4 resultados para Environmental variation

em Aston University Research Archive


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Fifteen Miscanthus genotypes grown in five locations across Europe were analysed to investigate the influence of genetic and environmental factors on cell wall composition. Chemometric techniques combining near infrared reflectance spectroscopy and conventional chemical analyses were used to construct calibration models for determination of acid detergent lignin, acid detergent fibre, and neutral detergent fibre from sample spectra. The developed equations were shown to predict cell wall components with a good degree of accuracy and significant genetic and environmental variation was identified. The influence of nitrogen and potassium fertiliser on the dry matter yield and cell wall composition of M. x giganteus was investigated. A detrimental affect on feedstock quality was observed to result from application of these inputs which resulted in an overall reduction in concentrations of cell wall components and increased accumulation of ash within the biomass. Pyrolysis-gas chromatography-mass spectrometry and thermo-gravimetric analysis indicates that genotypes other than the commercially cultivated M. x giganteus have potential for use in energy conversion processes and in the bio-refining. The yields and quality parameters of the pyrolysis liquids produced from Miscanthus compared favourably with that produced from SRC willow and produced a more stable pyrolysis liquid with a higher lower heating value. Overall, genotype had a more significant effect on cell wall composition than environment. This indicates good potential for dissection of this trait by QTL analysis and also for plant breeding to produce new genotypes with improved feedstock characteristics for energy conversion.

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Fifteen Miscanthus genotypes grown in five locations across Europe were analysed to investigate the influence of genetic and environmental factors on cell wall composition. Chemometric techniques combining near infrared reflectance spectroscopy (NIRS) and conventional chemical analyses were used to construct calibration models for determination of acid detergent lignin (ADL), acid detergent fibre (ADF), and neutral detergent fibre (NDF) from sample spectra. Results generated were subsequently converted to lignin, cellulose and hemicellulose content and used to assess the genetic and environmental variation in cell wall composition of Miscanthus and to identify genotypes which display quality traits suitable for exploitation in a range of energy conversion systems. The NIRS calibration models developed were found to predict concentrations with a good degree of accuracy based on the coefficient of determination (R2), standard error of calibration (SEC), and standard error of cross-validation (SECV) values. Across all sites mean lignin, cellulose and hemicellulose values in the winter harvest ranged from 76–115 g kg-1, 412–529 g kg-1, and 235–338 g kg-1 respectively. Overall, of the 15 genotypes Miscanthus x giganteus and Miscanthus sacchariflorus contained higher lignin and cellulose concentrations in the winter harvest. The degree of observed genotypic variation in cell wall composition indicates good potential for plant breeding and matching feedstocks to be optimised to different energy conversion processes.

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The thesis is concerned with relationships between profit, technology and environmental change. Existing work has concentrated on only a few questions, treated at either micro or macro levels of analysis. And there has been something of an impasse since the neoclassical and neomarxist approaches are either in direct conflict (macro level), or hardly interact (micro level). The aim of the thesis was to bypass this impasse by starting to develop a meso level of analysis that focusses on issues largely ignored in the traditional approaches - on questions about distribution. The first questions looked at were descriptive - what were the patterns of distribution over time of the variability in types and rates of environmental change, and in particular, was there any evidence of periodization? Two case studies were used to examine these issues. The first looked at environmental change in the iron and steel industry since 1700, and the second studied pollution in five industries in the basic processing sector. It was established that environmental change has been markedly periodized, with an apparently fairly regular `cycle length' of about fifty years. The second questions considered were explanatory - whether and how this periodization could be accounted for by reference to variations in aspects of profitability and technical change. In the iron and steel industry, it was found that diffusion rates and the rate of nature of innovation were periodized on the same pattern as was environmental change. And the same sort of variation was also present in the realm of profits, as evidenced by cyclical changes in output growth. Simple theoretical accounts could be given for all the empirically demonstrable links, and it was suggested that the most useful models at this meso level of analysis are provided by structural change models of economic development.

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Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty. © 2009 Springer Berlin Heidelberg.