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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/7361
Ver los metadatos del registro completo
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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 Técnicas2025-09-29T10:10:37Zoai: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:34982025-09-29 10:10:37.698CONICET 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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1844613996984926208 |
score |
13.070432 |