741 resultados para INTEGRATED CULTIVATION


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Stream-water flows and in-stream nitrate and ammonium concentrations in a small (36.7 ha) Atlantic Forest catchment were simulated using the Integrated Nitrogen in CAtchments (INCA) model version 1.9.4. The catchment, at Cunha, is in the Serra do Mar State Park, SE Brazil and is nearly pristine because the nearest major conurbations, Sao Paulo and Rio, are some 450 km distant. However, intensive farming may increase nitrogen (N) deposition and there are growing pressures for urbanisation. The mean-monthly discharges and NO3-N concentration dynamics were simulated adequately for the calibration and validation periods with (simulated) loss rates of 6.55 kg.ha(-1) yr(-1) for NO3-N and 3.85 kg.ha(-1) yr(-1) for NH4-N. To investigate the effects of elevated levels of N deposition in the future, various scenarios for atmospheric deposition were simulated; the highest value corresponded to that in a highly polluted area of Atlantic Forest in Sao Paulo City. It was found that doubling the atmospheric deposition generated a 25% increase in the N leaching rate, while at levels approaching the highly polluted Sao Paulo deposition rate, five times higher than the current rate, leaching increased by 240%, which would create highly eutrophic conditions, detrimental to downstream water quality. The results indicate that the INCA model can be useful for estimating N concentration and fluxes for different atmospheric deposition rates and hydrological conditions.

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A semi-distributed model, INCA, has been developed to determine the fate and distribution of nutrients in terrestrial and aquatic systems. The model simulates nitrogen and phosphorus processes in soils, groundwaters and river systems and can be applied in a semi-distributed manner at a range of scales. In this study, the model has been applied at field to sub-catchment to whole catchment scale to evaluate the behaviour of biosolid-derived losses of P in agricultural systems. It is shown that process-based models such as INCA, applied at a wide range of scales, reproduce field and catchment behaviour satisfactorily. The INCA model can also be used to generate generic information for risk assessment. By adjusting three key variables: biosolid application rates, the hydrological connectivity of the catchment and the initial P-status of the soils within the model, a matrix of P loss rates can be generated to evaluate the behaviour of the model and, hence, of the catchment system. The results, which indicate the sensitivity of the catchment to flow paths, to application rates and to initial soil conditions, have been incorporated into a Nutrient Export Risk Matrix (NERM).

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An integrated approach to climate change impact assessment is explored by linking established models of regional climate (SDSM), water resources (CATCHMOD) and water quality (INCA) within a single framework. A case study of the River Kennet illustrates how the system can be used to investigate aspects of climate change uncertainty, deployable water resources, and water quality dynamics in upper and lower reaches of the drainage network. The results confirm the large uncertainty in climate change scenarios and freshwater impacts due to the choice of general circulation model (GCM). This uncertainty is shown to be greatest during summer months as evidenced by large variations between GCM-derived projections of future tow river flows, deployable yield from groundwater, severity of nutrient flushing episodes, and Long-term trends in surface water quality. Other impacts arising from agricultural land-use reform or delivery of EU Water Framework Directive objectives under climate change could be evaluated using the same framework. (c) 2006 Elsevier B.V. All rights reserved.

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Consumption of green leafy vegetables is associated with reduced risk of several types of cancer and cardiovascular disease. These beneficial effects are attributed to a range of phytochemicals including flavonoids and glucosinolates, both of which are found in high levels in Brassicaceous crops. Rocket is the general name attributed to cultivars of Eruca sativa and Diplotaxis tenufolia, known as salad rocket and wild rocket, respectively. We have shown that different light levels during the cultivation period of these crops have a significant impact on the levels of flavonoids present in the crop at harvest, with over 15-fold increase achieved in quercetin, isorhamnetin, and cyanidin in high light conditions. Postharvest storage further affects the levels of both flavonoids and glucosinolates, with cyanidin increasing during shelf life and some glucosinolates, such as glucoiberverin, being reduced over the same storage period. In vitro assays using human colon cell lines demonstrate that glucosinolate-rich extracts of Eruca sativa cv. Sky, but not Diplotaxis tenufolia cv. Voyager, confer significant resistance to oxidative stress on the cells, which is indicative of the chemoprotective properties of the leaves from this species. Our findings indicate that both pre and postharvest environment and genotypic selection, when developing new lines of Brassicaceous vegetables, are important considerations with the goal of improving human nutrition and health.

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This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: ( i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and ( ii) a multimodel system composed of three European coupled ocean - atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated ( i. e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Nino or La Nina years rather than in neutral years.

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The LINK Integrated Farming Systems (LINK-IFS) Project (1992-1997) was setup to compare conventional and integrated arable farming systems (IAFS), concentrating on practical feasibility and economic viability, but also taking into account the level of inputs used and environmental impact. As part of this, an examination into energy use within the two systems was also undertaken. This paper presents the results from that analysis. The data used is from the six sites within the LINK-IFS Project, spread through the arable production areas of England and from the one site in Scotland, covering the 5 years of the project. The comparison of the energy used is based on the equipment and inputs used to produce I kg of each crop within the conventional and integrated rotations, and thereby the overall energy used for each system. The results suggest that, in terms of total energy used, the integrated system appears to be the most efficient. However, in terms of energy efficiency, energy use per kilogram of output, the results are less conclusive. (C) 2003 Elsevier Science B.V. All rights reserved.

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The CGIAR System conducts research to produce international public goods (IPG) that are of wide applicability creating a scientific base which speeds and broadens local adaptive development. Integrated natural resources management (INRM) research is sometimes seen to be very location specific and consequently does not lend itself readily to the production of IPGs. In this paper we analyse ways in which strategic approaches to INRM research can have broad international applicability and serve as useful foundations for the development of locally adapted technologies. The paper describes the evolution of the IPG concept within the CGIAR and elaborates on five major types of IPGs that have been generated from a varied set of recent INRM research efforts. CGIAR networks have both strengths and weaknesses in INRM research and application, with enormous differences in relative research and development capacities, responsibilities and data access of its partners, making programme process evolution critical to acceptance and participation. Many of the lessons learnt regarding challenges and corresponding IPG research approaches are relevant to designing and managing future multi-scale, multi-locational, coordinated INRM programmes involving broad-based partnerships to address complex environmental and livelihood problems for development.

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In the past decade, a number of mechanistic, dynamic simulation models of several components of the dairy production system have become available. However their use has been limited due to the detailed technical knowledge and special software required to run them, and the lack of compatibility between models in predicting various metabolic processes in the animal. The first objective of the current study was to integrate the dynamic models of [Brit. J. Nutr. 72 (1994) 679] on rumen function, [J. Anim. Sci. 79 (2001) 1584] on methane production, [J. Anim. Sci. 80 (2002) 2481 on N partition, and a new model of P partition. The second objective was to construct a decision support system to analyse nutrient partition between animal and environment. The integrated model combines key environmental pollutants such as N, P and methane within a nutrient-based feed evaluation system. The model was run under different scenarios and the sensitivity of various parameters analysed. A comparison of predictions from the integrated model with the original simulation models showed an improvement in N excretion since the integrated model uses the dynamic model of [Brit. J. Nutr. 72 (1994) 6791 to predict microbial N, which was not represented in detail in the original model. The integrated model can be used to investigate the degree to which production and environmental objectives are antagonistic, and it may help to explain and understand the complex mechanisms involved at the ruminal and metabolic levels. A part of the integrated model outputs were the forms of N and P in excreta and methane, which can be used as indices of environmental pollution. (C) 2004 Elsevier B.V All rights reserved.

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Abstracts EU Cost Action 849 .