A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples

Autores
Alcaraz, Mirta Raquel; Bortolato, Santiago Andres; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation-emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.
Fil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Bortolato, Santiago Andres. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina
Fil: Olivieri, Alejandro Cesar. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Materia
Augmented Parallel Factor Analysis
Fluoroquinolones
Liquid Chromatography
Third-Order Data
Water Samples
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:11336/37745
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samplesAlcaraz, Mirta RaquelBortolato, Santiago AndresGoicoechea, Hector CasimiroOlivieri, Alejandro CesarAugmented Parallel Factor AnalysisFluoroquinolonesLiquid ChromatographyThird-Order DataWater Sampleshttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation-emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.Fil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bortolato, Santiago Andres. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; ArgentinaFil: Olivieri, Alejandro Cesar. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaSpringer Heidelberg2015-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/37745Alcaraz, Mirta Raquel; Bortolato, Santiago Andres; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar; A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples; Springer Heidelberg; Analytical and Bioanalytical Chemistry; 407; 7; 2-2015; 1999-20111618-26421618-2650CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs00216-014-8442-zinfo:eu-repo/semantics/altIdentifier/doi/10.1007/s00216-014-8442-zinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:54:37Zoai:ri.conicet.gov.ar:11336/37745instacron: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 09:54:37.322CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
title A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
spellingShingle A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
Alcaraz, Mirta Raquel
Augmented Parallel Factor Analysis
Fluoroquinolones
Liquid Chromatography
Third-Order Data
Water Samples
title_short A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
title_full A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
title_fullStr A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
title_full_unstemmed A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
title_sort A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples
dc.creator.none.fl_str_mv Alcaraz, Mirta Raquel
Bortolato, Santiago Andres
Goicoechea, Hector Casimiro
Olivieri, Alejandro Cesar
author Alcaraz, Mirta Raquel
author_facet Alcaraz, Mirta Raquel
Bortolato, Santiago Andres
Goicoechea, Hector Casimiro
Olivieri, Alejandro Cesar
author_role author
author2 Bortolato, Santiago Andres
Goicoechea, Hector Casimiro
Olivieri, Alejandro Cesar
author2_role author
author
author
dc.subject.none.fl_str_mv Augmented Parallel Factor Analysis
Fluoroquinolones
Liquid Chromatography
Third-Order Data
Water Samples
topic Augmented Parallel Factor Analysis
Fluoroquinolones
Liquid Chromatography
Third-Order Data
Water Samples
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation-emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.
Fil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Bortolato, Santiago Andres. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina
Fil: Olivieri, Alejandro Cesar. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
description Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation-emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.
publishDate 2015
dc.date.none.fl_str_mv 2015-02
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/11336/37745
Alcaraz, Mirta Raquel; Bortolato, Santiago Andres; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar; A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples; Springer Heidelberg; Analytical and Bioanalytical Chemistry; 407; 7; 2-2015; 1999-2011
1618-2642
1618-2650
CONICET Digital
CONICET
url http://hdl.handle.net/11336/37745
identifier_str_mv Alcaraz, Mirta Raquel; Bortolato, Santiago Andres; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar; A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection: Quantitation of fluoroquinolones in water samples; Springer Heidelberg; Analytical and Bioanalytical Chemistry; 407; 7; 2-2015; 1999-2011
1618-2642
1618-2650
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%2Fs00216-014-8442-z
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00216-014-8442-z
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
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
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