5 resultados para Design science

em eResearch Archive - Queensland Department of Agriculture


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The article discusses a new decision support process for forestry pest management. Over the past few years, DSS have been introduced for forestry pest management, providing forest growers with advice in areas such as selecting the most suitable pesticide and relevant treatment. Most of the initiatives process knowledge from various domains for providing support for specific decision making problems. However, very few studies have identified the requirements of developing a combined process model in which all relevant practitioners can contribute and share knowledge for effective decision making; such an approach would need to include the decision makers’ perspective along with other relevant attributes such as the problem context and relevant policies. We outline a decision support process for forestry pest management, based on the design science research paradigm, in which a focus group technique has application to acquire both expert and practical knowledge in order to construct the DSS solution.

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Point sources of wastewater pollution, including effluent from municipal sewage treatment plants and intensive livestock and processing industries, can contribute significantly to the degradation of receiving waters (Chambers et al. 1997; Productivity Commission 2004). This has led to increasingly stringent local wastewater discharge quotas (particularly regarding Nitrogen, Phosphorous and suspended solids), and many municipal authorities and industry managers are now faced with upgrading their existing treatment facilities in order to comply. However, with high construction, energy and maintenance expenses and increasing labour costs, traditional wastewater treatment systems are becoming an escalating financial burden for the communities and industries that operate them. This report was generated, in the first instance, for the Burdekin Shire Council to provide information on design aspects and parameters critical for developing duckweed-based wastewater treatment (DWT) in the Burdekin region. However, the information will be relevant to a range of wastewater sources throughout Queensland. This information has been collated from published literature and both overseas and local studies of pilot and full-scale DWT systems. This report also considers options to generate revenue from duckweed production (a significant feature of DWT), and provides specifications and component cost information (current at the time of publication) for a large-scale demonstration of an integrated DWT and fish production system.

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Research into the genetics of whole herd profitability has been a focus of the Beef Cooperative Research Centre for Beef Genetic Technologies over the past decade and it has been identified that measures of male reproduction may offer a potential indirect means of selecting for improved female reproduction. This paper describes the experimental design and provides a descriptive analysis of an array of male traits in Brahman and Tropical Composite genotypes managed under the medium to high stress, semi-extensive to extensive production systems of northern Australia. A total of 1639 Brahman and 2424 Tropical Composite bulls with known pedigrees, bred and raised in northern Australia, were evaluated for a comprehensive range of productive and reproductive traits. These included blood hormonal traits (luteinising hormone, inhibin and insulin-like growth factor-I); growth and carcass traits (liveweight, body condition score, ultrasound scanned 12-13th rib fat, rump P8 fat, eye muscle area and hip height); adaptation traits (flight time and rectal temperature); and a bull breeding soundness evaluation (leg and hoof conformation, sheath score, length of everted prepuce, penile anatomy, scrotal circumference, semen mass activity, sperm motility and sperm morphology). Large phenotypic variation was evident for most traits, with complete overlap between genotypes, indicating that there is likely to be a significant opportunity to improve bull fertility traits through management and bull selection.

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Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.