In this study were successfully observed the one- (1H, 13C) and two-dimensional (1H-13C, 1H-15N, 1H-31P) NMR spectra of milk directly without any pretreatment. The signals of each NMR spectrum were assigned, and their existing states were also analyzed. Lactose existed in a free state in milk. The signals due to the butyric acid chain can be assigned among the other fatty acid chains. Monounsaturated fatty acid (oleic acid chains) and polyunsaturated fatty acid chains (linoleic and linolenic acid) were assigned by their characteristic signals. The signals from citrate, N-acetylcarbohydrates, and lecithin could be observed directly in the 1H-13C HSQC NMR spectra; the assignment of their signals was made through the 1H-13C, 1H-15N, and 1H-31P HMBC spectra of extracted milk. Signals from creatine and N-acetylcarbohydrates were detected for the first time.

In this paper, we report a (1)H and (13)C nuclear magnetic resonance (NMR)-based comprehensive analysis of coffee bean extracts of different degrees of roast. The roasting process of coffee bean extracts was chemically characterized using detailed signal assignment information coupled with multivariate data analysis. A total of 30 NMR-visible components of coffee bean extracts were monitored simultaneously as a function of the roasting duration. During roasting, components such as sucrose and chlorogenic acids were degraded and components such as quinic acids, N-methylpyridinium, and water-soluble polysaccharides were formed. Caffeine and myo-inositol were relatively thermally stable. Multivariate data analysis indicated that some components such as sucrose, chlorogenic acids, quinic acids, and polysaccharides could serve as chemical markers during coffee bean roasting. The present composition-based quality analysis provides an excellent holistic method and suggests useful chemical markers to control and characterize the coffee-roasting process.

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A complex mixture analysis by one-and two-dimensional nuclear magnetic resonance (NMR) spectroscopy was carried out for the first time for the identification and quantification of organic compounds in green coffee bean extract (GCBE). A combination of 1 H-1 H DQF-COSY, 1 H-13 C HSQC, and 1 H-13 C CT-HMBC two-dimensional sequences was used, and 16 compounds were identified. In particular, three isomers of caffeoylquinic acid were identified in the complex mixture without any separation. In addition, GCBE components were quantified by the integration of carbon signals by use of a relaxation reagent and an inverse-gated decoupling method without a nuclear Overhauser effect. This NMR methodology provides detailed information about the kinds and amounts of GCBE components, and in our study, the chemical makeup of GCBE was clarified by the NMR results.

(13)C NMR-based metabolomics was demonstrated as a useful tool for distinguishing the species and origins of green coffee bean samples of arabica and robusta from six different geographic regions. By the application of information on (13)C signal assignment, significantly different levels of 14 metabolites of green coffee beans were identified in the classifications, including sucrose, caffeine, chlorogenic acids, choline, amino acids, organic acids, and trigonelline, as captured by multivariate analytical models. These studies demonstrate that the species and geographical origin can be quickly discriminated by evaluating the major metabolites of green coffee beans quantitatively using (13)C NMR-based metabolite profiling.