analysis (PARAFAC). In all cases, U-PLS/RBL displayedbetter EEM handling capability in the presence of inner filter effectas compared to PARAFAC. In addition, iSPA improved the results obtained with U-PLS/RBL, in this case demonstrating the potential of variable selection.
Fil: de Araújo Gomes, Adriano. Departamento de Química, Universidad Federal de Paraíba;
Fil: Schenone, Agustina Violeta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina
Fil: Araújo, Mario Cesar. Departamento de Química, Universidad Federal de Paraíba;
description The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM),when under inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. Inner filter effectcan originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods. The algorithm presented in this paper was named iSPA-U-PLS/RBL. Both simulated and experimental data sets were used to compare the prediction capability during: a) simulated EEM; and b) quantitation of phenylephrine (PHE) in the presence of paracetamol (PAR) (or acetaminophen) in water samples. Test sets containing unexpected components were built in both systems (a single interference was taken into account in the simulated data set, while water samples were added with varying amounts of ibuprofen (IBU), and acetyl salicylic acid (ASA)). The prediction results and figures of merit obtained with the new algorithm were compared with those obtained with U-PLS/RBL (without intervals selection), and with the well-known parallel factors analysis (PARAFAC). In all cases, U-PLS/RBL displayedbetter EEM handling capability in the presence of inner filter effectas compared to PARAFAC. In addition, iSPA improved the results obtained with U-PLS/RBL, in this case demonstrating the potential of variable selection.
publishDate 2015
dc.date.none.fl_str_mv 2015-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/23071
de Araújo Gomes, Adriano; Schenone, Agustina Violeta; Goicoechea, Hector Casimiro; Araújo, Mario Cesar; Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect; Springer Heidelberg; Analytical and Bioanalytical Chemistry; 407; 19; 5-2015; 5649-5659
1618-2642
CONICET Digital
CONICET
url http://hdl.handle.net/11336/23071
identifier_str_mv de Araújo Gomes, Adriano; Schenone, Agustina Violeta; Goicoechea, Hector Casimiro; Araújo, Mario Cesar; Unfolded partial least squares/residual bilinearizationcombined with the Successive Projections Algorithmfor interval selection:enhanced excitation-emission fluorescence data modeling in presence of inner filter effect; Springer Heidelberg; Analytical and Bioanalytical Chemistry; 407; 19; 5-2015; 5649-5659
1618-2642
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007/s00216-015-8745-8
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00216-015-8745-8
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer Heidelberg
publisher.none.fl_str_mv Springer Heidelberg
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613259107237888
score 13.069144

Publicaciones similares