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Item Perfil volátil do Coffea arabica e Coffea canephora var. Conilon por SHS-GC-MS e quimiometria(Sociedade Brasileira de Química, 2023-11-20) Lyrio, Marcos Valério Vieira; Cunha, Pedro Henrique Pereira da; Debona, Danieli Grancieri; Agnoletti, Bárbara Zani; Frinhani, Roberta Quintino; Oliveira, Emanuele Catarina da Silva; Filgueiras, Paulo Roberto; Pereira, Lucas Louzada; Castro, Eustáquio Vinicius Ribeiro deThe volatile composition of coffee exerts a substantial influence on its quality, as it defines the characteristics of the beverage. However, these compounds are influenced by factors within the coffee production chain, such as botanical origin, geography, processing methods, and roasting. Consequently, the identification of such compounds becomes a vital tool for characterizing coffees to these factors. In this context, gas chromatography with headspace extraction is widely used for aroma analysis, providing a composition closer to consumer perception. Headspace extraction offers speed, simplicity, minimal sample preparation, and no need for solvents. In this study, static headspace extraction (SHS) coupled with gas chromatography-mass spectrometry (SHS-GC-MS) was employed to establish the chemical profile of volatile compounds in Coffea arabica and Coffea canephora var. conilon and determine discriminants between the species. A total of 97 compounds, belonging to 17 chemical classes, were identified. The chemometric analysis highlighted furans, phenols, and carboxylic acids as key differentiating classes. Notably, furfuryl alcohol, acetic acid, 4-vinylguaiacol, N-acetyl-4(H)-pyridine, and N-furfurylpyrrole emerged as crucial volatile compounds. The variable selection using Fisher weight applied directly in the chromatograms, produced models consistent with relative area data, with furfuryl alcohol and 4-vinylguaiacol regions being particularly influential in differentiation.Item Chemical and sensory perception of robusta coffees under wet processing(Editora UFLA, 2020) Oliveira, Emanuele Catarina da Silva; Guarçoni, Rogério Carvalho; Castro, Eustáquio Vinicius Ribeiro de; Castro, Marina Gomes de; Pereira, Lucas LouzadaThe quality of the coffee is determined by the sensorial analysis, using subjective methods and it is known that this quality is related to the chemical constituents of the grains. The present study used infrared spectroscopy to correlate the chemical composition of the grain with the final quality of the product and to assist in the current evaluation method, generating more reliability in the process. This study applied the spontaneous and induced fermentation with starter cultures (yeast) to evaluate the sensory potential from the impacts generated by the types of processes adopted. The experiments were conducted in a randomized block design with five replicates, in a 3x4 factorial scheme, with three fermentation times: 24, 48, and 72 hours and four wet processes: Washed, Yeast fermentation, Fully washed without yeast, and Fully washed with yeast. Infrared spectra were taken in the medium region (FTIR-ATR) of the 34 samples generated by the treatments. Given that the method of determining the quality of coffee is subjective, based on scores given by cuppers, the FTIR-ATR spectra were used in the construction of chemometric models to predict sensory ratings given to the attribute ‘acidity’. The mean error of prediction of the model constructed for the sensory score was 0.11. Sensory results indicated a higher score for the acidity attribute, in dry fermentation with yeast at the time of 48 hours, suggesting a new strategy for the production of quality robusta coffee.