964 resultados para Coffee beverages
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The objective of this work was to evaluate the toxicity of organic farming‑compatible products to the coffee leaf miner Leucoptera coffeella. Lime sulphur, enriched Bordeaux mixture (Viça Café Plus), and the "supermagro" biofertilizer were first tested in laboratory. The most promising product was tested afterwards under field conditions. In laboratory, different concentrations of each product were applied on L. coffeella eggs and on infested coffee‑mined leaves. Only lime sulphur had ovicidal effects at an acceptable concentration (1.6%) for field applications, but no significant effect on larvae mortality was found. Enriched Bordeaux mixture and the "supermagro" biofertilizer had no effect on L. coffeella eggs and larvae. In the field trial, biweekly or monthly sprayings of lime sulphur at different concentrations caused population decrease after 30 days; however, this effect was not significant after 60 or 90 days.
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The objective of this work was to evaluate the root system distribution and the yield of 'Conilon' coffee (Coffea canephora) propagated by seeds or cuttings. The experiment was carried out with 2x1 m spacing, in an Oxisol with sandy clay loam texture. A randomized complete block design was used, following a 2x9x6 factorial arrangement, with two propagation methods (seeds and cuttings), nine sampling spacings (0.15, 0.30, 0.45, 0.60, 0.75, and 0.90 m between rows, and 0.15, 0.30, and 0.45 between plants within rows), six soil depths (0.10-0.20, 0.20-0.30, 0.30-0.40, 0.40-0.50, and 0.50-0.60 m), and six replicates. Soil cores (27 cm3) with roots were taken from 12 experimental units, 146 months after planting. The surface area of the root system and root diameter, length, and volume were assessed for 13 years and, then, correlated with grain yield. The highest fine root concentration occurred at the superficial soil layers. The variables used to characterize the root system did not differ between propagation methods. Moreover, no differences were observed for net photosynthetic CO2 assimilation rate, stomatal conductance, internal CO2 concentrations, and instantaneous water-use efficiency in the leaves. Cutting-propagated plants were more productive than seed-propagated ones.
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The objective of this work was to generate drift curves from pesticide applications on coffee plants and to compare them with two European drift-prediction models. The used methodology is based on the ISO 22866 standard. The experimental design was a randomized complete block with ten replicates in a 2x20 split-plot arrangement. The evaluated factors were: two types of nozzles (hollow cone with and without air induction) and 20 parallel distances to the crop line outside of the target area, spaced at 2.5 m. Blotting papers were used as a target and placed in each of the evaluated distances. The spray solution was composed of water+rhodamine B fluorescent tracer at a concentration of 100 mg L-1, for detection by fluorimetry. A spray volume of 400 L ha-1 was applied using a hydropneumatic sprayer. The air-induction nozzle reduces the drift up to 20 m from the treated area. The application with the hollow cone nozzle results in 6.68% maximum drift in the nearest collector of the treated area. The German and Dutch models overestimate the drift at distances closest to the crop, although the Dutch model more closely approximates the drift curves generated by both spray nozzles.
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The objective of this work was to evaluate the influence of intercropping 'Conilon' coffee (Coffea canephora) with rubber trees on coffee tree microclimate, nutrition, growth, and yield. Rubber trees were planted in two double rows 33 m apart, with 4x2.3 m spacing between plants. Treatments consisted of the distances from the coffee plants to the rubber trees: 3, 6, 9, 12, and 15 m. Measurements of atmospheric variables (temperature, irradiance, and relative humidity), leaf nutrient concentration, internode length of plagiotropic and orthotropic branches, individual leaf area, chlorophyll content, and yield were performed. Intercropping promotes changes in the microclimatic conditions of coffee plants close to rubber trees, with reduction of temperature and irradiance level and increase in air relative humidity. The proximity of the coffee tree to the rubber trees promotes the elongation of the plagiotropic and orthotropic branches and increases the individual leaf area; however, it does not affect leaf concentrations of N, K, Mg, Fe, Zn, and B in 'Conilon' coffee and does not have a negative impact on yield.
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Background: Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers. Results: In this paper we show how PTC can be easily deployed and controlled on a super computer architecture using a web portal developed using Rapid. Rapid is a tool for efficiently generating standardized portlets for a wide range of applications and the approach described here is generic enough to be applied to other applications, or to deploy PTC on different HPC environments. Conclusions: The PTC portal allows users to upload a large number of sequences to be aligned by the parallel version of TC that cannot be aligned by a single machine due to memory and execution time constraints. The web portal provides a user-friendly solution.
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This article introduces a new interface for T-Coffee, a consistency-based multiple sequence alignment program. This interface provides an easy and intuitive access to the most popular functionality of the package. These include the default T-Coffee mode for protein and nucleic acid sequences, the M-Coffee mode that allows combining the output of any other aligners, and template-based modes of T-Coffee that deliver high accuracy alignments while using structural or homology derived templates. These three available template modes are Expresso for the alignment of protein with a known 3D-Structure, R-Coffee to align RNA sequences with conserved secondary structures and PSI-Coffee to accurately align distantly related sequences using homology extension. The new server benefits from recent improvements of the T-Coffee algorithm and can align up to 150 sequences as long as 10 000 residues and is available from both http://www.tcoffee.org and its main mirror http://tcoffee.crg.cat.
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Background: Epidemiological studies suggest that coffee consumption reduces the risk of cancer, but the molecular mechanisms of its chemopreventive effects remain unknown. Objective: To identify differentially expressed genes upon incubation of HT29 colon cancer cells with instant caffeinated coffee (ICC) or caffeic acid (CA) using whole genome microarrays. Results: ICC incubation of HT29 cells caused the overexpression of 57 genes and the underexpression of 161, while CA incubation induced the overexpression of 12 genes and the underexpression of 32. Using Venn-Diagrams, we built a list of five overexpressed genes and twelve underexpressed genes in common between the two experimental conditions. This list was used to generate a biological association network in which STAT5B and ATF-2 appeared as highly interconnected nodes. STAT5B overexpression was confirmed at the mRNA and protein levels. For ATF-2, the changes in mRNA levels were confirmed for both ICC and CA, whereas the decrease in protein levels was only observed in CA-treated cells. The levels of cyclin D1, a target gene for both STAT5B and ATF-2, were dowregulated by CA in colon cancer cells and by ICC and CA in breast cancer cells. Conclusions: Coffee polyphenols are able to affect cyclin D1 expression in cancer cells through the modulation of STAT5B and ATF-2.
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OBJECTIVE: To test the hypothesis that substituting artificially sweetened beverages (ASB) for sugar-sweetened beverages (SSB) decreases intrahepatocellular lipid concentrations (IHCL) in overweight subjects with high SSB consumption. METHODS: About 31 healthy subjects with BMI greater than 25 kg/m(2) and a daily consumption of at least 660 ml SSB were randomized to a 12-week intervention in which they replaced SSBs with ASBs. Their IHCL (magnetic resonance spectroscopy), visceral adipose tissue volume (VAT; magnetic resonance imaging), food intake (2-day food records), and fasting blood concentrations of metabolic markers were measured after a 4-week run-in period and after a 12-week period with ASB or control (CTRL). RESULTS: About 27 subjects completed the study. IHCL was reduced to 74% of the initial values with ASB (N = 14; P < 0.05) but did not change with CTRL. The decrease in IHCL attained with ASB was more important in subjects with IHCL greater than 60 mmol/l than in subjects with low IHCL. ALT decreased significantly with SSB only in subjects with IHCL greater than 60 mmol/l. There was otherwise no significant effect of ASB on body weight, VAT, or metabolic markers. CONCLUSIONS: In subjects with overweight or obesity and a high SSB intake, replacing SSB with ASB decreased intrahepatic fat over a 12-week period.
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Caffeine extraction procedures from water soluble and water insoluble materials for preparing stimulating beverages are described. Water soluble materials used were instant tea and coffee and water insoluble materials were, among others, guaraná powder and maté leaves. The extraction of caffeine from water soluble materials, especially instant tea, is more suitable for an organic chemistry teaching laboratory than the classic experiment using tea leaves, due to the economy of time and a larger amount of extracted caffeine. The procedure is time-saving and requires only a four-hour period. The experiments illustrate the extraction process as used in undergraduate organic chemistry laboratories.
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Coffee is one of the beverages most widely consumed in the world and the "cafezinho" is normally prepared from a blend of roasted powder of two species, Coffea arabica and Coffea canephora. Each one exhibits differences in their taste and in the chemical composition, especially in the caffeine percentage. There are several procedures proposed in the literature for caffeine determination in different samples like soft drinks, coffee, medicines, etc but most of them need a sample workup which involves at least one step of purification. This work describes the quantitative analysis of caffeine using ¹H NMR and the identification of the major components in commercial coffee samples using 1D and 2D NMR techniques without any sample pre-treatment.
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The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.
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A method using LC/ESI-MS/MS for the quantitative analysis of Ochratoxin A in roasted coffee was described. Linearity was demonstrated (r = 0.9175). The limits of detection and quantification were 1.0 and 3.0 ng g-1, respectively. Trueness, repeatability and intermediate precision values were 89.0-108.8%; 2.4-13.7%; 12.5-17.8%, respectively. To the best of our knowledge, this is the first report in which Ochratoxin A in roasted coffee is analysed by LC/ESI-MS/MS, contributing to the field of mycotoxin analysis, and it will be used for future production of Certified Reference Material.
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A simple and sensitive method has been proposed for the determination of sibutramine-HCl in energy drinks, green tea and pharmaceutical formulations using differential pulse voltammetry performed on a hanging mercury drop electrode. In the chosen experimental condition (Mcllvaine pH 4.0 buffer, 50 mV pulse amplitude and 40 mV s-1 scan velocity), sibutramine-HCl presented a reversible behavior and a peak maximum at -80 mV. Detection limit was 0.4 mg L-1 and the working linear range extended up to 33.3 mg L-1 (r = 0.99). Analysis of real and fortified samples enabled recoveries between 91 and 102%. The electroanalytical method was compared with a HPLC method which indicated it accuracy.
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A new cloud point extraction (CPE) method was developed for the separation and preconcentration of copper (II) prior to spectrophotometric analysis. For this purpose, 1-(2,4-dimethylphenyl) azonapthalen-2-ol (Sudan II) was used as a chelating agent and the solution pH was adjusted to 10.0 with borate buffer. Polyethylene glycol tert-octylphenyl ether (Triton X-114) was used as an extracting agent in the presence of sodium dodecylsulphate (SDS). After phase separation, based on the cloud point of the mixture, the surfactant-rich phase was diluted with acetone, and the enriched analyte was spectrophotometrically determined at 537 nm. The variables affecting CPE efficiency were optimized. The calibration curve was linear within the range 0.285-20 µg L-1 with a detection limit of 0.085 µg L-1. The method was successfully applied to the quantification of copper in different beverage samples.
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The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.