An independent and orthogonal analysis of the ten extraction conditions was conducted using NMR spectroscopy to confirm these results. By integrating the total area of the 1D JRES projections for each experiment (Table ) we can assess the complexity of metabolite extraction and the concentration of features in each sample. Figure shows an overlaid scatter and line plot of the total integrated area for non-polar and polar extractions by NMR. NMR shows a very similar trend to that observed in the LC-MS polar data (Figure ) using the number of deconvoluted features. The NMR non-polar data (Figure ) showed an increase in AUC with run number similar to that of the LC-MS non-polar data; however, the differences between run nine and the optimized conditions were not as extreme as those observed for LC-MS. This subtly stems from excluding the reconstitution solvent factor in the NMR data where CDCl3 and D2O were used for all ten non-polar and polar samples, respectively. Without the additional factor, run nine and ten only differ in extraction time (Table ), where very subtle differences are expected. Using NMR as a separate orthogonal and quantitative approach, we could confirm the observed trends using number of features, increasing our confidence in our optimized conditions and our choice of 'number of deconvoluted features' as a metric for untargeted metabolomics extraction performance.