Comparison of various chemometric approaches for large near infrared spectroscopic data of feed and feed products

J A Fernández Pierna; B Lecler; J P Conzen; A Niemoeller; V Baeten; P Dardenne

doi:10.1016/j.aca.2011.03.023

Comparison of various chemometric approaches for large near infrared spectroscopic data of feed and feed products

Anal Chim Acta. 2011 Oct 31;705(1-2):30-4. doi: 10.1016/j.aca.2011.03.023. Epub 2011 Mar 16.

Authors

J A Fernández Pierna¹, B Lecler, J P Conzen, A Niemoeller, V Baeten, P Dardenne

Affiliation

¹ Walloon Agricultural Research Centre (CRA-W), Valorisation of Agricultural Products Department, Food and Feed Quality Unit (U15), Henseval building, Chaussée de Namur 24, 5030 Gembloux, Belgium. fernandez@cra.wallonie.be

PMID: 21962344
DOI: 10.1016/j.aca.2011.03.023

Abstract

In the present study, different multivariate regression techniques have been applied to two large near-infrared data sets of feed and feed ingredients in order to fulfil the regulations and laws that exist about the chemical composition of these products. The aim of this paper was to compare the performances of different linear and nonlinear multivariate calibration techniques: PLS, ANN and LS-SVM. The results obtained show that ANN and LS-SVM are very powerful methods for non-linearity but LS-SVM can also perform quite well in the case of linear models. Using LS-SVM an improvement of the RMS for independent test sets of 10% is obtained in average compared to ANN and of 24% compared to PLS.