4 resultados para Ernst, Duke of Sachsen-Altenburg, 1826-1908.

em eResearch Archive - Queensland Department of Agriculture


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Fusarium wilt of cotton, caused by the fungus Fusarium oxysporum Schlechtend. f. sp. vasinfectum (Atk.) Snyd. & Hans, was first identified in 1892 in cotton growing in sandy acid soils in Alabama (8). Although the disease was soon discovered in other major cotton-producing areas, it did not become global until the end of the next century. After its original discovery, Fusarium wilt of cotton was reported in Egypt (1902) (30), India (1908) (60), Tanzania (1954) (110), California (1959) (33), Sudan (1960) (44), Israel (1970) (27), Brazil (1978) (5), China (1981) (17), and Australia (1993) (56). In addition to a worldwide distribution, Fusarium wilt occurs in all four of the domesticated cottons, Gossypium arboretum L., G. barbadense L., G. herbaceum L., and G. hirsutum L. (4,30). Disease losses in cotton are highly variable within a country or region. In severely infested fields planted with susceptible cultivars, yield losses can be high. In California, complete crop losses in individual fields have been observed (R. M. Davis, unpublished). Disease loss estimates prepared by the National Cotton Disease Council indicate losses of over 109,000 bales (227 kg or 500 lb) in the United States in 2004 (12).

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These rootstock and nitrogen fertiliser studies confirmed that rootstock race can significantly affect the development of postharvest disease and mineral nutrient accumulation in Hass avocado fruit. When Hass (Guatemalan race) was grafted to seedling Velvick (West Indian race) rootstock, the severity and incidence of anthracnose in fruit were significantly reduced by up to 64 and 37%, respectively, compared with seedling Duke 6 (Mexican race) rootstock. Stem-end rot was also influenced by rootstock in some seasons, and significant reductions (up to 87%) in the severity and incidence of stem-end rot were recorded in Hass fruit from Velvick compared with Duke 6 rootstock trees. These improvements in postharvest diseases were associated with significantly lower concentrations of nitrogen and potassium, higher concentrations of calcium and magnesium, lower ratios of nitrogen:calcium and higher ratios of calcium + magnesium:potassium in Hass leaves and fruit from Velvick compared with Duke 6 rootstock trees. Altering the rate of nitrogen fertiliser had minimal impact on postharvest disease development. However, in one season, reducing the rate of nitrogen fertiliser to nil significantly reduced the concentration of nitrogen in the fruit skin, decreased the nitrogen:calcium ratio and significantly reduced the severity and incidence of anthracnose in Hass fruit from both Velvick and Duke 6 rootstock trees. The form of nitrogen fertiliser (ammonium compared with nitrate) applied to the trees did not significantly affect the postharvest disease susceptibility of Hass avocado fruit on either Velvick or Duke 6 rootstock. The Guatemalan race rootstocks, Anderson 8 and Anderson 10, were also found to be superior to the Mexican race rootstock, Parida 1, for reducing anthracnose severity. This again, was associated with a better balance of mineral nutrients (significantly lower nitrogen:calcium and higher calcium + magnesium:potassium ratios) in the fruit. This rootstock effect, however, was only observed in the first season of a 3-year experiment, possibly because of a better balance between vegetative growth and fruit production in Parida 1 in the latter two seasons. Significant positive correlations between anthracnose severity and fruit skin nitrogen:calcium ratios were evident across all experiments.

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Herbicide contamination from agriculture is a major issue worldwide, and has been identified as a threat to freshwater and marine environments in the Great Barrier Reef World Heritage Area in Australia. The triazine herbicides are of particular concern because of potential adverse effects, both on photosynthetic organisms and upon vertebrate development. To date a number of bioremediation strategies have been proposed for triazine herbicides, but are unlikely to be implemented due to their reliance upon the release of genetically modified organisms. We propose an alternative strategy using a free-enzyme bioremediant, which is unconstrained by the issues surrounding the use of live organisms. Here we report an initial field trial with an enzyme-based product, demonstrating that the technology is technically capable of remediating water bodies contaminated with the most common triazine herbicide, atrazine.

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Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.