Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data

Autores
Bortolato, Santiago Andres; Lozano, Valeria Antonella; Muñoz de la Peña, Arsenio; Olivieri, Alejandro Cesar
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A new augmented parallel factor analysis model (Augmented PARAFAC) is presented, inspired by the useful augmentation concept employed in multivariate curve resolution-alternating least-squares (MCR-ALS), applicable to calibration based on non-quadrilinear four-way data, such as those produced by high-performance liquid chromatography with matrix excitation–emission fluorescence detection. The new model involves creating an augmented three-way array in the elution time direction, containing data for the calibration sample set and for each of the test samples, subsequently analyzed with an Augmented PARAFAC version. To test the properties of this approach, chromatographic data were simulated with different degrees of overlapping and misalignment among the chromatographic peaks. Additionally, experimental data from olive oil samples were tested with the new model, aimed at the quantitation of the level of chlorophylls and pheophytins. The results were compared with those obtained by data processing with MCR-ALS. Relative prediction errors (%) were: Augmented PARAFAC, 9.7, 21.0, 14.7 and 9.3, and MCR-ALS, 5.9, 14.5, 20.0 and 14.7 for Chl a, Chl b, Phe a Phe b, respectively, for concentrations in the range 0.00–1.00 μg mL− 1. Both MCR-ALS and Augmented PARAFAC allow one to obtain a detailed and realistic description of the analyzed samples, in terms of pure elution time, excitation and emission spectral profiles, which can be independently retrieved for every component.
Fil: Bortolato, Santiago Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Fil: Lozano, Valeria Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina
Fil: Muñoz de la Peña, Arsenio. Universidad de Extremadura; España
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina
Materia
Liquid Chromatography-Excitation-Emission Fluorescence Data
Multi-Way Calibration
Augmented Parallel Factor Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/5993
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/5993
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission DataBortolato, Santiago AndresLozano, Valeria AntonellaMuñoz de la Peña, ArsenioOlivieri, Alejandro CesarLiquid Chromatography-Excitation-Emission Fluorescence DataMulti-Way CalibrationAugmented Parallel Factor Analysishttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1A new augmented parallel factor analysis model (Augmented PARAFAC) is presented, inspired by the useful augmentation concept employed in multivariate curve resolution-alternating least-squares (MCR-ALS), applicable to calibration based on non-quadrilinear four-way data, such as those produced by high-performance liquid chromatography with matrix excitation–emission fluorescence detection. The new model involves creating an augmented three-way array in the elution time direction, containing data for the calibration sample set and for each of the test samples, subsequently analyzed with an Augmented PARAFAC version. To test the properties of this approach, chromatographic data were simulated with different degrees of overlapping and misalignment among the chromatographic peaks. Additionally, experimental data from olive oil samples were tested with the new model, aimed at the quantitation of the level of chlorophylls and pheophytins. The results were compared with those obtained by data processing with MCR-ALS. Relative prediction errors (%) were: Augmented PARAFAC, 9.7, 21.0, 14.7 and 9.3, and MCR-ALS, 5.9, 14.5, 20.0 and 14.7 for Chl a, Chl b, Phe a Phe b, respectively, for concentrations in the range 0.00–1.00 μg mL− 1. Both MCR-ALS and Augmented PARAFAC allow one to obtain a detailed and realistic description of the analyzed samples, in terms of pure elution time, excitation and emission spectral profiles, which can be independently retrieved for every component.Fil: Bortolato, Santiago Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); ArgentinaFil: Lozano, Valeria Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; ArgentinaFil: Muñoz de la Peña, Arsenio. Universidad de Extremadura; EspañaFil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; ArgentinaElsevier2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/5993Bortolato, Santiago Andres; Lozano, Valeria Antonella; Muñoz de la Peña, Arsenio; Olivieri, Alejandro Cesar; Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data; Elsevier; Chemometrics and Intelligent Laboratory Systems; 141; 3-2015; 1-110169-7439enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0169743914002469info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2014.11.013info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:38:53Zoai:ri.conicet.gov.ar:11336/5993instacron: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 09:38:54.269CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
title Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
spellingShingle Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
Bortolato, Santiago Andres
Liquid Chromatography-Excitation-Emission Fluorescence Data
Multi-Way Calibration
Augmented Parallel Factor Analysis
title_short Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
title_full Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
title_fullStr Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
title_full_unstemmed Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
title_sort Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data
dc.creator.none.fl_str_mv Bortolato, Santiago Andres
Lozano, Valeria Antonella
Muñoz de la Peña, Arsenio
Olivieri, Alejandro Cesar
author Bortolato, Santiago Andres
author_facet Bortolato, Santiago Andres
Lozano, Valeria Antonella
Muñoz de la Peña, Arsenio
Olivieri, Alejandro Cesar
author_role author
author2 Lozano, Valeria Antonella
Muñoz de la Peña, Arsenio
Olivieri, Alejandro Cesar
author2_role author
author
author
dc.subject.none.fl_str_mv Liquid Chromatography-Excitation-Emission Fluorescence Data
Multi-Way Calibration
Augmented Parallel Factor Analysis
topic Liquid Chromatography-Excitation-Emission Fluorescence Data
Multi-Way Calibration
Augmented Parallel Factor Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A new augmented parallel factor analysis model (Augmented PARAFAC) is presented, inspired by the useful augmentation concept employed in multivariate curve resolution-alternating least-squares (MCR-ALS), applicable to calibration based on non-quadrilinear four-way data, such as those produced by high-performance liquid chromatography with matrix excitation–emission fluorescence detection. The new model involves creating an augmented three-way array in the elution time direction, containing data for the calibration sample set and for each of the test samples, subsequently analyzed with an Augmented PARAFAC version. To test the properties of this approach, chromatographic data were simulated with different degrees of overlapping and misalignment among the chromatographic peaks. Additionally, experimental data from olive oil samples were tested with the new model, aimed at the quantitation of the level of chlorophylls and pheophytins. The results were compared with those obtained by data processing with MCR-ALS. Relative prediction errors (%) were: Augmented PARAFAC, 9.7, 21.0, 14.7 and 9.3, and MCR-ALS, 5.9, 14.5, 20.0 and 14.7 for Chl a, Chl b, Phe a Phe b, respectively, for concentrations in the range 0.00–1.00 μg mL− 1. Both MCR-ALS and Augmented PARAFAC allow one to obtain a detailed and realistic description of the analyzed samples, in terms of pure elution time, excitation and emission spectral profiles, which can be independently retrieved for every component.
Fil: Bortolato, Santiago Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Fil: Lozano, Valeria Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina
Fil: Muñoz de la Peña, Arsenio. Universidad de Extremadura; España
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina
description A new augmented parallel factor analysis model (Augmented PARAFAC) is presented, inspired by the useful augmentation concept employed in multivariate curve resolution-alternating least-squares (MCR-ALS), applicable to calibration based on non-quadrilinear four-way data, such as those produced by high-performance liquid chromatography with matrix excitation–emission fluorescence detection. The new model involves creating an augmented three-way array in the elution time direction, containing data for the calibration sample set and for each of the test samples, subsequently analyzed with an Augmented PARAFAC version. To test the properties of this approach, chromatographic data were simulated with different degrees of overlapping and misalignment among the chromatographic peaks. Additionally, experimental data from olive oil samples were tested with the new model, aimed at the quantitation of the level of chlorophylls and pheophytins. The results were compared with those obtained by data processing with MCR-ALS. Relative prediction errors (%) were: Augmented PARAFAC, 9.7, 21.0, 14.7 and 9.3, and MCR-ALS, 5.9, 14.5, 20.0 and 14.7 for Chl a, Chl b, Phe a Phe b, respectively, for concentrations in the range 0.00–1.00 μg mL− 1. Both MCR-ALS and Augmented PARAFAC allow one to obtain a detailed and realistic description of the analyzed samples, in terms of pure elution time, excitation and emission spectral profiles, which can be independently retrieved for every component.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
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/11336/5993
Bortolato, Santiago Andres; Lozano, Valeria Antonella; Muñoz de la Peña, Arsenio; Olivieri, Alejandro Cesar; Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data; Elsevier; Chemometrics and Intelligent Laboratory Systems; 141; 3-2015; 1-11
0169-7439
url http://hdl.handle.net/11336/5993
identifier_str_mv Bortolato, Santiago Andres; Lozano, Valeria Antonella; Muñoz de la Peña, Arsenio; Olivieri, Alejandro Cesar; Novel Augmented Parallel Factor Model for Four-Way Calibration of High-Performance Liquid Chromatography-Fluorescence Excitation-Emission Data; Elsevier; Chemometrics and Intelligent Laboratory Systems; 141; 3-2015; 1-11
0169-7439
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0169743914002469
info:eu-repo/semantics/altIdentifier/doi/
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2014.11.013
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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score 13.070432

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