Técnicas analíticas avançadas na caracterização química e adulteração de cafés - Correia, Radigya Meyrelles (2021)
Brazil is the largest producer and exporter of coffee and its rise in this market is associated with the growing improvement in the quality of the product. Espirito Santo is one of the largest coffee producers in Brazil, therefore, it is extremely important to evaluate the quality of coffee produced in the state. Aiming to propose new analytical methodologies by applying spectroscopy techniques in the portable near infrared region (microNIR) and Fourier Transform Ion Cyclotronic Resonance mass spectrometry (FT-ICR MS), the work was divided into three chapters in which factors involving the pre- and post-harvest of coffee beans were evaluated, including: 1) compare the results of FT-ICR MS, microNIR and sensory analysis to evaluate the cultivation of Robusta coffee in an Agroforestry System (AFS) with gliricidia, ingá , peach palm and banana tree; 2) build models of principal component analysis (PCA) and partial least squares regression (PLS) using microNIR spectra to verify the influence of roasting temperature on Arabica/Conilon coffee blends and the presence of adulterants such as corn and husks/sticks in Arabica coffee and 3) identify adulterations with Coffea canephora (Conilon) sludge at different levels (0 - 100 wt% of adulterant), through the analytical technique of portable NIR associated with chemometric tools: PCA, PLS-DA, SIMCA, PLS. These studies showed that the components responsible for distinguishing the samples grown with different species in SAF were chlorogenic acids and that the microNIR results corroborated with the ESI(- )FT-ICR MS data and the sensory analysis, grouping coffees grown in the associated AFS with Gliricidia sepium and Inga edulis. The qualitative and quantitative assessment of the presence of adulterants proved the ability of the portable NIR method to be efficient and capable of predicting adulteration with minimal levels of quantification (LOQs of 5–8% wt% for husks/sticks and corn, and in the range of 17-26 wt% for coffee grounds), which can be applied in the quality control of commercial coffee samples. It was also possible to identify that the roasting temperature affects the discrimination of Arabica and Conilon coffee blends and the drying temperature of the grounds influences the identification in blends with Conilon coffee. However, it was possible to obtain low accuracy values and good classification of authentic and non-authentic samples when evaluating the presence of coffee grounds.