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URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352
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Item Main minerals and organic compounds in commercial roasted and ground coffee: an exploratory data analysis(Sociedade Brasileira de Química, 2021) Kalschnea, Daneysa Lahis; Silva, Nathalia Karen; Canan, Cristiane; Benassi, Marta de Toledo; Flores, Eder Lisandro Moraes; Leite, Oldair DonizeteCoffee is one of the most popular beverages in the world, however, little information is found regarding the mineral composition of commercial roasted and ground coffees (RG) and its correlation with organic bioactive compounds. 21 commercial Brazilian RG coffee brands - 9 traditional (T) and 12 extra strong (ES) roasted ones - were analyzed for the Cu, Ca, Mn, Mg, K, Zn, and Fe minerals, caffeine, 5-caffeoylquinic acid (5-CQA) and melanoidins contents. For minerals determination by flame atomic absorption spectrometry (FAAS), the samples were decomposed by microwave-assisted wet digestion. Caffeine and 5-CQA were determined by liquid chromatography and melanoidins by molecular absorption spectrometry. The minerals and organic compounds contents association in RG coffee was observed by a principal component analysis. The thermostable compounds (minerals and caffeine) were related to dimension 1 and 2, while 5-CQA and melanoidins were related to dimension 3, allowing for the T coffees segmentation from ES ones.Item Spectroscopic and chromatographic fingerprint analysis of composition variations in Coffea arabica leaves subject to different light conditions and plant phenophases(Sociedade Brasileira de Química, 2014) Delaroza, Fernanda; Rakocevic, Miroslava; Malta, Galileu Bernardes; Bruns, Roy Edward; Scarminio, Ieda SpacinoFingerprints of self-shaded and sunlight-exposed leaves of the same Coffea arabica plant were obtained to determine metabolic concentration changes owing to different light environments and phenological stages. Leaf extract yields of the ethanol, acetone, dichloromethane and hexane solvents, as well as their statistical design mixtures, are reported. Highest yields are obtained with binary 1:1 ethanol-acetone mixtures for all sun-exposed and self-shaded leaves. Principal component analysis (PCA) of Fourier transform infrared (FTIR) spectra of leaf extracts indicate spectral differences between 2962-2828, 1759-1543 and below 1543 cm-1 that can be attributed to higher concentrations of fatty acid esters or the ester group in triglycerides, caffeine, chlorogenic acids and carbohydrates that are more prevalent in leaves of flowering plants. Highperformance liquid chromatography with UV diode array detector (HPLC-UV-DAD) spectra of the chromatographic peaks for the extracts showed that sun-exposed samples contain stronger absorptions for caffeine, chlorogenic acid and theobromine. Confirmatory experiments carried out with reference UV calibration curves determined caffeine contents for sun-exposed leaves that are about double those for self-shaded leaves of flowering plants. Knowledge of leaf caffeine content in Coffea arabica is of ecological importance since sun-exposed conditions seem more stressful than self-shading ones for this species. Lipid concentrations in self-shaded leaves are almost double those that were sun-exposed.Item Classification of robusta coffee fruits at different maturation stages using colorimetric characteristics(Associação Brasileira de Engenharia Agrícola, 2020) Costa, Anderson G.; Sousa, Daniela A. G. de; Paes, Juliana L.; Cunha, João P. B.; Oliveira, Marcus V. M. deCoffee growers who produce the robusta species (Conilon) have sought to increase productivity and drink quality by improving production techniques. Artificial vision systems can assist in increasing the efficiency of operations associated with crop management. This study aimed to obtain colorimetric characteristics of robusta coffee fruits at different stages of maturity and use them for classifying fruits from digital images. A digital camera with spectral resolution in the visible was used to acquire images from 60 samples of coffee fruits at the green, cherry, and over-ripe stages of maturity. Colorimetric variables were extracted from the RGB, HIS, and L*a*b* color models and correlated with the physicochemical attributes of the fruits. The principal componente analysis associated with the k-means technique was applied to the colorimetric variables that showed a significant correlation with the physical-chemical attributes. The colorimetric variables were reduced to a principal component, which presented na explanatory percentage of the variance of 82.33%. The clustering obtained by the application of the k-means technique showed the feasibility of using images for the automatic classification of robusta coffee fruits, with an overall accuracy of 100%.Item Comparison of sensory attributes and chemical markers of the infrared spectrum between defective and non-defective Colombian coffee samples(Editora UFLA, 2020) Rodriguez, Yeison Fernando Barrios; Calderon, Karen Tatiana Salas; Hernández, Joel GirónDefects in coffee affect the sensory quality of finished drink. To avoid this, defective beans are usually removed after threshing, as, once the green beans have been roasted, it becomes difficult to identify the defects. Procedures have been developed to evaluate coffee samples using infrared spectroscopy to detect such defects. As such, this study evaluated infrared spectra and sensory attributes of 39 coffee samples in: commercial ground and instant coffees, medium and high roast quality coffees, and defects present in the coffee. The sensory analysis was performed by 10 judges, semi-trained by a Q-grader, and eleven attributes were assessed using a semi-structured hedonic scale. The spectra obtained from the coffee samples were processed by mean centering, normalization (probabilistic quotient normalization), area normalization, first derivative and second derivative, later followed by principal component analyses. The sensory results showed differences in the evaluated attributes, differentiating between the samples of high quality medium roasted coffee from the other samples. After processing IR spectra of the samples by area normalization, PCA results exhibited four different groups: a) medium, high roasted quality coffee, with broken and chipped defects; b) commercial ground coffee and defects of sour, insect damaged, and faded; c) black defects, and d) instant coffee. Using the chemical descriptors obtained from the infrared spectra, it was possible to separate between high quality, commercial and instant coffee.