Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods

Autores
Sorol, Natalia Raquel; Arancibia, Eleuterio Luis; Bortolato, Santiago Andres; Olivieri, Alejandro Cesar
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Several variable selection algorithms were applied in order to sort informative wavelengths for building a partial least-squares (PLS) model relating visible/near infrared spectra to Brix degrees in samples of sugar cane juice. Two types of selection methods were explored. A first group was based on the PLS regression coefficients, such as the selection of coefficients significantly larger than their uncertainties, the estimation of the variable importance in projection (VIP), and uninformative variable elimination (UVE). The second group involves minimum error searches conducted through interval PLS (i-PLS), variable-size moving-window (VS-MW), genetic algorithms (GA) and particle swarm optimization (PSO). The best results were obtained using the latter two methodologies, both based on applications of natural computation. The results furnished by inspection of the spectrum of regression coefficients may be dangerous, in general, for selecting informative variables. This important fact has been confirmed by analysis of a set of simulated data mimicking the experimental sugar cane juice spectra.
Fil: Sorol, Natalia Raquel. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; Argentina
Fil: Arancibia, Eleuterio Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina
Fil: Bortolato, Santiago Andres. 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
Brix Degrees
Partial Least-Squares
Sugar Cane Juice Analysis
Variable Selection
Vis-Nir Spectroscopy
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:11336/52919
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/52919
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methodsSorol, Natalia RaquelArancibia, Eleuterio LuisBortolato, Santiago AndresOlivieri, Alejandro CesarBrix DegreesPartial Least-SquaresSugar Cane Juice AnalysisVariable SelectionVis-Nir Spectroscopyhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Several variable selection algorithms were applied in order to sort informative wavelengths for building a partial least-squares (PLS) model relating visible/near infrared spectra to Brix degrees in samples of sugar cane juice. Two types of selection methods were explored. A first group was based on the PLS regression coefficients, such as the selection of coefficients significantly larger than their uncertainties, the estimation of the variable importance in projection (VIP), and uninformative variable elimination (UVE). The second group involves minimum error searches conducted through interval PLS (i-PLS), variable-size moving-window (VS-MW), genetic algorithms (GA) and particle swarm optimization (PSO). The best results were obtained using the latter two methodologies, both based on applications of natural computation. The results furnished by inspection of the spectrum of regression coefficients may be dangerous, in general, for selecting informative variables. This important fact has been confirmed by analysis of a set of simulated data mimicking the experimental sugar cane juice spectra.Fil: Sorol, Natalia Raquel. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; ArgentinaFil: Arancibia, Eleuterio Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; ArgentinaFil: Bortolato, Santiago Andres. 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 Science2010-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/52919Sorol, Natalia Raquel; Arancibia, Eleuterio Luis; Bortolato, Santiago Andres; Olivieri, Alejandro Cesar; Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods; Elsevier Science; Chemometrics and Intelligent Laboratory Systems; 102; 2; 7-2010; 100-1090169-7439CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2010.04.009info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0169743910000584info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:51:09Zoai:ri.conicet.gov.ar:11336/52919instacron: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 14:51:09.608CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
title Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
spellingShingle Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
Sorol, Natalia Raquel
Brix Degrees
Partial Least-Squares
Sugar Cane Juice Analysis
Variable Selection
Vis-Nir Spectroscopy
title_short Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
title_full Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
title_fullStr Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
title_full_unstemmed Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
title_sort Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
dc.creator.none.fl_str_mv Sorol, Natalia Raquel
Arancibia, Eleuterio Luis
Bortolato, Santiago Andres
Olivieri, Alejandro Cesar
author Sorol, Natalia Raquel
author_facet Sorol, Natalia Raquel
Arancibia, Eleuterio Luis
Bortolato, Santiago Andres
Olivieri, Alejandro Cesar
author_role author
author2 Arancibia, Eleuterio Luis
Bortolato, Santiago Andres
Olivieri, Alejandro Cesar
author2_role author
author
author
dc.subject.none.fl_str_mv Brix Degrees
Partial Least-Squares
Sugar Cane Juice Analysis
Variable Selection
Vis-Nir Spectroscopy
topic Brix Degrees
Partial Least-Squares
Sugar Cane Juice Analysis
Variable Selection
Vis-Nir Spectroscopy
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Several variable selection algorithms were applied in order to sort informative wavelengths for building a partial least-squares (PLS) model relating visible/near infrared spectra to Brix degrees in samples of sugar cane juice. Two types of selection methods were explored. A first group was based on the PLS regression coefficients, such as the selection of coefficients significantly larger than their uncertainties, the estimation of the variable importance in projection (VIP), and uninformative variable elimination (UVE). The second group involves minimum error searches conducted through interval PLS (i-PLS), variable-size moving-window (VS-MW), genetic algorithms (GA) and particle swarm optimization (PSO). The best results were obtained using the latter two methodologies, both based on applications of natural computation. The results furnished by inspection of the spectrum of regression coefficients may be dangerous, in general, for selecting informative variables. This important fact has been confirmed by analysis of a set of simulated data mimicking the experimental sugar cane juice spectra.
Fil: Sorol, Natalia Raquel. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; Argentina
Fil: Arancibia, Eleuterio Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina
Fil: Bortolato, Santiago Andres. 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 Several variable selection algorithms were applied in order to sort informative wavelengths for building a partial least-squares (PLS) model relating visible/near infrared spectra to Brix degrees in samples of sugar cane juice. Two types of selection methods were explored. A first group was based on the PLS regression coefficients, such as the selection of coefficients significantly larger than their uncertainties, the estimation of the variable importance in projection (VIP), and uninformative variable elimination (UVE). The second group involves minimum error searches conducted through interval PLS (i-PLS), variable-size moving-window (VS-MW), genetic algorithms (GA) and particle swarm optimization (PSO). The best results were obtained using the latter two methodologies, both based on applications of natural computation. The results furnished by inspection of the spectrum of regression coefficients may be dangerous, in general, for selecting informative variables. This important fact has been confirmed by analysis of a set of simulated data mimicking the experimental sugar cane juice spectra.
publishDate 2010
dc.date.none.fl_str_mv 2010-07
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/11336/52919
Sorol, Natalia Raquel; Arancibia, Eleuterio Luis; Bortolato, Santiago Andres; Olivieri, Alejandro Cesar; Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods; Elsevier Science; Chemometrics and Intelligent Laboratory Systems; 102; 2; 7-2010; 100-109
0169-7439
CONICET Digital
CONICET
url http://hdl.handle.net/11336/52919
identifier_str_mv Sorol, Natalia Raquel; Arancibia, Eleuterio Luis; Bortolato, Santiago Andres; Olivieri, Alejandro Cesar; Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods; Elsevier Science; Chemometrics and Intelligent Laboratory Systems; 102; 2; 7-2010; 100-109
0169-7439
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2010.04.009
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0169743910000584
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
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
_version_ 1846083037421371392
score 13.22299

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