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dc.contributor.author
Sorol, Natalia Raquel
dc.contributor.author
Arancibia, Eleuterio Luis
dc.contributor.author
Bortolato, Santiago Andres
dc.contributor.author
Olivieri, Alejandro Cesar
dc.date.available
2018-07-23T20:25:45Z
dc.date.issued
2010-07
dc.identifier.citation
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
dc.identifier.issn
0169-7439
dc.identifier.uri
http://hdl.handle.net/11336/52919
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
Brix Degrees
dc.subject
Partial Least-Squares
dc.subject
Sugar Cane Juice Analysis
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Variable Selection
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Vis-Nir Spectroscopy
dc.subject.classification
Otras Ciencias Químicas
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Ciencias Químicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-07-23T13:51:18Z
dc.journal.volume
102
dc.journal.number
2
dc.journal.pagination
100-109
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Sorol, Natalia Raquel. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; Argentina
dc.description.fil
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
dc.description.fil
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
dc.description.fil
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
dc.journal.title
Chemometrics and Intelligent Laboratory Systems
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1016/j.chemolab.2010.04.009
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0169743910000584
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