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

Química Nova

Marco F. Ferrão¹  Cesar Mello¹  Alessandra Borin¹  Danilo A. Maretto¹  Ronei J. Poppi¹ 

关键词: support vector machines;    multivariate regression;    powdered milk;   

DOI  :  10.1590/S0100-40422007000400018

来源: SciELO

【 摘 要 】

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 R², 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.

【 授权许可】

CC BY-NC   
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