PARTIAL LINEAR FIT - A NEW NMR-SPECTROSCOPY PREPROCESSING TOOL FOR PATTERN-RECOGNITION APPLICATIONS

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.