NMR spectroscopy is a widely used method in study and analysis of phospholipids. Proton, carbon and phosphorus nuclei are commonly used in the NMR measurements for phospholipids. For use as a quantitative test, ³¹P NMR, which is observable by separating phospholipids into individual classes, is particularly important. The study of phospholipid by employing ³¹P NMR has a history of 50 years, and has already accumulated a lot of knowledge. We achieved accurate, individual and concomitant quantifications of phospholipid classes (mainly glycerophospholipids) in commercial polar lipids by using the ³¹P NMR technique incorporating a ¹H NMR methodology which is becoming popular as a method to determine the purity of low molecular organic standard substance. In this review, we describe about phospholipids quantification by using ³¹P NMR based on our previous study results.

Gas chromatograph (GC), liquid chromatograph (LC), liquid chromatograph/mass spectrometry (LC/MS) are widely used for analyzing useful ingredients in food samples such as lipids. Generally, samples are pretreated according to the analytes, such as deproteinization and derivatization, and are used for analysis. In recent years, direct ionizations and ambient ionizations have been actively studied as an ionization method for mass spectrometry. In DART-MS analysis using DART (Direct Analysis in Real Time) which is a type of the direct ionizations, food samples can be analyzed with little or no sample pretreatment. In this paper, we introduce applications of various lipid analyzes by mass spectrometry using DART-MS.

A significant number of “unknown” metabolite peaks are usually detected in foods and other samples by mass spectrometry (MS)-based untargeted metabolome analyses. Identification and annotation of these unknowns are useful for discovery of novel functional molecules and biomarkers, and for understanding the mechanisms of living organisms. In this article, we summarize current status and issues in the MS-based metabolomics and propose a database, Food Metabolome Repository (http://metabolites.in/foods), as a new data resource for improving metabolite annotations based on the sample specificity of the unknowns.