967 resultados para Supressive Soils


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Grasses, legumes, saltbushes and herbs were evaluated at 6 sites in southern inland Queensland to identify potential pasture and forage plants for use on marginal cropping soils. The region experiences summer heat waves and severe winter frosts. Emphasis was on perennial plants, and native species were included. Seedlings were transplanted into the unfertilized fields in either summer or autumn to suit the growing season of plants, and watered to ensure estab-lishment. Summer-growing grasses were the most successful group, while cool season-growing perennials mostly failed. Summer legumes were disappointing, with Stylosanthes scabra and Indigofera schimperi performing best. Some lines such as I. schimperi and the Eragrostis hybrid cv. Cochise were assessed as potential weeds owing to low animal acceptance. Native Rhynchosia minima grew well at some sites and deserves more study. Cenchrus ciliaris was always easy to establish and produced the highest yields. Persistence of some Digitaria and Bothriochloa species, Eragrostis curvula and Fingerhuthia africana at specific sites was encouraging, but potential weediness needs careful assessment. Standard species were identified to represent the main forage types, such as Austrostipa scabra for cool season-growing grasses, for incorporation into future trials with new genetic materials. The early field testing protocol used should be considered for use elsewhere, if unreliable rainfall poses a high risk of establishment failure from scarce seed.

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Abstract Biochar has significant potential to improve crop performance. This study examined the effect of biochar application on the photosynthesis and yield of peanut crop grown on two soil types. The commercial peanut cultivar Middleton was grown on red ferrosol and redoxi-hydrosol (Queensland, Australia) amended with a peanut shell biochar gradient (0, 0.375, 0.750, 1.50, 3.00 and 6.00 %, w/w, equivalent up to 85 t ha−1) in a glasshouse pot experiment. Biomass and pod yield, photosynthesis-[CO2] response parameters, leaf characteristics and soil properties (carbon, nitrogen (N) and nutrients) were quantified. Biochar significantly improved peanut biomass and pod yield up to 2- and 3-folds respectively in red ferrosol and redoxi-hydrosol. A modest (but significant) biochar-induced improvement of the maximumelectron transport rate and saturating photosynthetic rate was observed for red ferrosol. This response was correlated to increased leaf N and accompanied with improved soil available N and biological N fixation. Biochar application also improved the availability of other soil nutrients, which appeared critical in improving peanut performance, especially on infertile redoxihydrosol. Our study suggests that application of peanut shell derived biochar has strong potential to improve peanut yield on red ferrosol and redoxi-hydrosol. Biochar soil amendment can affect leaf N status and photosynthesis, but the effect varied with soil type.

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- Provided a practical variable-stepsize implementation of the exponential Euler method (EEM). - Introduced a new second-order variant of the scheme that enables the local error to be estimated at the cost of a single additional function evaluation. - New EEM implementation outperformed sophisticated implementations of the backward differentiation formulae (BDF) of order 2 and was competitive with BDF of order 5 for moderate to high tolerances.

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NITROUS OXIDE (N2O) IS a potent greenhouse gas and the predominant ozone-depleting substance in the atmosphere. Agricultural nitrogenous fertiliser use is the major source of human-induced N2O emissions. A field experiment was conducted at Bundaberg from October 2012 to September 2014 to examine the impacts of legume crop (soybean) rotation as an alternative nitrogen (N) source on N2O emissions during the fallow period and to investigate low-emission soybean residue management practices. An automatic monitoring system and manual gas sampling chambers were used to measure greenhouse gas emissions from soil. Soybean cropping during the fallow period reduced N2O emissions compared to the bare fallow. Based on the N content in the soybean crop residues, the fertiliser N application rate was reduced by about 120 kg N/ha for the subsequent sugarcane crop. Consequently, emissions of N2O during the sugarcane cropping season were significantly lower from the soybean cropped soil than those from the conventionally fertilised (145 kg N/ha) soil following bare fallow. However, tillage that incorporated the soybean crop residues into soil promoted N2O emissions in the first two months. Spraying a nitrification inhibitor (DMPP) onto the soybean crop residues before tillage effectively prevented the N2O emission spikes. Compared to conventional tillage, practising no-till with or without growing a nitrogen catch crop during the time after soybean harvest and before cane planting also reduced N2O emissions substantially. These results demonstrated that soybean rotation during the fallow period followed with N conservation management practices could offer a promising N2O mitigation strategy in sugarcane farming. Further investigation is required to provide guidance on N and water management following soybean fallow to maintain sugar productivity.

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Qualitative and quantitative assessment of the fungal flora of rice field soils yielded 102 species of fungi belonging to 44 genera, when dilution plate, soil plate, root-washing and baiting techniques were employed. The order of efficacy of the methods used was: root-washing > soil plate > dilution plate > baiting. Baiting method, used specifically to isolate aquatic and keratinophilic fungi from soils was studied in detail with reference to the former. Qualitatively, corn leaf bait was the most efficient one while pine pollens and hemp seeds were least efficient. A semi-quantitative method was employed to study the statistically significant differences among the different factors used. Among the keratinophilic baits,viz., human hair, fowl’s feather and wool, wool bait was least efficient. The results of this investigation are discussed.

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This thesis deals with the response of biodegradation of selected anthropogenic organic contaminants and natural autochthonous organic matter to low temperature in boreal surface soils. Furthermore, the thesis describes activity, diversity and population size of autotrophic ammonia-oxidizing bacteria (AOB) in a boreal soil used for landfarming of oil-refinery wastes, and presents a new approach, in which the particular AOB were enriched and cultivated in situ from the landfarming soil onto cation exchange membranes. This thesis demonstrates that rhizosphere fraction of natural forest humus soil and agricultural clay loam soil from Helsinki Metropolitan area were capable of degrading of low to moderate concentrations (0.2 50 µg cm-3) of PCP, phenanthrene and 2,4,5-TCP at temperatures realistic to boreal climate (-2.5 to +15 °C). At the low temperatures, the biodegradation of PCP, phenanthrene and 2,4,5-TCP was more effective (Q10-values from 1.6 to 7.6) in the rhizosphere fraction of the forest soil than in the agricultural soil. Q10-values of endogenous soil respiration (carbon dioxide evolution) and selected hydrolytic enzyme activities (acetate-esterase, butyrate-esterase and β-glucosidase) in acid coniferous forest soil were 1.6 to 2.8 at temperatures from -3 to +30 °C. The results indicated that the temperature dependence of decomposition of natural autochthonous soil organic matter in the studied coniferous forest was only moderate. The numbers of AOB in the landfarming (sandy clay loam) soil were determined with quantitative polymerase chain reaction (real-time PCR) and with Most Probable Number (MPN) methods, and potential ammonium oxidation activity was measured with the chlorate inhibition technique. The results indicated presence of large and active AOB populations in the heavily oil-contaminated and urea-fertilised landfarming soil. Assessment of the populations of AOB with denaturing gradient gel electrophoresis (DGGE) profiling and sequence analysis of PCR-amplified 16S rRNA genes showed that Nitrosospira-like AOB in clusters 2 and 3 were predominant in the oily landfarming soil. This observation was supported by fluorescence in situ hybridization (FISH) analysis of the AOB grown on the soil-incubated cation-exchange membranes. The results of this thesis expand the suggested importance of Nitrosospira-like AOB in terrestrial environments to include chronically oil-contaminated soils.

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The increase in global temperature has been attributed to increased atmospheric concentrations of greenhouse gases (GHG), mainly that of CO2. The threat of severe and complex socio-economic and ecological implications of climate change have initiated an international process that aims to reduce emissions, to increase C sinks, and to protect existing C reservoirs. The famous Kyoto protocol is an offspring of this process. The Kyoto protocol and its accords state that signatory countries need to monitor their forest C pools, and to follow the guidelines set by the IPCC in the preparation, reporting and quality assessment of the C pool change estimates. The aims of this thesis were i) to estimate the changes in carbon stocks vegetation and soil in the forests in Finnish forests from 1922 to 2004, ii) to evaluate the applied methodology by using empirical data, iii) to assess the reliability of the estimates by means of uncertainty analysis, iv) to assess the effect of forest C sinks on the reliability of the entire national GHG inventory, and finally, v) to present an application of model-based stratification to a large-scale sampling design of soil C stock changes. The applied methodology builds on the forest inventory measured data (or modelled stand data), and uses statistical modelling to predict biomasses and litter productions, as well as a dynamic soil C model to predict the decomposition of litter. The mean vegetation C sink of Finnish forests from 1922 to 2004 was 3.3 Tg C a-1, and in soil was 0.7 Tg C a-1. Soil is slowly accumulating C as a consequence of increased growing stock and unsaturated soil C stocks in relation to current detritus input to soil that is higher than in the beginning of the period. Annual estimates of vegetation and soil C stock changes fluctuated considerably during the period, were frequently opposite (e.g. vegetation was a sink but soil was a source). The inclusion of vegetation sinks into the national GHG inventory of 2003 increased its uncertainty from between -4% and 9% to ± 19% (95% CI), and further inclusion of upland mineral soils increased it to ± 24%. The uncertainties of annual sinks can be reduced most efficiently by concentrating on the quality of the model input data. Despite the decreased precision of the national GHG inventory, the inclusion of uncertain sinks improves its accuracy due to the larger sectoral coverage of the inventory. If the national soil sink estimates were prepared by repeated soil sampling of model-stratified sample plots, the uncertainties would be accounted for in the stratum formation and sample allocation. Otherwise, the increases of sampling efficiency by stratification remain smaller. The highly variable and frequently opposite annual changes in ecosystem C pools imply the importance of full ecosystem C accounting. If forest C sink estimates will be used in practice average sink estimates seem a more reasonable basis than the annual estimates. This is due to the fact that annual forest sinks vary considerably and annual estimates are uncertain, and they have severe consequences for the reliability of the total national GHG balance. The estimation of average sinks should still be based on annual or even more frequent data due to the non-linear decomposition process that is influenced by the annual climate. The methodology used in this study to predict forest C sinks can be transferred to other countries with some modifications. The ultimate verification of sink estimates should be based on comparison to empirical data, in which case the model-based stratification presented in this study can serve to improve the efficiency of the sampling design.

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The present study examines the shrinkage behaviour of residually derived black cotton (BC) soil and red soil compacted specimens that were subjected to air-drying from the swollen state. The soil specimens were compacted at varying dry density and moisture contents to simulate varied field conditions. The void ratio and moisture content of the swollen specimens were monitored during the drying process and relationship between them is analyzed. Shrinkage is represented as reduction in void ratio with decrease in water content of soil specimens. It is found to occur in three distinct stages. Total shrinkage magnitude depends on the type of clay mineral present. Variation in compaction conditions effect marginally total shrinkage magnitudes of BC soil specimens but have relatively more effect on red soil specimens. A linear relation is obtained between total shrinkage magnitude and volumetric water content of soil specimens in swollen state and can be used to predict the shrinkage magnitude of soils.

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In this paper an approach for obtaining depth and section modulus of the cantilever sheet pile wall using inverse reliability method is described. The proposed procedure employs inverse first order reliability method to obtain the design penetration depth and section modulus of the steel sheet pile wall in order that the reliability of the wall against failure modes must meet a desired level of safety. Sensitivity analysis is conducted to assess the effect of uncertainties in design parameters on the reliability of cantilever sheet pile walls. The analysis is performed by treating back fill soil properties, depth of the water table from the top of the sheet pile wall, yield strength of steel and section modulus of steel pile as random variables. Two limit states, viz., rotational and flexural failure of sheet pile wall are considered. The results using this approach are used to develop a set of reliability based design charts for different coefficients of variation of friction angle of the backfill (5%, 10% and 15%). System reliability considerations in terms of series and parallel systems are also studied.

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The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.