INQUINOA   21218
INSTITUTO DE QUIMICA DEL NOROESTE
Unidad Ejecutora - UE
artículos
Título:
Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice
Autor/es:
NATALIA SOROL, ELEUTERIO ARANCIBIA, SANTIAGO A. BERTOLATO, ALEJANDRO C. OLIVIERI
Revista:
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Año: 2010
ISSN:
0169-7439
Resumen:
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 prediction (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.