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URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352
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Item Discrimination of commercial roasted and ground coffees according to chemical composition(Sociedade Brasileira de Química, 2012) Souza, Romilaine M. N. de; Benassi, Marta T.Roasted and ground 38 commercial coffees and coffees of known species (arabica, robusta) were characterized by principal component analysis using as variables nicotinic acid, trigonelline, 5-o-caffeoylquinic acid (5-CQA), caffeine, kahweol and cafestol, which are potentially indicative of species. The objective of the study was to assess the relevance of such parameters in coffee discrimination. Nicotinic acid allowed the characterization of roasting degree. Trigonelline and 5-CQA presented variability among arabica and robusta coffees as well as among comercial ones. Thermostable parameters (caffeine, kahweol and cafestol) had high discriminative potential between the species. In general, high levels of caffeine and low levels of diterpenes (kahweol and cafestol) were related with higher proportions of robusta in the products, which were observed by the decreasing kahweol/cafestol ratio and increasing caffeine/kahweol ratio. The use of these new parameters (kahweol/cafestol and caffeine/kahweol ratios) was suggested as tools for assessing the addition of robusta in commercial coffees.Item Evaluation of the metabolic profile of arabica coffee via NMR in relation to the time and temperature of the roasting procedure(Sociedade Brasileira de Química, 2021) Alves, Roger P.; Antoniosi Filho, Nelson R.; Lião, Luciano M.; Flores, Igor S.Coffee is one of the most popular and consumed products in the world, with high nutritional value and economic importance. However, some factors can change the organoleptic properties of a coffee species, without causing significant damage such as loss of important components. The present study evaluated the chemical profile, via nuclear magnetic resonance (NMR), of the main biological properties and substances of the drink, verifying similarities in the composition of different types of arabica coffee made in different conditions, such as the roasting time and temperature. The main components were identified, using information from the literature and a database, and compared with the experimental data of 1D and 2D ¹H NMR. The spectral data were analyzed and grouped via principal component analysis (PCA) using the Bruker Amix 3.9.14 software. ¹H NMR was able to monitor the roasting process and qualify the intact bean and chemical profile of the coffee according to the roasting conditions. Due to the importance of the monitored components, the coffee species analyzed can be identified, along with the appearance of unwanted or adulterating compounds that are normally added to the product to reduce the cost of commercialization.Item Multivariate analysis applied to spray deposition in ground application of phytosanitary products in coffee plants(Associação Brasileira de Engenharia Agrícola, 2021) Palma, Roxanna P.; Cunha, João P. A. R. da; Guimarães, Ednaldo C.; Santana, Denise G. de; Assunção, Heli H. T. deAn adequate combination of factors involved in the technology used for phytosanitary product application contributes to an efficient spray deposition on the target. The objective of this study was to use multivariate analysis to characterize the magnitude of effects and the order of influence of three factors that interfere with the quality of phytosanitary product application in coffee plants. An entirely randomized design was adopted, with four repetitions, using a 2 × 2 × 3 factorial scheme, with two classes of droplets quality (fine and coarse), two application rates (250 and 400 L ha-1), and the use of adjuvants (with no adjuvant or with Fighter® and Aureo® adjuvants). The quality of the application was determined by jointly analyzing the spray deposition on three thirds of leaves, in their internal and external layers, the runoff to soil, coverage, droplet density, relative amplitude, and the volumetric median diameter. The results underwent analysis of variance (ANOVA) to measure the effect sizes (η2). After testing the assumptions of multivariate analysis, clustering and principal component analyses were performed. The class of droplets was found to be the most influential factor in the quality of the phytosanitary product application (spray deposition and runoff to soil). When focusing on spray deposition on leaves, the second-most influential factor was the application rate and the relation between the application rate and the adjuvants. For the other variables, the second-most influential factor was the application rate.