Chemometric Analysis of NMR Spectra
NMR is one of the most powerful analytical techniques of our time. It allows detailed investigation of qualitative and quantitative characteristics of complex chemical and biological samples. The resulting NMR data provides a wealth of information about the samples, but the NMR data analysis has been and still is suffering from oversimplified approaches making it difficult to extract all the information efficiently. For instance, univariate methods that just use one or a few selected variables for the analysis from a whole spectrum lead to a huge loss of information. Such a simplifying approach reduces the chance of discovering new findings and truly learning about complex aspects of the samples investigated. Multivariate data analysis techniques allows for truly exploratory and comprehensive analysis of NMR data. This is particularly advantageous in the investigation of complex biological samples. Chemometrics can be helpful here by providing tools for unsupervised and supervised data exploration, multivariate calibration, classification and discrimination.
This chapter presents some important steps in the pre-processing of NMR data as well as some of the most common chemometric techniques for data exploration and analysis. An example of NMR spectra of apple juice samples is given, to illustrate the power of the combination of NMR data and chemometrics.
KeywordsNMR Chemometrics PCA PLS MCR
- 1.Günther H. NMR spectroscopy: basic principles, concepts and applications in chemistry. Weinheim: Germany: Wiley-VCH; 2013.Google Scholar
- 2.Johnels D, Edlund U, Grahn H, Hellberg S, Sjöström M, Wold S, Clementi S, Dunn WJ. Clustering of aryl carbon-13 nuclear magnetic resonance substituent chemical shifts. A multivariate data analysis using principal components. J Chem Soc Perkin Trans 2. 1983;863–871.Google Scholar
- 3.Grahn H, Delaglio F, Delsuc MA, Levy GC. Multivariate data analysis for pattern recognition in two-dimensional NMR. J Magn Reson. 1988;77:294–307.Google Scholar
- 6.Miller JN, Miller JC. Statistics and chemometrics for analytical chemistry. Essex: England: Pearson Education; 2005.Google Scholar
- 10.Spyros A, Dais P, Belton P. NMR spectroscopy in food analysis. Cambridge: Royal Society of Chemistry; 2013.Google Scholar
- 11.Ebrahimi P. Metabolic profiling of food protective cultures by in vitro NMR spectroscopy. Ph.d. thesis: Department of Food and Science, Faculty of Science, University of Copenhagen; Frederiksberg: Denmark. 2015.Google Scholar
- 12.Morris GA. Reference deconvolution. eMagRes: Wiley; 2007.Google Scholar
- 16.Savorani F, Tomasi G, Engelsen SB. Alignment of 1D NMR data using the icoshift tool: a tutorial. Magn Reson Food Sci. 2013;14–24.Google Scholar
- 34.Stone M. An asymptotic equivalence of choice of model by cross-validation and Akaike’s criterion. J R Stat Soc B Methodol. 1977;39:44–7.Google Scholar
- 40.Engelsen SB, Savorani F, Rasmussen MA. Chemometric exploration of quantitative NMR data. eMagRes. 2013;2:267–278.Google Scholar
- 43.Nielsen MM, Viereck N, Engelsen SB. Phytic acid degradation by phytase–as viewed by 31P NMR and multivariate curve resolution. Magn Reson Food Sci. 2007;214–22.Google Scholar