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

Publication date: 1 May 2018
Source:Talanta, Volume 181
Author(s): Valber Elias de Almeida, Adriano de Araújo Gomes, David Douglas de Sousa Fernandes, Héctor Casimiro Goicoechea, Roberto Kawakami Harrop Galvão, Mario Cesar Ugulino Araújo
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.

Graphical abstract

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