81 resultados para Soil interpretation

em University of Queensland eSpace - Australia


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The reflectance signatures of plantation pine canopy and understorey components were measured using a spectro-radiometer. The aim was to establish whether differences observed in the reflectance signature of stressed and unstressed pine needles were consistent with observed differences in the reflectance of multispectral Landsat Thematic Mapper (TM) images of healthy and stressed forest. Because overall scene reflectance includes the contribution of each scene component, needle reflectance may not be representative of canopy reflectance. In this investigation, a limited dataset of reflectance signatures from stressed and unstressed needles confirmed the negative relationship between pine needle health and reflectance which was observed in visible red wavelengths. However, the reflectance contribution from bushes, pine needle litter and bare soil tended to reinforce this relationship suggesting that in this instance, overall scene reflectance is comprised of the proportional reflectance of each scene component. In near infrared wavelengths, differences between healthy and stressed needle reflectance suggested a strong positive relationship between reflectance and tree health. For Landsat TM images, previous research had only observed a weak positive relationship between stand health and near infrared reflectance in these pine canopies. This suggests that for multispectral Landsat TM images, reflectance of near infrared light from pine canopies may be affected by other factors which may include the scattering of light within canopies. These results are seen as promising for the use of hyperspectral images to detect stand health, provided that pixel reflectance is not influenced by other scene components.

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The use of 'balanced' Ca, Mg, and K ratios, as prescribed by the basic cation saturation ratio (BCSR) concept, is still used by some private soil-testing laboratories for the interpretation of soil analytical data. This review aims to examine the suitability of the BCSR concept as a method for the interpretation of soil analytical data. According to the BCSR concept, maximum plant growth will be achieved only when the soil’s exchangeable Ca, Mg, and K concentrations are approximately 65 % Ca, 10 % Mg, and 5 % K (termed the ‘ideal soil’). This ‘ideal soil’ was originally proposed by Firman Bear and co-workers in New Jersey (USA) during the 1940s as a method of reducing luxury K uptake by alfalfa (Medicago sativa L.). At about the same time, William Albrecht, working in Missouri (USA), concluded through his own investigations that plants require a soil with a high Ca saturation for optimal growth. Whilst it now appears that several of Albrecht’s experiments were fundamentally flawed, the BCSR (‘balanced soil’) concept has been widely promoted, suggesting that the prescribed cationic ratios provide optimum chemical, physical, and biological soil properties. Our examination of data from numerous studies (particularly those of Albrecht and Bear, themselves) would suggest that, within the ranges commonly found in soils, the chemical, physical, and biological fertility of a soil is generally not influenced by the ratios of Ca, Mg, and K. The data do not support the claims of the BCSR, and continued promotion of the BCSR will result in the inefficient use of resources in agriculture and horticulture.

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The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

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This book provides a way for farmers in developing countries to benefit from scientific knowledge on plant nutrition and soil fertility. Specifically, it will help farmers recognise and deal with shortages or excesses of chemical elements.

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Bulk density of undisturbed soil samples can be measured using computed tomography (CT) techniques with a spatial resolution of about 1 mm. However, this technique may not be readily accessible. On the other hand, x-ray radiographs have only been considered as qualitative images to describe morphological features. A calibration procedure was set up to generate two-dimensional, high-resolution bulk density images from x-ray radiographs made with a conventional x-ray diffraction apparatus. Test bricks were made to assess the accuracy of the method. Slices of impregnated soil samples were made using hardsetting seedbeds that had been gamma scanned at 5-mm depth increments in a previous study. The calibration procedure involved three stages: (i) calibration of the image grey levels in terms of glass thickness using a staircase made from glass cover slips, (ii) measurement of ratio between the soil and resin mass attenuation coefficients and the glass mass attenuation coefficient, using compacted bricks of known thickness and bulk density, and (iii) image correction accounting for the heterogeneity of the irradiation field. The procedure was simple, rapid, and the equipment was easily accessible. The accuracy of the bulk density determination was good (mean relative error 0.015), The bulk density images showed a good spatial resolution, so that many structural details could be observed. The depth functions were consistent with both the global shrinkage and the gamma probe data previously obtained. The suggested method would be easily applied to the new fuzzy set approach of soil structure, which requires generation of bulk density images. Also, it would be an invaluable tool for studies requiring high-resolution bulk density measurement, such as studies on soil surface crusts.

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Watson is a fully developed suburb of some 30 years in Canberra (the capital city of Australia), A plunge dip using arsenical pesticides for tick control was operated there between 1946 and 1960, Chemical investigations revealed that many soil samples obtained from the study area contained levels of arsenic exceeding the current health-based investigation levels of 100 mg kg(-1) set by the National Health and Medical Research Council in Australia, For the speciation study, nine composite samples of surface and sub-surface soils and a composite sample of rocks were selected. ICP-MS analysis showed that arsenic levels in these samples ranged from 32 to 1597 mg kg(-1), Chemical speciation of arsenic showed that the arsenite (trivalent) components were 0.32-56% in the soil and 44.8% in the rock composite samples. Using a rat model, the absolute bioavailability of these contaminated soils relative to As3+ or As5+ ranged from 1.02 to 9.87% and 0.26 to 2.98%, respectively, An attempt was made to develop a suitable leachate test as an index of bioavailability. However, the results indicated that there was no significant correlation between the bioavailability and leachates using neutral pH water or 1 M HCl. Our results indicate that speciation is highly significant for the interpretation of bioavailability and risk assessment data; the bioavailable fractions of arsenic in soils from Watson are small and therefore the health impact upon the environment and humans due to this element is limited.

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A multisegment percolation system (MSPS) consisting of 25 individual collection wells was constructed to study the effects of localised soil heterogeneities on the transport of solutes in the vadose zone. In particular, this paper discusses the transport of water and nutrients (NO3-, Cl-, PO43-) through structurally stable, free-draining agricultural soil from Victoria, Australia. A solution of nutrients was irrigated onto the surface of a large undisturbed soil core over a 12-h period. This was followed by a continuous irrigation of distilled water at a fate which did not cause pending for a further 18 days. During this time, the volume of leachate and the concentration of nutrients in the leachate of each well were measured. Very significant variation in drainage patterns across a small spatial scale was observed. Leaching of nitrate-nitrogen and chloride from the core occurred two days after initial application. However, less than 1% of the total applied phosphate-phosphorus leached from the soil during the 18-day experiment, indicating strong adsorption. Our experiments indicate considerable heterogeneity in water flow patterns and solute leaching on a small spatial scale. These results have significant ramifications for modelling solute transport and predicting nutrient loadings on a larger scale.

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Community awareness of the sustainable use of land, water and vegetation resources is increasing. The sustainable use of these resources is pivotal to sustainable farming systems. However, techniques for monitoring the sustainable management of these resources are poorly understood and untested. We propose a framework to benchmark and monitor resources in the grains industry. Eight steps are listed below to achieve these objectives: (i) define industry issues; (ii) identify the issues through growers, stakeholder and community consultation; (iii) identify indicators (measurable attributes, properties or characteristics) of sustainability through consultation with growers, stakeholders, experts and community members, relating to: crop productivity; resource maintenance/enhancement; biodiversity; economic viability; community viability; and institutional structure; (iv) develop and use selection criteria to select indicators that consider: responsiveness to change; ease of capture; community acceptance and involvement; interpretation; measurement error; stability, frequency and cost of measurement; spatial scale issues; and mapping capability in space and through time. The appropriateness of indicators can be evaluated using a decision making system such as a multiobjective decision support system (MO-DSS, a method to assist in decision making from multiple and conflicting objectives); (v) involve stakeholders and the community in the definition of goals and setting benchmarking and monitoring targets for sustainable farming; (vi) take preventive and corrective/remedial action; (vii) evaluate effectiveness of actions taken; and (viii) revise indicators as part of a continual improvement principle designed to achieve best management practice for sustainable farming systems. The major recommendations are to: (i) implement the framework for resources (land, water and vegetation, economic, community and institution) benchmarking and monitoring, and integrate this process with current activities so that awareness, implementation and evolution of sustainable resource management practices become normal practice in the grains industry; (ii) empower the grains industry to take the lead by using relevant sustainability indicators to benchmark and monitor resources; (iii) adopt a collaborative approach by involving various industry, community, catchment management and government agency groups to minimise implementation time. Monitoring programs such as Waterwatch, Soilcheck, Grasscheck and Topcrop should be utilised; (iv) encourage the adoption of a decision making system by growers and industry representatives as a participatory decision and evaluation process. Widespread use of sustainability indicators would assist in validating and refining these indicators and evaluating sustainable farming systems. The indicators could also assist in evaluating best management practices for the grains industry.

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Under certain soil conditions, e.g. hardsetting clay B-horizons of South-Eastern Australia, wheat plants do not perform as well as would be expected given measurements of bulk soil attributes. In such soils, measurement indicates that a large proportion (80%) of roots are preferentially located in the soil within 1 mm of macropores. This paper addresses the question of whether there are biological and soil chemical effects concomitant with this observed spatial relationship. The properties of soil manually dissected from the 1-3 mm wide region surrounding macropores, the macropore sheath, were compared to those that are measured in a conventional manner on the bulk soil. Field specimens of two different soil materials were dissected to examine biological differentiation. To ascertain whether the macropore sheath soil differs from rhizosphere soil, wheat was grown in structured and repacked cores under laboratory conditions. The macropore sheath soil contained more microbial biomass per unit mass than both the bulk soil and the rhizosphere. The bacterial population in the macropore sheath was able to utilise a wider range of carbon substrates and to a greater extent than the bacterial population in the corresponding bulk soil. These differences between the macropore sheath and bulk soil were almost non-existent in the repacked cores. Evidence for larger numbers of propagules of the broad host range fungus Pythium in the macropore sheath soil were also obtained.

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Plants require roots to supply water, nutrients and oxygen for growth. The spatial distribution of roots in relation to the macropore structure of the soil in which they are growing influences how effective they are at accessing these resources. A method for quantifying root-macropore associations from horizontal soil sections is illustrated using two black vertisols from the Darling Downs, Queensland, Australia. Two-dimensional digital images were obtained of the macropore structure and root distribution for an area 55 x 55 mm at a resolution of 64 mu m. The spatial distribution of roots was quantified over a range of distances using the K-function. In all specimens, roots were shown to be clustered at short distances (1-10 mm) becoming more random at longer distances. Root location in relation to macropores was estimated using the function describing the distance of each root to the nearest macropore. From this function, a summary variable, termed the macropore sheath, was defined. The macropore sheath is the distance from macropores within which 80% of roots are located. Measured root locations were compared to random simulations of root distribution to establish if there was a preferential association between roots and macropores. More roots were found in and around macropores than expected at random.

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Plant performance is, at least partly, linked to the location of roots with respect to soil structure features and the micro-environment surrounding roots. Measurements of root distributions from intact samples, using optical microscopy and field tracings have been partially successful but are imprecise and labour-intensive. Theoretically, X-ray computed micro-tomography represents an ideal solution for non-invasive imaging of plant roots and soil structure. However, before it becomes fast enough and affordable or easily accessible, there is still a need for a diagnostic tool to investigate root/soil interplay. Here, a method for detection of undisturbed plant roots and their immediate physical environment is presented. X-ray absorption and phase contrast imaging are combined to produce projection images of soil sections from which root distributions and soil structure can be analyzed. The clarity of roots on the X-ray film is sufficient to allow manual tracing on an acetate sheet fixed over the film. In its current version, the method suffers limitations mainly related to (i) the degree of subjectivity associated with manual tracing and (ii) the difficulty of separating live and dead roots. The method represents a simple and relatively inexpensive way to detect and quantify roots from intact samples and has scope for further improvements. In this paper, the main steps of the method, sampling, image acquisition and image processing are documented. The potential use of the method in an agronomic perspective is illustrated using surface and sub-surface soil samples from a controlled wheat trial. Quantitative characterization of root attributes, e.g. radius, length density, branching intensity and the complex interplay between roots and soil structure, is presented and discussed.

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The measurement of organic carbon in soils has traditionally used dichromate oxidation procedures including the Wakley and Black and the Heanes methods. The measurement of carbon in soils by high temperature combustion is now widely used providing a rapid automated procedure without the use of toxic chemicals. This procedure however measures total carbon thus requiring some means of correction for soil samples containing carbonate and charcoal forms of carbon. This paper examines the effects of known additions of charcoal to a range of soil types on the results obtained by the Walkley and Black, Heanes and combustion methods. The results show, that while the charcoal carbon does not react under Walkley and Black conditions, some proportion does so with the Heanes method. A comparison of six Australian Soil and Plant Analysis Council reference soil samples by the three methods showed good agreement between the Heanes method, the combustion method and only slightly lower recoveries by the Walkley and Black procedure. Carbonate carbon will cause an overestimation of soil organic carbon by the combustion method thus requiring a separate determination of carbonate carbon to be applied as a correction. This work shows that a suitable acid pre-treatment of alkaline soils in the sample boats followed by a drying step eliminates the carbonate carbon prior to combustion and the need for an additional measurement. The measurement of carbon in soils by high temperature combustion in an oxygen atmosphere has been shown to be a rapid and reliable method capable of producing results in good agreement with one of the established dichromate oxidation procedures.

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Phenylalanine hydroxylase (PAH) is the enzyme that converts phenylalanine to tyrosine as a rate-limiting step in phenylalanine catabolism and protein and neurotransmitter biosynthesis. Over 300 mutations have been identified in the gene encoding PAH that result in a deficient enzyme activity and lead to the disorders hyperphenylalaninaemia and phenylketonuria. The determination of the crystal structure of PAH now allows the determination of the structural basis of mutations resulting in PAH deficiency. We present an analysis of the structural basis of 120 mutations with a 'classified' biochemical phenotype and/or available in vitro expression data. We find that the mutations can be grouped into five structural categories, based on the distinct expected structural and functional effects of the mutations in each category. Missense mutations and small amino acid deletions are found in three categories:'active site mutations', 'dimer interface mutations', and 'domain structure mutations'. Nonsense mutations and splicing mutations form the category of 'proteins with truncations and large deletions'. The final category, 'fusion proteins', is caused by frameshift mutations. We show that the structural information helps formulate some rules that will help predict the likely effects of unclassified and newly discovered mutations: proteins with truncations and large deletions, fusion proteins and active site mutations generally cause severe phenotypes; domain structure mutations and dimer interface mutations spread over a range of phenotypes, but domain structure mutations in the catalytic domain are more likely to be severe than domain structure mutations in the regulatory domain or dimer interface mutations.