Coffee is one of the most popular and consumed products in the world, with high nutritional value and economic importance. However, some factors can change the organoleptic properties of a coffee species, without causing significant damage such as loss of important components. The present study evaluated the chemical profile, via nuclear magnetic resonance (NMR), of the main biological properties and substances of the drink, verifying similarities in the composition of different types of arabica coffee made in different conditions, such as the roasting time and temperature. The main components were identified, using information from the literature and a database, and compared with the experimental data of 1D and 2D 1H NMR. The spectral data were analyzed and grouped via principal component analysis (PCA) using the Bruker Amix 3.9.14 software. 1H NMR was able to monitor the roasting process and qualify the intact bean and chemical profile of the coffee according to the roasting conditions. Due to the importance of the monitored components, the coffee species analyzed can be identified, along with the appearance of unwanted or adulterating compounds that are normally added to the product to reduce the cost of commercialization.

Brazilian gasoline type C can be purchased with octane number as the main difference. This quality parameter directly affects the price. Intermediate formulations may not be easily distinguished from conform samples due to similarity in visual appearance and physicochemical properties. The use of anhydrous ethanol as an additive also influences the octane values of the product. In this context, the present study describes the use of 1H nuclear magnetic resonance spectroscopy (1H NMR) associated with chemometrics in the characterization and distinction of gasolines by different octane number. Conform samples of common, premium and blends of common-premium were used. Models of NMR-PCA (principal component analysis) and NMR-SIMCA (soft independent modelling of class analogies) showed a good correlation with the values determined by the standard method. The octane values predicted by the NMR-PLS (partial least squares) model achieved a good correlation root mean square errors of prediction (RMSEP = 0.50), with the values determined by the standard method as well.

This work describes the potential of chemometric analyses applied to 1H high-resolution magic angle spinning nuclear magnetic resonance (1H HR-MAS NMR) data for the chemotaxonomic investigation of Hancornia speciosa (Apocynaceae) varieties. This plant, popularly known as mangaba, has a complex morphological differentiation and thus chemical analyses can be used for their taxonomic classification. In comparison to traditional techniques, 1H HR-MAS NMR allied with chemometrics provided a simple and low cost method for chemotaxonomy. Leaves of four varieties of H. speciosa from a common garden experiment was studied and demonstrated that H. speciosa var. speciosa differs from others due to its specific metabolic profile, and var. pubescens was discriminated based on its high phenolic compound content. The distinction between the latter variety and gardineri is important once it allows for the selection of samples with greater commercial value, once they produce the largest and heaviest fruits.