Optimizing Extraction Solvents for Plant Chemical Analysis Using ¹H NMR and Principal Component Analysis

Natural products, particularly plants, remain a vital source of bioactive compounds owing to their unparalleled metabolic diversity across pharmaceuticals, cosmetics, foods, and agriculture. However, this diversity, encompassing not only a multitude of compounds but also their varying chemical and physical properties, presents a challenge in their effective utilization. Targeted analysis of specific metabolites, as well as untargeted approaches covering a wide metabolite range, necessitate optimal extraction solvents tailored to meet diverse requirements. Achieving optimization requires two crucial components: analytical methods capable of capturing a broad spectrum of metabolites and effective data analysis to derive meaningful conclusions. In this regard, 1H nuclear magnetic resonance (NMR) spectroscopy combined with principal component analysis (PCA) emerges as a promising approach for optimization. In this protocol, employing two model plants, leaves of basil (Ocimum basilicum) and lettuce (Lactura sativa), we deduce optimal extraction solvents from mixtures of methanol-water, acetonitrile, and chloroform, leveraging ¹H NMR and PCA analyses.