3 resultados para logistic regression analysis

em eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry


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A disease outbreak investigation was conducted in western Queensland to investigate a rare suspected outbreak of pyrrolizidine alkaloid (PA) toxicosis in horses. Thirty five of 132 horses depastured on five properties on the Mitchell grass plains of western Queensland died in the first six months of 2010. Clinical–pathological findings were consistent with PA toxicosis. A local variety of Crotalaria medicaginea was the only hepatotoxic plant found growing on affected properties. Pathology reports and departure and arrival dates of two brood mares provided evidence of a pre wet season exposure period. All five affected properties experienced a very dry spring and early summer preceded by a large summer wet season. The outbreak was characterised as a point epidemic with a sudden peak of deaths in March followed by mortalities steadily declining until the end of June. The estimated morbidity (serum IGG > 50 IU/L) rate was 76%. Average crude mortality was 27% but higher in young horses (67%) and brood mares (44%). Logistic regression analysis showed that young horses and brood mares and those grazing denuded pastures in December were most strongly associated with dying whereas those fed hay and/or grain based supplements were less likely to die. This is the first detailed study of an outbreak of PA toxicosis in central western Queensland and the first to provide evidence that environmental determinants were associated with mortality, that the critical exposure period was towards the end of the dry season, that supplementary feeding is protective and that denuded pastures and the horses physiological protein requirement are risk factors.

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The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July-August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July-August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July-August predictor) forecasts are more skillful using the SOI, long-lead (May-June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.

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Strong statistical evidence was found for differences in tolerance to natural infections of Tobacco streak virus (TSV) in sunflower hybrids. Data from 470 plots involving 23 different sunflower hybrids tested in multiple trials over 5 years in Australia were analysed. Using a Bayesian Hierarchical Logistic Regression model for analysis provided: (i) a rigorous method for investigating the relative effects of hybrid, seasonal rainfall and proximity to inoculum source on the incidence of severe TSV disease; (ii) a natural method for estimating the probability distributions of disease incidence in different hybrids under historical rainfall conditions; and (iii) a method for undertaking all pairwise comparisons of disease incidence between hybrids whilst controlling the familywise error rate without any drastic reduction in statistical power. The tolerance identified in field trials was effective against the main TSV strain associated with disease outbreaks, TSV-parthenium. Glasshouse tests indicate this tolerance to also be effective against the other TSV strain found in central Queensland, TSV-crownbeard. The use of tolerant germplasm is critical to minimise the risk of TSV epidemics in sunflower in this region. We found strong statistical evidence that rainfall during the early growing months of March and April had a negative effect on the incidence of severe infection with greatly reduced disease incidence in years that had high rainfall during this period.