Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution

Autores
Pisano, Pablo Luis; Silva, Maria Fernanda; Olivieri, Alejandro Cesar
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Second-order data were measured using high-performance liquid-chromatography with diode array detection (HPLC-DAD) for a number of wine samples, which were directly injected in the HPLC-DAD system without sample pre-treatment. The data were arranged in data matrices whose modes were elution time and UV–visible absorption wavelength, and processed by extended multivariate curve resolution coupled to alternating leastsquares (MCR–ALS). The individual data matrices were organized in a row-wise augmented data matrix sharing the time subspace, due to the high spectral similarity among several sample components. This required previous time alignment of the chromatograms using a suitable synchronization algorithm, in order to produce a bilinear augmented data matrix to be processed by MCR–ALS. The latter algorithm led to resolved component chromatograms and spectra, from which component scores could be estimated, which are proportional to the relative component concentrations in each studied sample. The matrix of sample scores was then submitted to principal component analysis, which was applied for data exploration according to grape varietal and geographical origin. The results showed that the present data generation and analysis are useful for the discrimination of all samples of the Malbec varietal from the remaining ones, but achieved partial success regarding geographical origin.
Fil: Pisano, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina
Fil: Silva, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mendoza. Instituto de Biología Agrícola de Mendoza; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina
Materia
Liquid Chromatography
Multivariate Curve Resolution
Principal Component Analysis
Direct Injection
Wine Data Exploration
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:11336/7361
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolutionPisano, Pablo LuisSilva, Maria FernandaOlivieri, Alejandro CesarLiquid ChromatographyMultivariate Curve ResolutionPrincipal Component AnalysisDirect InjectionWine Data Explorationhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Second-order data were measured using high-performance liquid-chromatography with diode array detection (HPLC-DAD) for a number of wine samples, which were directly injected in the HPLC-DAD system without sample pre-treatment. The data were arranged in data matrices whose modes were elution time and UV–visible absorption wavelength, and processed by extended multivariate curve resolution coupled to alternating leastsquares (MCR–ALS). The individual data matrices were organized in a row-wise augmented data matrix sharing the time subspace, due to the high spectral similarity among several sample components. This required previous time alignment of the chromatograms using a suitable synchronization algorithm, in order to produce a bilinear augmented data matrix to be processed by MCR–ALS. The latter algorithm led to resolved component chromatograms and spectra, from which component scores could be estimated, which are proportional to the relative component concentrations in each studied sample. The matrix of sample scores was then submitted to principal component analysis, which was applied for data exploration according to grape varietal and geographical origin. The results showed that the present data generation and analysis are useful for the discrimination of all samples of the Malbec varietal from the remaining ones, but achieved partial success regarding geographical origin.Fil: Pisano, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; ArgentinaFil: Silva, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mendoza. Instituto de Biología Agrícola de Mendoza; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; ArgentinaFil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; ArgentinaElsevier Science2014-01-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/7361Pisano, Pablo Luis; Silva, Maria Fernanda; Olivieri, Alejandro Cesar; Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution; Elsevier Science; Chemometrics And Intelligent Laboratory Systems; 132; 7-1-2014; 1-70169-7439enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0169743913002402info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2013.12.010info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:07:49Zoai:ri.conicet.gov.ar:11336/7361instacron: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 15:07:49.745CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
title Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
spellingShingle Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
Pisano, Pablo Luis
Liquid Chromatography
Multivariate Curve Resolution
Principal Component Analysis
Direct Injection
Wine Data Exploration
title_short Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
title_full Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
title_fullStr Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
title_full_unstemmed Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
title_sort Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution
dc.creator.none.fl_str_mv Pisano, Pablo Luis
Silva, Maria Fernanda
Olivieri, Alejandro Cesar
author Pisano, Pablo Luis
author_facet Pisano, Pablo Luis
Silva, Maria Fernanda
Olivieri, Alejandro Cesar
author_role author
author2 Silva, Maria Fernanda
Olivieri, Alejandro Cesar
author2_role author
author
dc.subject.none.fl_str_mv Liquid Chromatography
Multivariate Curve Resolution
Principal Component Analysis
Direct Injection
Wine Data Exploration
topic Liquid Chromatography
Multivariate Curve Resolution
Principal Component Analysis
Direct Injection
Wine Data Exploration
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Second-order data were measured using high-performance liquid-chromatography with diode array detection (HPLC-DAD) for a number of wine samples, which were directly injected in the HPLC-DAD system without sample pre-treatment. The data were arranged in data matrices whose modes were elution time and UV–visible absorption wavelength, and processed by extended multivariate curve resolution coupled to alternating leastsquares (MCR–ALS). The individual data matrices were organized in a row-wise augmented data matrix sharing the time subspace, due to the high spectral similarity among several sample components. This required previous time alignment of the chromatograms using a suitable synchronization algorithm, in order to produce a bilinear augmented data matrix to be processed by MCR–ALS. The latter algorithm led to resolved component chromatograms and spectra, from which component scores could be estimated, which are proportional to the relative component concentrations in each studied sample. The matrix of sample scores was then submitted to principal component analysis, which was applied for data exploration according to grape varietal and geographical origin. The results showed that the present data generation and analysis are useful for the discrimination of all samples of the Malbec varietal from the remaining ones, but achieved partial success regarding geographical origin.
Fil: Pisano, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina
Fil: Silva, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mendoza. Instituto de Biología Agrícola de Mendoza; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina
description Second-order data were measured using high-performance liquid-chromatography with diode array detection (HPLC-DAD) for a number of wine samples, which were directly injected in the HPLC-DAD system without sample pre-treatment. The data were arranged in data matrices whose modes were elution time and UV–visible absorption wavelength, and processed by extended multivariate curve resolution coupled to alternating leastsquares (MCR–ALS). The individual data matrices were organized in a row-wise augmented data matrix sharing the time subspace, due to the high spectral similarity among several sample components. This required previous time alignment of the chromatograms using a suitable synchronization algorithm, in order to produce a bilinear augmented data matrix to be processed by MCR–ALS. The latter algorithm led to resolved component chromatograms and spectra, from which component scores could be estimated, which are proportional to the relative component concentrations in each studied sample. The matrix of sample scores was then submitted to principal component analysis, which was applied for data exploration according to grape varietal and geographical origin. The results showed that the present data generation and analysis are useful for the discrimination of all samples of the Malbec varietal from the remaining ones, but achieved partial success regarding geographical origin.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-07
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/11336/7361
Pisano, Pablo Luis; Silva, Maria Fernanda; Olivieri, Alejandro Cesar; Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution; Elsevier Science; Chemometrics And Intelligent Laboratory Systems; 132; 7-1-2014; 1-7
0169-7439
url http://hdl.handle.net/11336/7361
identifier_str_mv Pisano, Pablo Luis; Silva, Maria Fernanda; Olivieri, Alejandro Cesar; Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution; Elsevier Science; Chemometrics And Intelligent Laboratory Systems; 132; 7-1-2014; 1-7
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/S0169743913002402
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2013.12.010
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 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 13.22299

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