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Given the successful application of spectroscopic methods in the field of coffee analysis as fast and reliable routine techniques, the objective of this work was to evaluate the feasibility of employing Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) for discrimination between roasted coffees that presented distinct sensory characteristics and were submitted to a range of roasting conditions. Samples consisted of coffees obtained from Nespresso type capsules of intensity levels ranging from 2 to 12. Principal Component Analysis (PCA) of the processed spectra provided separation of the samples into three groups: low (positive PC1), medium (scattered) and high (negative PC1) intensity. Group separation was related to both roasting intensity and sensory parameters, with a clear separation between samples described as low roasted with fruity and floral flavors in comparison to samples described as being intense and very roasted. PLS-DA models were constructed and provided satisfactory discrimination according to sensory characteristics. Samples were classified according to flavor as sugar browning, enzymatic, or dry distillation. Such results confirm the potential of DRIFTS in the discrimination and classification of roasted and ground coffees.

The Specialty Coffee Association (SCA) sensory analysis protocol is the methodology that is used to classify specialty coffees. However, because the sensory analysis is sensitive to the taster’s training, cognitive psychology, and physiology, among other parameters, the feasibility of instrumental approaches has been recently studied for complementing such analyses. Spectroscopic methods, mainly near infrared (NIR) and mid infrared (FTIR—Fourier Transform Infrared), have been extensively employed for food quality authentication. In view of the aforementioned, we compared NIR and FTIR to distinguish different qualities and sensory characteristics of specialty coffee samples in the present study. Twenty-eight green coffee beans samples were roasted (in duplicate), with roasting conditions following the SCA protocol for sensory analysis. FTIR and NIR were used to analyze the ground and roasted coffee samples, and the data then submitted to statistical analysis to build up PLS models in order to confirm the quality classifications. The PLS models provided good predictability and classification of the samples. The models were able to accurately predict the scores of specialty coffees. In addition, the NIR spectra provided relevant information on chemical bonds that define specialty coffee in association with sensory aspects, such as the cleanliness of the beverage.