995 resultados para Coffee quality


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Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

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Despite the increasing acknowledgment of scholars and practitioners that many large-scale agricultural land acquisitions in developing countries fail or never materialize, empirical evidence about how and why they fail to date is still scarce. Too often, land deals are portrayed as straightforward investments and their success is taken for granted. Looking at the coffee sector in Laos, the authors of this article explore dimensions of the land grab debate that have not yet been sufficiently examined. Coffee concessionaires in southern Laos often fail to use all of the land granted them and fail to produce high yields on the land they do use. Thus, the authors challenge the often-assumed superiority and effectiveness of large-scale versus small-scale production, specifically the argument that they modernize agricultural production and optimize land use. They argue that examining failed investments is as important as studying successful ones for understanding the implications of the land grabbing phenomenon for social, economic, and environmental outcomes. Knowledge about the scale of “failed land deals” provides important motivation for national governments to close the gap between intentions and actual outcomes. This article engages with the current debate on quality of investment and challenges the approach of employing land concessions as a vehicle for economic development in the Lao coffee sector and in other sectors and countries.

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The moist evergreen Afromontane forest of SW Ethiopia has become extremely fragmented and most remnants are intensively managed for cultivation of coffee (Coffea arabica). We investigated the distributions of epiphytic orchids in shade trees and their understory in forests with contrasting management intensity to determine biodiversity losses associated with coffee cultivation and to determine the capacity of coffee shrubs to act as refugia for orchid species. We studied epiphytic orchids in managed forests and natural forests and recorded orchid diversity and abundance in different tree zones of 339 trees and in the understory. Coffee management was associated with a downward shift of orchid species as orchid species were occurring in significantly lower tree zones in managed forest. The number of shrubs in the understory of managed forest was not higher than in natural forests, yet orchid abundance was higher in the understory of managed forests. Local extinctions of epiphytic orchids and species losses in the outer tree zones (a contraction of habitat) in managed forests are most likely driven by losses of large, complex-structured climax trees, and changes in microclimate, respectively. Coffee shrubs and their shade trees in managed forests are shown here to be a suitable habitat for only a limited set of orchid species. As farmers continue to convert natural forest into managed forest for coffee cultivation, further losses of habitat quality and collateral declines in regional epiphytic orchid diversity can be expected. Therefore, the conservation of epiphytic orchid diversity, as well as other components of diversity of the coffee forests, must primarily rely on avoiding coffee management intensification in the remaining natural forest. Convincing farmers to keep forest-climax trees in their coffee forest and to tolerate orchids on their coffee shrubs may also contribute to a more favorable conservation status of orchids in Ethiopian coffee agroecosystems.

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In coffee processing the fermentation stage is considered one of the critical operations by its impact on the final quality of the product. However, the level of control of the fermentation process on each farm is often not adequate; the use of sensorics for controlling coffee fermentation is not common. The objective of this work is to characterize the fermentation temperature in a fermentation tank by applying spatial interpolation and a new methodology of data analysis based on phase space diagrams of temperature data, collected by means of multi-distributed, low cost and autonomous wireless sensors. A real coffee fermentation was supervised in the Cauca region (Colombia) with a network of 24 semi-passive TurboTag RFID temperature loggers with vacuum plastic cover, submerged directly in the fermenting mass. Temporal evolution and spatial distribution of temperature is described in terms of the phase diagram areas which characterizes the cyclic behaviour of temperature and highlights the significant heterogeneity of thermal conditions at different locations in the tank where the average temperature of the fermentation was 21.2 °C, although there were temperature ranges of 4.6°C, and average spatial standard deviation of ±1.21ºC. In the upper part of the tank we found high heterogeneity of temperatures, the higher temperatures and therefore the higher fermentation rates. While at the bottom, it has been computed an area in the phase diagram practically half of the area occupied by the sensors of the upper tank, therefore this location showed higher temperature homogeneity

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The fermentation stage is considered to be one of the critical steps in coffee processing due to its impact on the final quality of the product. The objective of this work is to characterise the temperature gradients in a fermentation tank by multi-distributed, low-cost and autonomous wireless sensors (23 semi-passive TurboTag® radio-frequency identifier (RFID) temperature loggers). Spatial interpolation in polar coordinates and an innovative methodology based on phase space diagrams are used. A real coffee fermentation process was supervised in the Cauca region (Colombia) with sensors submerged directly in the fermenting mass, leading to a 4.6 °C temperature range within the fermentation process. Spatial interpolation shows a maximum instant radial temperature gradient of 0.1 °C/cm from the centre to the perimeter of the tank and a vertical temperature gradient of 0.25 °C/cm for sensors with equal polar coordinates. The combination of spatial interpolation and phase space graphs consistently enables the identification of five local behaviours during fermentation (hot and cold spots).

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Long-distance migratory birds are declining globally and migration has been identified as the primary source of mortality in this group. Despite this, our lack of knowledge of habitat use and quality at stopovers, i.e., sites where the energy for migration is accumulated, remains a barrier to designing appropriate conservation measures, especially in tropical regions. There is therefore an urgent need to assess stopover habitat quality and concurrently identify efficient and cost-effective methods for doing so. Given that fuel deposition rates directly influence stopover duration, departure fuel load, and subsequent speed of migration, they are expected to provide a direct measure of habitat quality and have the advantage of being measurable through body-mass changes. Here, we examined seven potential indicators of quality, including body-mass change, for two ecologically distinct Neotropical migratory landbirds on stopover in shade-coffee plantations and tropical humid premontane forest during spring migration in Colombia: (1) rate of body-mass change; (2) foraging rate; (3) recapture rate; (4) density; (5) flock size; (6) age and sex ratios; and (7) body-mass distribution. We found higher rates of mass change in premontane forest than in shade-coffee in Tennessee Warbler Oreothlypis peregrina, a difference that was mirrored in higher densities and body masses in forest. In Gray-cheeked Thrush Catharus minimus, a lack of recaptures in shade-coffee and higher densities in forest, also suggested that forest provided superior fueling conditions. For a reliable assessment of habitat quality, we therefore recommend using a suite of indicators, taking into account each species’ ecology and methodological considerations. Our results also imply that birds stopping over in lower quality habitats may spend a longer time migrating and require more stopovers, potentially leading to important carryover effects on reproductive fitness. Evaluating habitat quality is therefore imperative prior to defining the conservation value of newly identified stopover regions.

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Miami-Dade County has approximately 27,000 people living with HIV (PLWH), and the highest HIV incidence in the nation. PLWH have reported several types of sleep disturbances. Caffeine is an anorexic and lipolytic stimulant that may adversely affect sleep patterns, dietary intakes and body composition. High caffeine consumption (>250 mg. per day or the equivalent of >4 cups of brewed coffee) may also affect general functionality, adherence to antiretroviral treatment (ART) and HIV care. This study assess the relationship of high caffeine intake with markers of disease progression, sleep quality, insomnia, anxiety, nutritional intakes and body composition. A convenience sample of 130 PLWH on stable ART were recruited from the Miami Adult Studies on HIV (MASH) cohort, and followed for three months. After consenting, questionnaires on Modified Caffeine Consumption (MCCQ), Pittsburg Insomnia Rating Scale (PIRS), Pittsburg Sleep Quality Index (PSQI), Generalized Anxiety Disorder-7 (GAD-7), socio-demographics, drug and medication use were completed. CD4 count, HIV viral load, anthropometries, and body composition measures were obtained. Mean age was 47.89±6.37 years, 60.8% were male and 75.4% were African-Americans. Mean caffeine intake at baseline was 337.63 ± 304.97 mg/day (Range: 0-1498 mg/day) and did not change significantly at 3 months. In linear regression, high caffeine consumption was associated with higher CD4 cell count (β=1.532, P=0.049), lower HIV viral load (β=-1.067, P=0.048), higher global PIRS (β=1.776, P=0.046), global PSQI (β=2.587, P=0.038), and GAD-7 scores (β=1.674, P=0.027), and with lower fat mass (β=-0.994, P=0.042), energy intakes (β=-1.643, P=0.042) and fat consumption (β=-1.902, P=0.044), adjusting for relevant socioeconomic and disease progression variables. Over three months, these associations remained significant. The association of high caffeine with lower BMI weakened when excluding users of other anorexic and stimulant drugs such as cocaine and methamphetamine, suggesting that caffeine in combination, but not alone, may worsen their action. In summary, high caffeine consumption was associated with better measures of disease progression; but was also detrimental on sleep quality, nutritional intakes, BMI and body composition and associated with insomnia and anxiety. Large scale studies for longer time are needed to elucidate the contribution of caffeine to the well-being of PLWH.

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In Colombia coffee production is facing risks due to an increase in the variability and amount of rainfall, which may alter hydrological cycles and negatively influence yield quality and quantity. Shade trees in coffee plantations, however, are known to produce ecological benefits, such as intercepting rainfall and lowering its velocity, resulting in a reduced net-rainfall and higher water infiltration. In this case study, we measured throughfall and soil hydrological properties in four land use systems in Cauca, Colombia, that differed in stand structural parameters: shaded coffee, unshaded coffee, secondary forest and pasture. We found that throughfall was rather influenced by stand structural characteristics than by rainfall intensity. Lower throughfall was recorded in the shaded coffee compared to the other systems when rain gauges were placed at a distance of 1.0 m to the shade tree. The variability of throughfall was high in the shaded coffee, which was due to different canopy characteristics and irregular arrangements of shade tree species. Shaded coffee and secondary forest resembled each other in soil structural parameters, with an increase in saturated hydraulic conductivity and microporosity, whereas bulk density and macroporosity decreased, compared to the unshaded coffee and pasture. In this context tree-covered systems indicate a stronger resilience towards changing rainfall patterns, especially in mountainous areas where coffee is cultivated.

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OBJECTIVE: To evaluate the scored Patient-generated Subjective Global Assessment (PG-SGA) tool as an outcome measure in clinical nutrition practice and determine its association with quality of life (QoL). DESIGN: A prospective 4 week study assessing the nutritional status and QoL of ambulatory patients receiving radiation therapy to the head, neck, rectal or abdominal area. SETTING: Australian radiation oncology facilities. SUBJECTS: Sixty cancer patients aged 24-85 y. INTERVENTION: Scored PG-SGA questionnaire, subjective global assessment (SGA), QoL (EORTC QLQ-C30 version 3). RESULTS: According to SGA, 65.0% (39) of subjects were well-nourished, 28.3% (17) moderately or suspected of being malnourished and 6.7% (4) severely malnourished. PG-SGA score and global QoL were correlated (r=-0.66, P<0.001) at baseline. There was a decrease in nutritional status according to PG-SGA score (P<0.001) and SGA (P<0.001); and a decrease in global QoL (P<0.001) after 4 weeks of radiotherapy. There was a linear trend for change in PG-SGA score (P<0.001) and change in global QoL (P=0.003) between those patients who improved (5%) maintained (56.7%) or deteriorated (33.3%) in nutritional status according to SGA. There was a correlation between change in PG-SGA score and change in QoL after 4 weeks of radiotherapy (r=-0.55, P<0.001). Regression analysis determined that 26% of the variation of change in QoL was explained by change in PG-SGA (P=0.001). CONCLUSION: The scored PG-SGA is a nutrition assessment tool that identifies malnutrition in ambulatory oncology patients receiving radiotherapy and can be used to predict the magnitude of change in QoL.