7 resultados para contextual knowledge

em eResearch Archive - Queensland Department of Agriculture


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This paper describes a new knowledge acquisition method using a generic design environment where context-sensitive knowledge is used to build specific DSS for rural business. Although standard knowledge acquisition methods have been applied in rural business applications, uptake remains low and familiar weaknesses such as obsolescence and brittleness apply. We describe a decision support system (DSS) building environment where contextual factors relevant to the end users are directly taken into consideration. This "end user enabled design environment" (EUEDE) engages both domain experts in creating an expert knowledge base and business operators/end users (such as farmers) in using this knowledge for building their specific DSS. We document the knowledge organisation for the problem domain, namely a dairy industry application. This development involved a case-study research approach used to explore dairy operational knowledge. In this system end users can tailor their decision-making requirements using their own judgement to build specific DSSs. In a specific end user's farming context, each specific DSS provides expert suggestions to assist farmers in improving their farming practice. The paper also shows the environment's generic capability.

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Mangoes consigned to domestic markets suffered from fruit quality problems from 1997 to 2000. A high incidence of disease breakdown and green-ripe fruit resulted in loss of confidence by marketers, and reduced profits for everyone from grower to retailer. The ‘Better Mangoes’ project was initiated to identify where, and why quality was being lost, and to use this information to improve the knowledge and practices of supply chain businesses.

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A successful supply chain must delivery the right product, value and satisfaction to the end customer, and profitability for its participants. Critical to getting the product right is the practices used to produce and maintain product quality through the supply chain from production to sale to the end customer. This paper describes the approach used by a R&D team to add value to supply chains through improving knowledge and practices. The desired outcome is better produce quality for consumers and more control and less wastage for chain participants. The team worked with specific supply chains to identify areas for improvement and to develop, test and implement improved practices. The knowledge gained was communicated to the industry to gain wider adoption of results. Three conditions were identified as critical for practice change - motivation, knowledge, and capacity for change. For improvement in practices to occur, a business must be motivated and have the knowledge and capacity to improve. Two case studies of working with Australian supply chains (mango and melons) are presented to illustrate our participatory methodology. A key activity is monitoring produce quality and handling practices and conditions to demonstrate to participants the points where quality deterioration occurs in the supply chain. This participatory approach is successful because working with supply chain participants generates knowledge and solutions to real problems. It enables the participants to observe the effect of handling practices and conditions on produce quality, gain knowledge and assess the benefits of improvements. Where existing knowledge is not present, research is conducted to fill the knowledge gaps. IV International Conference on Managing Quality in Chains - The Integrated View on Fruits and Vegetables Quality

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Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

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The traditional reductionist approach to science has a tendency to create 'islands of knowledge in a sea of ignorance', with a much stronger focus on analysis of scientific inputs rather than synthesis of socially relevant outcomes. This might be the principal reason why intended end users of climate information generally fail to embrace what the climate science community has to offer. The translation of climate information into real-life action requires 3 essential components: salience (the perceived relevance of the information), credibility (the perceived technical quality of the information) and legitimacy (the perceived objectivity of the process by which the information is shared). We explore each of these components using 3 case studies focused on dryland cropping in Australia, India and Brazil. In regards to 'salience' we discuss the challenge for climate science to be 'policy-relevant', using Australian drought policy as an example. In a village in southern India 'credibility' was gained through engagement between scientists and risk managers with the aim of building social capital, achieved only at high cost to science institutions. Finally, in Brazil we found that 'legitimacy' is a fragile, yet renewable resource that needs to be part of the package for successful climate applications; legitimacy can be easily eroded but is difficult to recover. We conclude that climate risk management requires holistic solutions derived from cross-disciplinary and participatory, user-oriented research. Approaches that combine climate, agroecological and socioeconomic models provide the scientific capabilities for establishment of 'borderless' institutions without disciplinary constraints. Such institutions could provide the necessary support and flexibility to deliver the social benefits of climate science across diverse contexts. Our case studies show that this type of solution is already being applied, and suggest that the climate science community attempt to address existing institutional constraints, which still impede climate risk management.

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This review of grader grass (Themeda quadrivalvis) attempts to collate current knowledge and identify knowledge gaps that may require further research. Grader grass is a tropical annual grass native to India that is now spread throughout many of the tropical regions of the world. In Australia, it has spread rapidly since its introduction in the 1930s and is now naturalised in the tropical areas of Queensland, the Northern Territory and Western Australia and extends south along the east coast to northern New South Wales. It is a vigorous grass with limited palatability, that is capable of invading native and improved pastures, cropping land and protected areas such as state and national parks. Grader grass can form dense monocultures that reduce biodiversity, decrease animal productivity and increase the fire hazard in the seasonally dry tropics. Control options are based on herbicides, grazing management and slashing, while overgrazing appears to favour grader grass. The effect of fire on grader grass is inconclusive and needs to be defined. Little is known about the biology and impacts of grader grass in agricultural and protected ecosystems in Australia. In particular, information is needed on soil seed bank longevity, seed production, germination and growth, which would allow the development of management strategies to control this weedy grass.