An NMR-based metabolomic approach applied to the characterization and typification of Brazilian honey

Honey is a natural food consumed globally, typically recognized as a prototype of all-natural food, with a well-known set of relevant biological activities, e.g., antioxidant, antimicrobial, and antiinflammatory. Along with wines, olive oil, fruit juices, and milk, honey has been frequently prone to adulteration with low-cost honeys, sugar syrups, water, and starch. Indeed, because demand is on the rise and supply is short, honey quality control is essential to maintain fair trade pricing and avoid risks to consumers' health. In this sense, a series of analytical techniques have been used, such as 1 H-nuclear magnetic resonance spectroscopy ( 1 H-NMR), that allow the detection, identification, and quantification of several targets and dozens of nontarget compounds (i.e., metabolic profile) within a single measurement. Since a huge amount of data is collected by 1 H-NMR profiling honey, multivariate statistical methods are routinely applied to the metabolomic data set, optimizing the quality control process by extracting additional and relevant information associated with the samples' authenticity. In this chapter, a review of the application of bioanalytical NMR spectroscopy is initially presented, followed by an NMR-based metabolomic pilot study of polyfloral honeys produced in southern Brazil as an analytical approach for the characterization and typification of natural foods. Through the detection and identification of metabolites in the 1 H-NMR spectra and chemometric analysis (i.e., principal component analysis), chemical shifts and their assigned compounds of greatest influence on the classification model might be identified, as well as the sample clustering related to the geographic and botanical origin of honey. Due to its noninvasive approach, relatively easy and fast data preparation and acquisition, as well as the detection and quantification of a wide range of metabolites, NMR spectroscopy proves to be a powerful technique for characterizing honey, allowing the identification of chemical signatures related to its geographical and botanical origins and also to intentional and unintentional fraud.