Multivariate analysis of CPMAS 13 C-NMR spectra of soils and humic matter as a tool to evaluate organic carbon quality in natural systems D. S ˇ MEJKALOVA ´ a , R. S PACCINI a & A. P ICCOLO a,b a Dipartimento di Scienze del Suolo, della Pianta, dell’Ambiente e delle Produzioni Animali (DiSSPAPA), Universita ` di Napoli Federico II, Via Universita ` 100, 80055 Portici, Italy, and b Centro Interdipartimentale per la Risonanza Magnetica Nucleare (CERMANU), Universita ` di Napoli Federico II, Via Universita ` 100, 80055 Portici, Italy Summary A series of humic and fulvic acids isolated from different sources, size-fractions separated from a humic acid, and three soils of different origin were subjected to CPMAS 13 C-NMR spectroscopy to obtain the distribution of their carbon contents. The relative areas of chemical shift regions in NMR spectra were used to apply a principal component analysis (PCA) to the three sets of samples. The multivariate ana- lysis was successful in efficiently differentiating samples on the basis of the quality of their organic car- bon content. The PC biplots based on two principal components distinguished objectively among samples as accurately as it was possible to do by subjective qualitative evaluation of the original spec- tra. In the case of the soils, a discriminant analysis (DA) was applied to build a classification model that allowed the validation of the three soils according to their origin. Percentage of validation in the classification model is expected to increase when a large number of NMR spectra are accumulated and/or the concentration of organic carbon in samples is enhanced. The multivariate analyses described are likely to become a useful tool to increase the importance of CPMAS 13 C-NMR spectra in the appraisal of natural organic matter variations in heterogeneous natural systems. Introduction Cross polarization magic angle spinning (CPMAS) 13 C-NMR spectroscopy has been increasingly applied in recent years to study organic matter quality and dynamics in either bulk soils or isolated fractions from environmental compartments (Ko¨gel-Knabner, 1997; Keeler & Maciel, 2003). The major advantage of CPMAS 13 C-NMR spectroscopy resides in the rapid and non-destructive acquisition of quantitative struc- tural information on carbon forms present in environmental samples without the need for extensive pre-treatment (Wilson, 1987; Kinchesh et al., 1995; Preston, 1996; Smernik & Oades, 2000; Ziarelli & Caldarelli, 2006). The quality of CPMAS 13 C-NMR spectra may be limited by paramagnetic compo- nents present in the material, by side bands, which reduce the intensity of centre bands, and by baseline distortions due to dead time at the start of the signal detection. These factors lower and broaden NMR signals and are believed to induce an underestimation of the carbon content (Wilson, 1987; Preston, 1996; Piccolo & Conte, 1998). However, correct quantification of structures in 13 C-NMR spectra of soils or humic fractions may be achieved when paramagnetic species are lessened with material purification (Conte et al., 2001) and by measuring rel- ative signal intensities over specific NMR spectral regions (Conte et al., 2002), and by carefully subtracting side-bands (Piccolo & Conte, 2003). Nevertheless, a detailed comparison among NMR spectra is required in order to relate such quan- titative measurements to the origin and treatment of soils or humic matter. This procedure may become excessively tedious and time-consuming if a large number of spectra are to be compared. It is generally reckoned that the treatment and interpretation of numerous data can be simplified by chemometric methods or multivariate analyses. Among these, principal component ana- lysis (PCA) is widely applied to simplify interpretation of chem- ical and spectroscopic results for complex systems (Einax et al., 1997). The main purpose of PCA is to reduce the original data set, represented by an ‘n’ dimensional space (where n is the number of variables or experimental results), into a few princi- pal components (PC), which concomitantly retain the maximum Correspondence: A. Piccolo. E-mail: alpiccol@unina.it Received 1 March 2007; revised version accepted 19 November 2007 496 # 2008 The Authors Journal compilation # 2008 British Society of Soil Science European Journal of Soil Science, June 2008, 59, 496–504 doi: 10.1111/j.1365-2389.2007.01005.x