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Item Physicochemical characterization of coffee parchment of species Coffea arabica variety Castillo®(Universidade Federal de Lavras, 2024-07-03) Campuzano, Francisco; Escobar, Diana Marcela; L., Ana María TorresCoffee parchment is one of the most abundant wastes from coffee processing in Colombia, representing 5.8% of dry weight of the berry. This waste has been scarcely characterized, then this work is a complete physicochemical characterization of coffee parchment of the species Coffea arabica variety Castillo®. The coffee parchment composition was studied, determining the fractions of cellulose (49 %), hemicellulose (21 %), lignin (28 %), and inorganics (3 %) presented. Also, FTIR analysis was made to explore the different functional groups of the constituent molecules and confirm their presence, likewise the thermal profile was determined to confirm the composition and explore the thermal stability of this waste. Crystallinity was determined by the Segal method using XRD. A morphological analysis by SEM and a granulometric analysis of this raw material is also presented. All these analyses are important for proposing alternative uses of coffee parchment, such as obtaining cellulose.Item Effect of roast degree, preparation method, and variety in the sensory and chemical characteristics of coffee (coffea arabica): a mid-infrared spectrum analysis(Editora UFLA, 2021) Barrios-Rodríguez, Yeison Fernando; Córdoba, Gisela-Andrea; Bahamón-Monje, Andrés Felipe; Gutiérrez-Guzmán, NelsonIn coffee beverages, there are several factors that affect the final compounds and generate sensory variations. This study evaluated the effect of five preparation methods, three roast degrees, and three different varieties (coffea arabica) on the physicochemical compounds of coffee (coffea arabica) be fore and after preparation by using information obtained from the mid-infrared spectrum. The effect on some sensory attributes was assessed by means of a panel of 54 habitual coffee consumers. Spectrum data were processed using hierarchical clustering and principal component analysis (PCA), while a mixed general linear model was applied for sensory analysis. The results showed that each factor behaves independently, showing a significant effect (p < 0.05) on a greater number of attributes. The preparation method and the roast degree are attributed to the changes generated in the chemical character istics of coffee during these processes. Through the analysis of the infrared spectrum (IR) by hierarchical cluster, it was found that, before the preparation of the coffee drinks, the samples are grouped by roast degree, regardless of the type of variety. Spectrum analysis by PCA after brewing indicated that there is a greater effect of the roast degree and variety of coffee (coffea arabica) on the chemical markers of the IR spectra. Finally, wavelengths 1,800, 1,740, 1,650, 1,550, 1,480, 1,150, and 710 cm-1, which had a greater contribution in the PCA and allowed the evaluated samples to be grouped differently, are those related to non-volatile compounds such as caffeine, chlorogenic acids, and trigonelline, which provide sensory characteristics to the final drink.