974 resultados para Crop Forecasting System
Resumo:
A model has been developed which enables the viscosities of coal ash slags to be predicted as a function of composition and temperature under reducing conditions. The model describes both completely liquid and heterogeneous, i.e. partly crystallised, slags in the Al2O3-CaO-'FeO'-SiO2 system in equilibrium with metallic iron. The Urbain formalism has been modified to describe the viscosities of the liquid slag phase over the complete range of compositions and a wide range of temperatures. The computer package F * A * C * T was used to predict the proportions of solids and the compositions of the remaining liquid phases. The Roscoe equation has been used to describe the effect of presence of solid suspension (slurry effect) on the viscosity of partly crystallised slag systems. The model provides a good description of the experimental data of fully liquid, and liquid + solids mixtures, over the complete range of compositions and a wide range of temperatures. This model can now be used for viscosity predictions in industrial slag systems. Examples of the application of the new model to coal ash fluxing and blending are given in the paper. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
Experimental and thermodynamic modeling studies have been carried out on the Zn-Fe-Si-O system. This research is part of a wider program to characterize zinc/lead industrial slags and sinters in the PbO-ZnO-SiO2-CaO-FeO-Fe2O3 system. Experimental investigations involve high-temperature equilibration and quenching techniques followed by electron probe X-ray microanalysis (EPMA). Liquidus temperatures and solid solubilities of the crystalline phases were measured in the temperature range from 1200 °C to 1450 °C (1473 to 1723 K) in the zinc ferrite, zincite, willemite, and tridymite primary-phase fields in the Zn-Fe-Si-O system in air. These equilibrium data for the Zn-Fe-Si-O system in air, combined with previously reported data for this system, were used to obtain an optimized self-consistent set of parameters of thermodynamic models for all phases.
Resumo:
A field experiment compared two rice (Oryza sativa L.) cropping systems: paddy or raised beds with continuous furrow irrigation; and trialled four cultivars: Starbonnet, Lemont, Amaroo and Ceysvoni, and one test line YRL39; that may vary in adaptation to growth on raised beds. The grain yield of rice ranged from 740 to 1250 g/m(2) and was slightly greater in paddy than on raised beds. Although there were early growth responses to fertilizer nitrogen on raised beds, the crop nitrogen content at maturity mostly exceeded 20 g/m(2) in both systems, so nitrogen was unlikely to have limited yield. Ceysvoni yielded best in both systems, a result of good post-anthesis growth and larger grain size, although its whole-grain mill-out percentage was poor relative to the other cultivars. Starbonnet and Lemont yielded poorly on raised beds, associated with too few tillers and too much leaf area. When grown on raised beds all cultivars experienced a delay in anthesis resulting in more tillers, leaf area and dry weight at anthesis, and probably a greater yield potential. The growth of rice after anthesis, however, was similar on raised beds and in paddy, so reductions in harvest index and grain size on raised beds were recorded. The data indicated that water supply was not a major limitation to rice growth on raised beds, but slower crop development was an issue that would affect the use of raised beds in a cropping system, especially in rice-growing areas where temperatures are too cool for optimal crop development. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
Current serotyping methods classify Pasteurella multocida into five capsular serogroups (serogroups A, B, D, E, and F) and 16 somatic serotypes (serotypes 1 to 16). In the present study, we have developed a multiplex PCR assay as a rapid alternative to the conventional capsular serotyping system. The serogroup-specific primers used in this assay were designed following identification, sequence determination, and analysis of the capsular biosynthetic loci of each capsular serogroup. The entire capsular biosynthetic loci of P. multocida A:1 (X-73) and B:2 (M1404) have been cloned and sequenced previously (J. Y. Chung, Y. M. Zhang, and B. Adler, FEMS Microbiol. Lett. 166:289-296, 1998; J. D. Boyce, J. Y. Chung, and B. Adler, Vet. Microbiol. 72:121-134, 2000). Nucleotide sequence analysis of the biosynthetic region (region 2) from each of the remaining three serogroups, serogroups D, E, and F, identified serogroup-specific regions and gave an indication of the capsular polysaccharide composition. The multiplex capsular PCR assay was highly specific, and its results, with the exception of those for some serogroup F strains, correlated well with conventional serotyping results. Sequence analysis of the strains that gave conflicting results confirmed the validity of the multiplex PCR and indicated that these strains were in fact capsular serogroup A. The multiplex PCR will clarify the distinction between closely related serogroups A and F and constitutes a rapid assay for the definitive classification of P. multocida capsular types
Resumo:
Brushtail possums, Trichosurus vulpecula Kerr, were experimentally infected with Ross River (RR) or Barmah Forest (BF) virus by Aedes vigilax (Skuse) mosquitoes. Eight of 10 animals exposed to RR virus developed neutralizing antibody, and 3 possums developed high viremia for < 48 hr after infection, sufficient to infect recipient mosquitoes. Two of 10 animals exposed to BF virus developed neutralizing antibody. Both infected possums maintained detectable neutralizing antibody to BF for at least 45 days after infection (log neutralization index > 2.0 at 45 days). Eight possums did not develop neutralizing antibody to BF despite exposure to infected mosquitoes. These results suggest that T. vulpecula may potentially act as a reservoir species for RR in urban areas. However, T. vulpecula infected with BF do not develop viremia sufficient to infect mosquitoes and are unlikely to be important hosts for BF.
Resumo:
Traffic and tillage effects on runoff and crop performance on a heavy clay soil were investigated over a period of 4 years. Tillage treatments and the cropping program were representative of broadacre grain production practice in northern Australia, and a split-plot design used to isolate traffic effects. Treatments subject to zero, minimum, and stubble mulch tillage each comprised pairs of 90-m 2 plots, from which runoff was recorded. A 3-m-wide controlled traffic system allowed one of each pair to be maintained as a non-wheeled plot, while the total surface area of the other received a single annual wheeling treatment from a working 100-kW tractor. Rainfall/runoff hydrographs demonstrate that wheeling produced a large and consistent increase in runoff, whereas tillage produced a smaller increase. Treatment effects were greater on dry soil, but were still maintained in large and intense rainfall events on wet soil. Mean annual runoff from wheeled plots was 63 mm (44%) greater than that from controlled traffic plots, whereas runoff from stubble mulch tillage plots was 38 mm (24%) greater than that from zero tillage plots. Traffic and tillage effects appeared to be cumulative, so the mean annual runoff from wheeled stubble mulch tilled plots, representing conventional cropping practice, was more than 100 mm greater than that from controlled traffic zero tilled plots, representing best practice. This increased infiltration was reflected in an increased yield of 16% compared with wheeled stubble mulch. Minimum tilled plots demonstrated a characteristic midway between that of zero and stubble mulch tillage. The results confirm that unnecessary energy dissipation in the soil during the traction process that normally accompanies tillage has a major negative effect on infiltration and crop productivity. Controlled traffic farming systems appear to be the only practicable solution to this problem.
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FILTER is an innovative, CSIRO developed system for treating effluent using high rate land application and subsequent effluent recapture via a closely spaced, subsurface drainage network. We report on the summer performance of a FILTER system established in a subtropical environment on a relatively impermeable swelling clay soil underlain by a deep regional water table. Using secondary treated sewage effluent, the FILTER system produced effluent of tertiary nutrient standards (less than or equal to5 mg/L TN; less than or equal to1 mg/L TP), with salinity levels suitable for subsequent irrigation reuse (EC less than or equal to2.5 dS/m). Removal of faecal coliforms was considerably less effective. The hydraulic loading rate achieved was about two and a half times larger than conventional irrigation demand, but this was associated with high deep percolation losses (e 3 mm/day). Comparisons are made with the original FILTER system developed and tested by Jayawardane et al. in temperate Australia. Suggestions are made for modifications to, and further testing of FILTER in a subtropical environment.
Resumo:
Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
Observations of accelerating seismic activity prior to large earthquakes in natural fault systems have raised hopes for intermediate-term eartquake forecasting. If this phenomena does exist, then what causes it to occur? Recent theoretical work suggests that the accelerating seismic release sequence is a symptom of increasing long-wavelength stress correlation in the fault region. A more traditional explanation, based on Reid's elastic rebound theory, argues that an accelerating sequence of seismic energy release could be a consequence of increasing stress in a fault system whose stress moment release is dominated by large events. Both of these theories are examined using two discrete models of seismicity: a Burridge-Knopoff block-slider model and an elastic continuum based model. Both models display an accelerating release of seismic energy prior to large simulated earthquakes. In both models there is a correlation between the rate of seismic energy release with the total root-mean-squared stress and the level of long-wavelength stress correlation. Furthermore, both models exhibit a systematic increase in the number of large events at high stress and high long-wavelength stress correlation levels. These results suggest that either explanation is plausible for the accelerating moment release in the models examined. A statistical model based on the Burridge-Knopoff block-slider is constructed which indicates that stress alone is sufficient to produce accelerating release of seismic energy with time prior to a large earthquake.