Resumo: Neste trabalho caracterizaram-se amostras de solo e substâncias húmicas (SH) extraídas de diferentes solos da Bacia do Médio Rio Negro e também determinaram-se a capacidade de complexação de íons Hg(II) por SH e constantes de troca entre espécies metálicas originalmente complexadas às SH por íons Hg(II). As amostras de solos foram caracterizadas através do teor de matéria orgânica, análises elementar e granulométrica. Os resultados mostraram que os teores de matéria orgânica para as amostras de solo diminuíram com a profundidade. Com base nos resultados de análise granulométrica feita nas amostras de solos, caracterizou-se o aumento dos teores de argila em função da profundidade com a conseqüente diminuição dos teores de areia e silte. As substâncias húmicas extraídas de amostras de solos coletados na Bacia do Médio Rio Negro-AM foram caracterizados por análise elementar, ressonância paramagnética eletrônica e ressonância magnética nuclear. Os resultados mostraram que, em função da profundidade, os valores das razões atômicas C/N foram praticamente constantes ao contrário das razões C/O e C/H, as quais diminuíram. As concentrações de radicais livres do tipo semi-quinona das substâncias húmicas variaram de 0,08 a 5,38 x 1018 spins g-1 de carbono, indicando diferença entre os níveis de humificação das SH extraídas de solos amazônicos. As SH extraídas de solos de regiões alagáveis apresentaram maiores concentrações de spins em relação às SH extraídas de regiões não alagáveis, indicando influência da umidade no processo de humificação. / Abstract: In this research were characterized humic substances (HS) and soil samples extracted from Rio Negro-AM Medium Basin and capacity of complexation (CC) of Hg(II) by HS and constants of exchange between metallic species originally complexed in the HS by Hg(II) had also been determined. The soil samples were characterized through organic material composition, elemental and granulometry analysis. The results showed decreasing of the organic material composition with the depth. According to the results taken, was characterized an increasing in the composition of clay with the depth, but in the other hand, a reduction in silt and sand composition. The humic substances extracted of soil samples from Rio Negro-AM Medium Basin were characterized by elemental analysis, electronic paramagnetic resonance and nuclear magnetic resonance. The results had shown that, in function of the depth, the atomic ratio values C/N were constants, while the atomic ratio C/O and C/H decresed. The concentrations of free radicals of the humic substances were 0.08 to 5.38 x 1018 spins g-1 of carbon, indicating difference in the humification levels of HS extracted from Amazonian soils. The HS extracted in flooded regions showed bigger spins concentrations comparing to ones extracted in unflooded regions, showing that the humidity influences in the process of humification. The NMR of 13C dates showed the sequence of percentage of kind of carbon: aliphatic > ethers/hydroxyls > carboxyls/esthers/amides > aromatics > phenols @ carbonyls of aldehydes and ketones for HS samples extracted of the differences profiles of the Amazonian soils studied. / Orientador: André Henrique Rosa / Coorientador: Julio Cesar Rocha / Banca: Wilson Tadeu Lopes da Silva / Banca: Marisa Veiga Capela / Banca: Isabele Rodrigues Nascimento / Banca: Ézio Sargentini Junior / Doutor

O solo é um compartimento ambiental altamente complexo e, em razão do crescimento populacional acelerado e da intensa atividade industrial e agrícola, tem sofrido com a contaminação de substâncias de origens diversas. Entre as principais atividades que contribuem para a perturbação da qualidade dos solos estão as atividades de geração de energia pela queima de combustíveis fósseis, como o carvão mineral. Dentre as substâncias presentes nos rejeitos do carvão queimado em usinas termelétricas estão compostos orgânicos e metais pesados que interagem com o material genético, produzindo mutações e acarretando prejuízos em nível de organismo (como as neoplasias), mas também em níveis maiores de organização biológica (como a perda de diversidade genética em populações). Estudos de avaliação do potencial mutagênico em amostras de solo são escassos, principalmente investigando a ação de mutágenos de origem inorgânica. Além disso, estudos de mutagênese em solos sob a influência de rejeitos de carvão têm sido pouco abordados na literatura. Desta forma, os objetivos deste trabalho foram: (i) testar um protocolo para avaliação de atividade mutagênica em extratos inorgânicos e orgânicos de solo; (ii) avaliar a presença e o perfil dos compostos mutagênicos em solos sob a influência de cinzas de carvão e (iii) investigar as rotas ambientais para dispersão dos compostos mutagênicos na área de estudo. Para atingir estes objetivos, processos de extração de compostos orgânicos e inorgânicos de solo foram testados quanto a sua eficiência em extrair da amostra compostos potencialmente mutagênicos frente a linhagem de Salmonella typhimurium que detecta erro no quadro de leitura (TA98). Os protocolos mais eficientes foram utilizados para os testes com diferentes amostras de solo sob a influência de rejeitos de carvão utilizando diversas linhagens, na ausência e presença de ativação metabólica (fração S9 mix). Os resultados de mutagênese associados aos resultados da caracterização química de compostos orgânicos e metais indicaram que os contaminantes presentes nas cinzas de carvão podem se dispersar com facilidade para áreas adjacentes. Essa abordagem de estudo permitiu relacionar a presença de determinadas classes de compostos com diferentes danos no DNA e inferir distintas rotas ambientais de dispersão para esses compostos. A realização deste trabalho ressalta a importância de estudos em matrizes ambientais complexas, em especial solos contaminados, que buscam integrar os dados de mutagênese e utilizá-los sob uma perspectiva ecológica. / Soil is a highly complex environmental compartment that has suffered contamination by substances from multiple sources mainly due to fast population growth and intense industrial and agricultural activity. Among the main activities that affect soil quality are power generation activities that use fossil fuels, such as mineral coal. Among the several compounds present in coal ashes that are employed in coal-fired power plants are substances that interact with the genetic material, causing mutations and/or damage at the individual level (like neoplasias) but also at higher levels of biological organization (like loss of genetic diversity in populations). There are few studies on the mutagenic potential of soil samples, especially those that investigate the action of mutagens from inorganic sources. Moreover, studies of mutagenesis in soils under the influence of coal-fired power plants have rarely been reported in literature. Thus, this work aimed at: (i) testing a protocol for the evaluation of mutagenic activity in inorganic and organic extracts from soil samples; (ii) evaluating the presence and the profile of mutagenic compounds in soils under the influence of coal ashes and (iii) investigating environmental routes of dispersion of mutagenic compounds in the study area. In order to achieve these aims, extraction processes for inorganic and organic compounds were tested concerning their efficiency to extract compounds potentially mutagenic to the specific Salmonella typhimurium strain that detects frameshift mutagens (TA98). The most efficient protocols were further utilized for the tests with different soil samples under the influence of coal-fired power plant using several strains, in absence and presence of metabolic activation (S9 mix fraction). Mutagenesis results associated with the chemical characterization of the organic compounds and metals indicated that contaminants present in coal ashes can be easily dispersed to adjacent areas. This approach allowed relating the presence of certain classes of compounds to specific damages in DNA and inferring distinct dispersion routes for these compounds. This work highlights the importance of studies concerning complex environmental matrices, specially contaminated soils, which seek the integration of mutagenesis data and their use from an ecological perspective.

This study focuses on emerging E. coil serotypes and has developed methods for the isolation and identification of non-0157 STEC and EPEC. A basal medium for the isolation of these pathogens was developed as well as a serogroup specific PCR assay for the detection of the 02 serogroup. These culture and molecular based techniques have proven to be valuable in the detection, identification, and epidemiological investigation of these groups of emerging pathogens. These methods were applied to 1) a farm study, whereby samples (faecal and soil) and 2) an abattoir study, whereby samples (hide and carcass) were analysed for the presence of non-0157 STEC and EPEC. Isolates were subsequently characterised in terms of serotype/serogroup and virulence markers. The data generated by this work has illustrated the extent of non-0157 STEC and EPEC contamination in the farm and abattoir environments, thus providing scientific background upon which control strategies may be based.

Made available in DSpace on 2016-06-02T19:05:37Z (GMT). No. of bitstreams: 1 2176.pdf: 7940164 bytes, checksum: 98727460db08f23e4e24aa4a4b695d4d (MD5) Previous issue date: 2008-08-28 / This work presents a Virtual Reality environment dedicated to the analysis of tomographic images of Soil Science. Its architecture uses models proceeding from a volumetric (3-D) reconstruction algorithm, summed with several graphics processes of manipulation and visualization, in a way to provide immersion and interaction of the user with the virtual scene. Its validation was performed based on a case study involving the analysis of the porosity of the agricultural soil samples, which presents preferential paths for the water and solute flow (fingering). Results illustrate the consistent verification of the preferential paths of the agricultural soil samples, analyzed based on the developed environment. / Este trabalho apresenta um ambiente de Realidade Virtual dedicado à análise de imagens tomográficas da Ciência do Solo. Sua arquitetura utiliza modelos provenientes de um algoritmo de reconstrução volumétrica (3-D) adicionado a diversos processos gráficos de manipulação e visualização, de tal forma a possibilitar imersão e interação do usuário com a cena virtual. Sua validação foi realizada com base em um estudo de caso envolvendo análise de porosidade de amostras de solos agrícolas, os quais apresentam caminhos preferenciais para o fluxo de água e solutos (fingering). Resultados ilustram a verificação consistente dos caminhos preferenciais das amostras de solos agrícolas, analisadas com base no ambiente desenvolvido.

No / The roadside vegetation in some counties of north England (north and west Yorkshire) was studied to determine the community structure according to the British National Vegetation Classification (NVC) and main environmental factors influencing its composition. The data from Phytosociological survey (699 quadrats) and from the physico-chemical analyses of 233 soil samples from 35 sites were obtained. Both the classification (TWINSPAN & MATCH) and ordination programs (Canonical Correspondence Analysis) were used. The roadside vegetation is mainly dominated by few grasses (Arrhenatherum elatius, Festuca rubra, Dactylis glomerata, Lolium perenne, Poa trivialis, Elymus repens, Holcus lanatus) and their associated herbs (Cirsium arvense, Heracleum sphondylium, Urtica dioica). Five NVC Mesotrophic grassland communities (Arrhenatheretum elatioris community MG1, Lolium perenne-Cynosurus cristatus grassland MG6, Lolium perenne leys MG7, Holcus lanatus- Deschampsia cespitosa grassland MG9, Festuca rubra-Agrostis stolonifera-Potentilla anserina grassland MG11) and one Upland Festuca ovina- Agrostis capillaris-Galium saxatile grassland, U4 were identified which in general, exhibited good fit with the typical NVC units. Altitude, pH, potassium, sodium and road age were found to be the main variables affecting the roadside vegetation. By relating the floristic composition with ecological characteristics of the roadside verges, three kinds of pattern of variation are observed. The first pattern is related to regional or geographical characteristics and the second pattern of variation exists across the width of the road verges showing a zonal pattern of plant distribution. The third scale of pattern is active at the local level including micro-environmental conditions, e.g., local edaphic variables.

This thesis has a theoretical and a practical part. The first part contains theoretical introduction to the phenomenon of increased stiffness at very small strains and possibilities of its practical applications. The available methods for evaluating initial shear modulus tests are described below. Increased attention is paid to the method of evaluation of test data in the frequency domain using the Fourier transform. The last chapter in this part describes an algorithm designed for automatic evaluation of measurements in the frequency domain. The practical part deals with measurement and evaluation of initial shear modulus for Brno clay as a function of vertical stress in oedometric test. Firstly, a device is presented that allows the extension of the oedometric test with sensors for measuring initial shear modulus of soil. This device was designed for the test in this thesis. Subsequently, the test plan is described including description of all soil samples. In this thesis, several types of soil samples from a single site were tested. Next, the results of the individual tests are evaluated by the selected methods. Examples are used for showing the differences in evaluation of the same data by other methods. At the end, the results of the individual tests for all sample types are compared with each other and with data from literature.

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<p dir="ltr">Digital soil mapping (DSM) combines field and laboratory data with environmental factors to predict soil properties. The accuracy of these predictions depends on factors such as model selection, data quality and quantity, and landscape characteristics. In our study, we investigated the impact of sample density and the use of various environmental covariates (ECs) including slope, topographic position index, topographic wetness index, multiresolution valley bottom flatness, and multiresolution ridge top flatness, as well as the spatial resolution of these ECs on the predictive accuracy of four predictive models; Cubist (CB), Random Forest (RF), Regression Kriging (RK), and Ordinary Kriging (OK). Our analysis was conducted at three sites in Indiana: the Purdue Agronomy Center for Research and Education (ACRE), Davis Purdue Agriculture Center (DPAC), and Southeast Purdue Agricultural Center (SEPAC). Each site had its unique soil data sampling designs, management practices, and topographic conditions. The primary focus of this study was to predict the spatial distribution of soil properties, including soil organic matter (SOM), cation exchange capacity (CEC), and clay content, at different depths (0-10cm, 0-15cm, and 10-30cm) by utilizing five environmental covariates and four spatial resolutions for the ECs (1-1.5 m, 5 m, 10 m, and 30 m).</p><p dir="ltr">Various evaluation metrics, including R², root mean square error (RMSE), mean square error (MSE), concordance coefficient (pc), and bias, were used to assess prediction accuracy. Notably, the accuracy of predictions was found to be significantly influenced by the site, sample density, model type, soil property, and their interactions. Sites exhibited the largest source of variation, followed by sampling density and model type for predicted SOM, CEC, and clay spatial distribution across the landscape.</p><p dir="ltr">The study revealed that the RF model consistently outperformed other models, while OK performed poorly across all sites and properties as it only relies on interpolating between the points without incorporating the landscape characteristics (ECs) in the algorithm. Increasing sample density improved predictions up to a certain threshold (e.g., 66 samples at ACRE for both SOM and CEC; 58 samples for SOM and 68 samples for CEC at SEPAC), beyond which the improvements were marginal. Additionally, the study highlighted the importance of spatial resolution, with finer resolutions resulting in better prediction accuracy, especially for SOM and clay content. Overall, comparing data from the two depths (0-10cm vs 10-30cm) for soil properties predications, deeper soil layer data (10-30cm) provided more accurate predictions for SOM and clay while shallower depth data (0-10cm) provided more accurate predictions for CEC. Finally, higher spatial resolution of ECs such as 1-1.5 m and 5 m contributed to more accurate soil properties predictions compared to the coarser data of 10 m and 30 m resolutions.</p><p dir="ltr">In summary, this research underscores the significance of informed decisions regarding sample density, model selection, and spatial resolution in digital soil mapping. It emphasizes that the choice of predictive model is critical, with RF consistently delivering superior performance. These findings have important implications for land management and sustainable land use practices, particularly in heterogeneous landscapes and areas with varying management intensities.</p>