The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares

Autores
Pellegrino Vidal, Rocio; Allegrini, Franco; Olivieri, Alejandro Cesar
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained.
Fil: Pellegrino Vidal, Rocio. 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: Allegrini, Franco. 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: Olivieri, Alejandro Cesar. 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
ANALYTICAL FIGURES OF MERIT
CONSTRAINTS
MULTIVARIATE CURVE RESOLUTION
SENSITIVITY
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:11336/87344
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squaresPellegrino Vidal, RocioAllegrini, FrancoOlivieri, Alejandro CesarANALYTICAL FIGURES OF MERITCONSTRAINTSMULTIVARIATE CURVE RESOLUTIONSENSITIVITYhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained.Fil: Pellegrino Vidal, Rocio. 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: Allegrini, Franco. 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: Olivieri, Alejandro Cesar. 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; ArgentinaElsevier Science2018-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/87344Pellegrino Vidal, Rocio; Allegrini, Franco; Olivieri, Alejandro Cesar; The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares; Elsevier Science; Analytica Chimica Acta; 1003; 3-2018; 10-150003-2670CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0003267017314198info:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2017.12.008info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:44:43Zoai:ri.conicet.gov.ar:11336/87344instacron: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:34982025-09-03 09:44:43.901CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
title The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
spellingShingle The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
Pellegrino Vidal, Rocio
ANALYTICAL FIGURES OF MERIT
CONSTRAINTS
MULTIVARIATE CURVE RESOLUTION
SENSITIVITY
title_short The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
title_full The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
title_fullStr The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
title_full_unstemmed The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
title_sort The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares
dc.creator.none.fl_str_mv Pellegrino Vidal, Rocio
Allegrini, Franco
Olivieri, Alejandro Cesar
author Pellegrino Vidal, Rocio
author_facet Pellegrino Vidal, Rocio
Allegrini, Franco
Olivieri, Alejandro Cesar
author_role author
author2 Allegrini, Franco
Olivieri, Alejandro Cesar
author2_role author
author
dc.subject.none.fl_str_mv ANALYTICAL FIGURES OF MERIT
CONSTRAINTS
MULTIVARIATE CURVE RESOLUTION
SENSITIVITY
topic ANALYTICAL FIGURES OF MERIT
CONSTRAINTS
MULTIVARIATE CURVE RESOLUTION
SENSITIVITY
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained.
Fil: Pellegrino Vidal, Rocio. 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: Allegrini, Franco. 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: Olivieri, Alejandro Cesar. 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 Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained.
publishDate 2018
dc.date.none.fl_str_mv 2018-03
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/11336/87344
Pellegrino Vidal, Rocio; Allegrini, Franco; Olivieri, Alejandro Cesar; The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares; Elsevier Science; Analytica Chimica Acta; 1003; 3-2018; 10-15
0003-2670
CONICET Digital
CONICET
url http://hdl.handle.net/11336/87344
identifier_str_mv Pellegrino Vidal, Rocio; Allegrini, Franco; Olivieri, Alejandro Cesar; The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares; Elsevier Science; Analytica Chimica Acta; 1003; 3-2018; 10-15
0003-2670
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0003267017314198
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2017.12.008
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
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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 13.033874

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