Multivariate data analysis (MVA) has been used as an aid in the analysis and interpretation of 13C NMR spectra in the solid state. The goal of this study was to investigate the effect of some important instrumental parameters and calculation strategies on the outcome of the multivariate data analysis. The samples used were two peat forming plants, Sphagnumfuscum and Carex rostrata, incubated in four different redox environments. It was found that normalising each NMR spectrum to a constant area should be avoided. Using non-normalised data we get a slightly better class separation and the peaks in the ‘subspectra’ are sharpened. Depending on the relative size of interesting variation one should be careful when choosing the number of variables, i.e. number of data points characterising each spectrum. The line broadening technique should be used with great care in order not to obscure the information. We also suggest the use of the free induction decay (FID)/MVA directly for classification purposes. This is a new approach to analyse the output data from NMR measurements.
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Nuclear magnetic resonance spectrometry,Peat forming plants,Multivariate data analysis,Principal component analysis,Free induction decay