10 resultados para Composting process

em eResearch Archive - Queensland Department of Agriculture


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The intent of this study was to design, document and implement a Quality Management System (QMS) into a laboratory that incorporated both research and development (R&D) and routine analytical activities. In addition, it was necessary for the QMS to be easily and efficiently maintained to: (a) provide documented evidence that would validate the system's compliance with a certifiable standard, (b) fit the purpose of the laboratory, (c) accommodate prevailing government policies and standards, and (d) promote positive outcomes for the laboratory through documentation and verification of the procedures and methodologies implemented. Initially, a matrix was developed that documented the standards' requirements and the necessary steps to be made to meet those requirements. The matrix provided a check mechanism on the progression of the system's development. In addition, it was later utilised in the Quality Manual as a reference tool for the location of full procedures documented elsewhere in the system. The necessary documentation to build and monitor the system consisted of a series of manuals along with forms that provided auditable evidence of the workings of the QMS. Quality Management (QM), in one form or another, has been in existence since the early 1900's. However, the question still remains: is it a good thing or just a bugbear? Many of the older style systems failed because they were designed by non-users, fiercely regulatory, restrictive and generally deemed to be an imposition. It is now considered important to foster a sense of ownership of the system by the people who use the system. The system's design must be tailored to best fit the purpose of the operations of the facility if maximum benefits to the organisation are to be gained.

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There are renewed calls for end-user participation and the integration of local knowledge in agricultural research. In Australia, the response has included an increased emphasis on participatory on-farm research with farmers and commercial agronomists that tests accepted principals to answer practical local farming questions. However, this pursuit of greater relevance has often led to compromises in research designs, unclear results and frustration amongst farmers, commercial agronomists and Research Development and Extension (RDE) agency researchers. This paper reports on a series of pre-season planning workshops from `Doing successful on-farm research', a workshop-based initiative that provides guidelines and a series of interactive activities to plan better participatory on-farm research. The workshop approach helps people design on-farm research that is appropriate to their own needs and local conditions. It assists them to clearly identify their issues, develop specific research questions and decide the best approach to answer those questions with the appropriate rigour for their own situations. These `Doing successful on-farm research' workshops address four potential deficiencies in on-farm research and farming systems RDE more generally in Australia: (1) variable participation of scientists and farmers in on-farm research; (2) the lack of clear guidelines for effective participatory practice and on-farm research; (3) limited support for on-farm research beyond the intensive investigations conducted by RDE agencies and (4) limited support for industry and farmers to contextualise information and research outcomes for specific individual circumstances and faster adaptation of technology. This may be a valuable contribution to balancing the demands for both relevance and rigour in on-farm research in Australia. In "Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

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Replicable experimental studies using a novel experimental facility and a machine-based odour quantification technique were conducted to demonstrate the relationship between odour emission rates and pond loading rates. The odour quantification technique consisted of an electronic nose, AromaScan A32S, and an artificial neural network. Odour concentrations determined by olfactometry were used along with the AromaScan responses to train the artificial neural network. The trained network was able to predict the odour emission rates for the test data with a correlation coefficient of 0.98. Time averaged odour emission rates predicted by the machine-based odour quantification technique, were strongly correlated with volatile solids loading rate, demonstrating the increased magnitude of emissions from a heavily loaded effluent pond. However, it was not possible to obtain the same relationship between volatile solids loading rates and odour emission rates from the individual data. It is concluded that taking a limited number of odour samples over a short period is unlikely to provide a representative rate of odour emissions from an effluent pond. A continuous odour monitoring instrument will be required for that more demanding task.

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The value of CLIMEX models to inform biocontrol programs was assessed, including predicting the potential distribution of biocontrol agents and their subsequent population dynamics, using bioclimatic models for the weed Parkinsonia aculeata, two Lantana camara biocontrol agents, and five Mimosa pigra biocontrol agents. The results showed the contribution of data types to CLIMEX models and the capacity of these models to inform and improve the selection, release and post release evaluation of biocontrol agents. Foremost among these was the quality of spatial and temporal information as well as the extent to which overseas range data samples the species’ climatic envelope. Post hoc evaluation and refinement of these models requires improved long-term monitoring of introduced agents and their dynamics at well selected study sites. The authors described the findings of these case studies, highlighted their implications, and considered how to incorporate models effectively into biocontrol programs.

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Understanding plant demography and plant response to herbivory is critical to the selection of effective weed biological control agents. We adopt the metaphor of 'filters' to suggest how agent prioritisation may be improved to narrow our choices down to those likely to be most effective in achieving the desired weed management outcome. Models can serve to capture our level of knowledge (or ignorance) about our study system and we illustrate how one type of modelling approach (matrix models) may be useful in identifying the weak link in a plant life cycle by using a hypothetical and an actual weed example (Parkinsonia aculeata). Once the vulnerable stage has been identified we propose that studying plant response to herbivory (simulated and/or actual) can help identify the guilds of herbivores to which a plant is most likely to succumb. Taking only potentially effective agents through the filter of host specificity may improve the chances of releasing safe and effective agents. The methods we outline may not always lead us definitively to the successful agent(s), but such an empirical, data-driven approach will make the basis for agent selection explicit and serve as testable hypotheses once agents are released.

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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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Membrane filtration technology has been proven to be a technically sound process to improve the quality of clarified cane juice and subsequently to increase the productivity of crystallisation and the quality of sugar production. However, commercial applications have been hindered because the benefits to crystallisation and sugar quality have not outweighed the increased processing costs associated with membrane applications. An 'Integrated Sugar Production Process (ISPP) Concept Model' is proposed to recover more value from the non-sucrose streams generated by membrane processing. Pilot scale membrane fractionation trials confirmed the technical feasibility of separating high-molecular weight, antioxidant and reducing sugar fractions from cane juice in forms suitable for value recovery. It was also found that up to 40% of potassium salts from the juice can be removed by membrane application while removing the similar amount of water with potential energy saving in subsequent evaporation. Application of ISPP would allow sugar industry to co-produce multiple products and high quality mill sugar while eliminating energy intensive refining processes.

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The eucalypt leaf beetle, Paropsis atomaria Olivier, is an increasingly important pest of eucalypt plantations in subtropical eastern Australia. A process-based model, ParopSys, was developed using DYMEXTM and was found to accurately predict the beetle populations. Climate change scenarios within the latest Australian climate model forecast range were run in ParopSys at three locations to predict changes in beetle performance. Relative population peaks of early generations did not change but shifted to earlier in the season. Temperature increases of 1.0 to 1.5 ºC or greater predicted an extra generation of adults at Gympie and Canberra, but not for Lowmead, where increased populations of late season adults were observed under all scenarios. Furthermore, an additional generation of late-larval stages was predicted at temperature increases of greater than 1.0 ºC at Lowmead. Management strategies to address these changes are discussed, as are requirements to improve the predictive capacity of the model.

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Near infrared spectroscopy (NIRS) can play a vital role as a cost effective, rapid, non-invasive, reproducible diagnostic tool for many environmental management, agricultural and industrial waste water monitoring applications. In this paper we highlight the ability of NIRS technology to be used as a diagnostic tool in agricultural and environmental applications through the successful assessment of Fourier Transform NIRS to predict α santalol in sandalwood chip samples, and maturity of ‘Hass’ avocado fruit based on dry matter content. Presented at the Third International Conference on Challenges in Environmental Science & Engineering, CESE-2010. 26 September – 1 October 2010, The Sebel, Cairns, Queensland, Australia.

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In western Queensland, severe drought conditions began in late 2001 and did not generally ease until the 2008/09 summer. Despite the ability of Mitchell grass plants to become dormant during drought, a large proportion of plants appeared to be dead rather than drought-dormant by the end of the 2002/03 summer. Tillers and remaining leaves were blackened and unpalatable to livestock. The term Mitchell grass dieback was coined by producers and other observers to describe what had occurred, although most were confident that the grass would recover with the breaking of the drought. Mitchell grass plants generally failed to respond to widespread average summer rains in early 2004 (> 250 mm). Observation suggested that moisture had penetrated to a soil depth of about 60 cm and a response from plants was expected. When there was no general response, research into the reasons for this was initiated (NBP.348 'Mitchell grass death in Queensland: extent, economic impact and potential for recovery'; 2005-07). This included an investigation of discrete areas of pasture that had responded to the 2003-04 summer rain. Further declines in condition of Mitchell grasslands occurred between winter 2005 and winter 2006 and, by 2006, field surveys indicated that 53% of this pasture community was in poor (C) condition, primarily due to dieback. Measurements at some sites suggested practices such as wet season spelling and burning can pre-condition Mitchell grass pasture for greater resistance to drought-induced dieback. However, the casual mechanisms and the effective timing and frequency of these practices remained unclear.