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.

Author affiliation: Sorol, Natalia. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; Argentina

Author affiliation: 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

Author affiliation: 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

Author affiliation: 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