Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm

DE ALMEIDA, VALBER ELIAS; DE ARAÚJO GOMES, ADRIANO; DE SOUSA FERNANDES, DAVID DOUGLAS; GOICOECHEA, HÉCTOR CASIMIRO; GALVÃO, ROBERTO KAWAKAMI HARROP; ARAÚJO, MARIO CESAR UGULINO

TALANTA

ELSEVIER SCIENCE BV

Año: 2018 vol. 181 p. 38 - 43

0039-9140

This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) modelling technique. The proposed iSPA-Kernel-PLS algorithm is employed in a case study involving a Vis-NIR spectrometric dataset with complex nonlinear features. The analytical problem consists of determining Brix and sucrose content in samples from a sugar production system, on the basis of transflectance spectra. As compared to full-spectrum Kernel-PLS, the iSPA-Kernel-PLS models involve a smaller number of variables and display statistically significant superiority in terms of accuracy and/or bias in the predictions