Quantitation of components in complex mixtures utilizing two dimensional NMR spectroscopy

Nuclear Magnetic Resonance (NMR) spectroscopy is well documented to provide qualitative data for structural determination of chemical compounds. More recently, numerous applications of NMR for quantitative analyses of chemical mixtures have been utilized. The majority of these applications use integration of discrete 1D NMR spectral resonances to quantitate individual components of the mixtures. 1D ¹H NMR typically provides the highest sensitivity analyses with excellent linear response to component concentrations. Quantitative analyses of complex mixtures via 1D NMR however are often hindered by resonance overlap. Utilization of ¹H-¹³C heteronuclear correlation (HSQC) and 2D J-resolved experiments provides dispersion in a second dimension, ¹³C chemical shift and ¹H coupling constant respectively, for better identification and quantification of signals. The HSQC cross-peak volumes are influenced by uneven excitation, etc. and therefore the volumes for different resonances from the same molecule can vary based on these factors. Nevertheless, utilizing the same experimental parameters for any given cross-peak, the areas for the same peak should scale linearly with molar concentration. In this study, we have investigated the quantitative accuracy of these 2D spectra on a complex model system containing phenolics, alkaloids, sugars, terpenes, and polyketides and made comparisons to quantification using chemometric approaches. Applications to natural product extracts and formulations and ability to implement this into automated analysis methods will be presented.