Jtwe. Vogels et al., PARTIAL LINEAR FIT - A NEW NMR-SPECTROSCOPY PREPROCESSING TOOL FOR PATTERN-RECOGNITION APPLICATIONS, Journal of chemometrics, 10(5-6), 1996, pp. 425-438
NMR spectroscopy is increasingly used in combination with multivariate
analysis applications. Especially in the analysis of food products an
d the study of natural processes it has proved its usefulness. The sam
ples used in these evaluations are however, often difficult to control
. 'Positional' shifts of peaks due to differences in pH and other phys
ico-chemical interactions are quite common. A reduction of the resolut
ion of the spectra is generally sufficient to correct for these effect
s. This approach is, however, not possible if the fine structure in th
e data is important in the analysis. A solution to this problem is to
use the partial linear fit (PLF) algorithm described here. Using PLF p
reprocessing the fine structure in the data is utilized to correct for
any 'positional' variances, which results in a significant improvemen
t in the classification ability and a greater stability of the multiva
riate data analysis. (C) 1996 by John Wiley & Sons, Ltd.