Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
- Autores
- Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar
- Año de publicación
- 2010
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches.
Fil: Lozano, Valeria Antonella. 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: Ibañez, Gabriela Alejandra. 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
-
SECOND-ORDER ADVANTAGE
PARTIAL LEAST-SQUARES
RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY
IDENTICAL PROFILES IN ONE DIMENSION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/127801
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CONICET Digital (CONICET) |
spelling |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization methodLozano, Valeria AntonellaIbañez, Gabriela AlejandraOlivieri, Alejandro CesarSECOND-ORDER ADVANTAGEPARTIAL LEAST-SQUARESRESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCYIDENTICAL PROFILES IN ONE DIMENSIONhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches.Fil: Lozano, Valeria Antonella. 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: Ibañez, Gabriela Alejandra. 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; ArgentinaAmerican Chemical Society2010-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/127801Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar; Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method; American Chemical Society; Analytical Chemistry; 82; 11; 6-2010; 4510-45190003-2700CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/abs/10.1021/ac100424dinfo:eu-repo/semantics/altIdentifier/doi/10.1021/ac100424dinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:29:17Zoai:ri.conicet.gov.ar:11336/127801instacron: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:34982025-10-15 15:29:18.161CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
title |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
spellingShingle |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method Lozano, Valeria Antonella SECOND-ORDER ADVANTAGE PARTIAL LEAST-SQUARES RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY IDENTICAL PROFILES IN ONE DIMENSION |
title_short |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
title_full |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
title_fullStr |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
title_full_unstemmed |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
title_sort |
Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method |
dc.creator.none.fl_str_mv |
Lozano, Valeria Antonella Ibañez, Gabriela Alejandra Olivieri, Alejandro Cesar |
author |
Lozano, Valeria Antonella |
author_facet |
Lozano, Valeria Antonella Ibañez, Gabriela Alejandra Olivieri, Alejandro Cesar |
author_role |
author |
author2 |
Ibañez, Gabriela Alejandra Olivieri, Alejandro Cesar |
author2_role |
author author |
dc.subject.none.fl_str_mv |
SECOND-ORDER ADVANTAGE PARTIAL LEAST-SQUARES RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY IDENTICAL PROFILES IN ONE DIMENSION |
topic |
SECOND-ORDER ADVANTAGE PARTIAL LEAST-SQUARES RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY IDENTICAL PROFILES IN ONE DIMENSION |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.4 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches. Fil: Lozano, Valeria Antonella. 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: Ibañez, Gabriela Alejandra. 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 |
Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-06 |
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/11336/127801 Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar; Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method; American Chemical Society; Analytical Chemistry; 82; 11; 6-2010; 4510-4519 0003-2700 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/127801 |
identifier_str_mv |
Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar; Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method; American Chemical Society; Analytical Chemistry; 82; 11; 6-2010; 4510-4519 0003-2700 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://pubs.acs.org/doi/abs/10.1021/ac100424d info:eu-repo/semantics/altIdentifier/doi/10.1021/ac100424d |
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 |
dc.publisher.none.fl_str_mv |
American Chemical Society |
publisher.none.fl_str_mv |
American Chemical Society |
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_ |
1846083432681046016 |
score |
13.22299 |