Optimization of Extraction Methods for NMR and LC-MS Metabolite Fingerprint Profiling of Botanical Ingredients in Food and Natural Health Products (NHPs)
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Updated: Sep 9, 2025

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
Published on: January 7, 2019
Varathan Vinayagam1, Arunachalam Thirugnanasambandam1,2, Subramanyam Ragupathy1
1College of Biological Science, University of Guelph, Guelph, ON N1G 2W1, Canada.
Abstract:
Metabolite fingerprint profiling is a robust tool for verifying suppliers of authentic botanical ingredients. While comparative studies exist, few apply identical conditions across multiple species; this study utilized a cross-species comparison to identify versatile solvents despite biochemical variability. Multiple solvents were used for sample extraction prior to analysis by proton NMR and liquid chromatography-mass spectrometry (LC-MS) for multiple botanicals including Camellia sinensis, Cannabis sativa, Myrciaria dubia, Sambucus nigra, Zingiber officinale, Curcuma longa, Silybum marianum, Vaccinium macrocarpon, and Prunus cerasus. Comparisons were normalized by total intensity; deuterated methanol aids NMR lock but is not required for LC-MS. Hierarchical clustering analysis (HCA) evaluated solvent efficacy. Methanol-deuterium oxide (1:1) was the most effective extraction method, yielding 155 NMR spectral metabolite variables for Camellia sinensis, while methanol (90% CH3OH + 10% CD3OD) produced 198 for Cannabis sativa and 167 for Myrciaria dubia, with 11, 9, and 28 assigned metabolites, respectively. LC-MS detected 121 metabolites in Myrciaria dubia in methanol as the most effective extraction method. Methanol (10% deuterated) is the most effective extraction method for comprehensive metabolite fingerprinting using NMR and LC-MS protocols because it provides the broadest metabolite coverage. This study advances fit-for-purpose methods to qualify suppliers of botanical ingredients in food and NHP quality control programs.
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