Author/Authors :
Forina، نويسنده , , M. and Drava، نويسنده , , G. and Armanino، نويسنده , , C. and Boggia، نويسنده , , R. and Lanteri، نويسنده , , S. and Leardi، نويسنده , , R. and Corti، نويسنده , , P. and Conti، نويسنده , , P. and Giangiacomo، نويسنده , , R. and Galliena، نويسنده , , C. and Bigoni، نويسنده , , R. and Quartari، نويسنده , , I. and Serra، نويسنده , , C. and Ferri، نويسنده , , D. and Leoni، نويسنده , , O. and Lazzeri، نويسنده , , L.، نويسنده ,
Abstract :
A procedure for the transfer of the regression equation in near-infrared spectroscopy (NIRS), from a first instrument to a second instrument, is presented. The procedure uses partial least squares (PLS) regression twice: in the first step to compute the relationship between the spectra of transfer samples of the two instruments, and in the second step to compute the regression equation (relationship between chemical variables and spectral variables) of the first instrument. These two PLS steps are combined to predict the regression equation of the second instrument. Sometimes the PLS relationship between the two instruments is obtained from the principal components of the spectra of the two instruments. The procedure is applied to a set of 60 samples of soy flour, representative of the Italian soy production. 40 samples were used both as transfer samples and to compute the regression equation. 20 samples were used as evaluation set. Spectra were recorded with four different instruments, in four different laboratories. The result of the transfer procedure were evaluated by means of the standard error of prediction (SEP) with the predicted regression equation. Owing also to the great number of samples in the transfer set, and to the noise filtering effect of the twin PLS procedure, SEP with the predicted regression equation is not greater than that with the regression equation computed directly from the second instrument. The effect of some parameters, such as the number of PLS latent variables in the two steps, is also studied.
