Please use this identifier to cite or link to this item:
|Type:||Artigo de periódico|
|Title:||Ls-svm: A New Chemometric Tool For Multivariate Regression. Comparison Of Ls-svm And Pls Regression For Determination Of Common Adulterants In Powdered Milk By Nir Spectroscopy [ls-svm: Uma Nova Ferramenta Quimiométrica Para Regressão Multivariada. Comparação De Modelos De Regressão Ls-svm E Pls Na Quantificação De Adulterantes Em Leite Em Pó Empregando Nir]|
|Abstract:||Least-squares support vector machines (LS-SVM) were used as an alternative multivariate calibration method for the simultaneous quantification of some common adulterants found in powdered milk samples, using near-infrared spectroscopy. Excellent models were built using LS-SVM for determining R 2, RMSECV and RMSEP values. LS-SVMs show superior performance for quantifying starch, whey and sucrose in powdered milk samples in relation to PLSR. This study shows that it is possible to determine precisely the amount of one and two common adulterants simultaneously in powdered milk samples using LS-SVM and NIR spectra.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.