17 resultados para methodologies


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A major outcome of this project has been the identification and prioritisation of the major management issues related to the ecological impacts of fish stocking and the elucidation of appropriate research methodologies that can be used to investigate these issues. This information is paramount to development of the relevant research projects that will lead to stocking activities aligned with world’s best practice, a requisite for ecologically sustainable recreational freshwater fisheries. In order to quantify the major management issues allied to the sustainability of freshwater fish stocking, stakeholders from around Australia were identified and sent a questionnaire to determine which particular issues they regarded as important. These stakeholders included fisheries managers or researchers from Federal, Territory and State jurisdictions although others, including representatives from environment and conservation agencies and peak recreational fishing and stocking groups were also invited to give their opinions. The survey was completed in late 2007 and the results analysed to give a prioritized list of key management issues relating to the impacts of native fish stocking activities. In the analysis, issues which received high priority rankings were flagged as potential topics for discussion at a future expert workshop. Identified high priority issues fell into the following core areas: marking techniques, genetics, population dynamics, introduction of pathogens and exotic biological material and ecological, biological and conservation issues. The next planned outcome, determination of the most appropriate methodologies to address these core issues in research projects, was addressed through the outputs of an expert workshop held in early 2008. Participants at this workshop agreed on a range of methodologies for addressing priority sustainability issues and decided under what circumstances that these methodologies should be employed.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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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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Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

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Objective To improve the isolation rate and identification procedures for Haemophilus parasuis from pig tissues. Design Thirteen sampling sites and up to three methods were used to confirm the presence of H. parasuis in pigs after experimental challenge. Procedure Colostrum-deprived, naturally farrowed pigs were challenged intratracheally with H parasuis serovar 12 or 4. Samples taken during necropsy were either inoculated onto culture plates, processed directly for PCR or enriched prior to being processed for PCR. The recovery of H parasuis from different sampling sites and using different sampling methods was compared for each serovar. Results H parasuis was recovered from several sample sites for all serovar 12 challenged pigs, while the trachea was the only positive site for all pigs following serovar 4 challenge. The method of solid medium culture of swabs, and confirmation of the identity of cultured bacteria by PCR, resulted in 38% and 14% more positive results on a site basis for serovars 12 and 4, retrospectively, than direct PCR on the swabs. This difference was significant in the serovar 12 challenge. Conclusion Conventional culture proved to be more effective in detecting H parasuis than direct PCR or PCR on enrichment broths. For subacute (serovar 4) infections, the most successful sites for culture or direct PCR were pleural fluid, peritoneal fibrin and fluid, lung and pericardial fluid. For acute (serovar 12) infections, the best sites were lung, heart blood, affected joints and brain. The methodologies and key sampling sites identified in this study will enable improved isolation of H parasuis and aid the diagnosis of Glässer's disease.

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Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

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To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

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Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and. to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry.

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The north Queensland banana industry is under pressure from government and community expectations to exhibit good environmental stewardship. The industry is situated on the high-rainfall north Queensland coast adjacent to 2 natural icons, the Great Barrier Reef to the east and World Heritage-listed rain forest areas to the west. The main environmental concern is agricultural industry pollutants harming the Great Barrier Reef. In addition to environmental issues the banana industry also suffers financial pressure from declining margins and production loss from tropical cyclones. As part of a broader government strategy to reduce land-based pollutants affecting the Great Barrier Reef, the formation of a pilot banana producers group to address these environmental and economic pressures was facilitated. Using an integrated farming systems approach, we worked collaboratively with these producers to conduct an environmental risk assessment of their businesses and then to develop best management practices (BMP) to address environmental concerns. We also sought input from technical experts to provide increased rigour for the environmental risk assessment and BMP development. The producers' commercial experience ensured new ideas for improved sustainable practices were constantly assessed through their profit-driven 'filter' thus ensuring economic sustainability was also considered. Relying heavily on the producers' knowledge and experience meant the agreed sustainable practices were practical, relevant and financially feasible for the average-sized banana business in the region. Expert input and review also ensured that practices were technically sound. The pilot group producers then implemented and adapted selected key practices on their farms. High priority practices addressed by the producers group included optimizing nitrogen fertilizer management to reduce runoff water nitrification, developing practical ground cover management to reduce soil erosion and improving integrated pest management systems to reduce pesticide use. To facilitate wider banana industry understanding and adoption of the BMP's developed by the pilot group, we conducted field days at the farms of the pilot group members. Information generated by the pilot group has had wider application to Australian horticulture and the process has been subsequently used with the north Queensland sugar industry. Our experiences have shown that integrated farming systems methodologies are useful in addressing complex issues like environmental and economic sustainability. We have also found that individual horticulture businesses need on-going technical support for change to more sustainable practices. One-off interventions have little impact, as farm improvement is usually an on-going incremental process. A key lesson from this project has been the need to develop practical, farm scale economic tools to clarify and demonstrate the financial impact of alternative management practices. Demonstrating continued profitability is critical to encourage widespread industry adoption of environmentally sustainable practices

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For many fisheries, there is a need to develop appropriate indicators, methodologies, and rules for sustainably harvesting marine resources. Complexities of scientific and financial factors often prevent addressing these, but new methodologies offer significant improvements on current and historical approaches. The Australian spanner crab fishery is used to demonstrate this. Between 1999 and 2006, an empirical management procedure using linear regression of fishery catch rates was used to set the annual total allowable catch (quota). A 6-year increasing trend in catch rates revealed shortcomings in the methodology, with a 68% increase in quota calculated for the 2007 fishing year. This large quota increase was prevented by management decision rules. A revised empirical management procedure was developed subsequently, and it achieved a better balance between responsiveness and stability. Simulations identified precautionary harvest and catch rate baselines to set quotas that ensured sustainable crab biomass and favourable performance for management and industry. The management procedure was simple to follow, cost-effective, robust to strong trends and changes in catch rates, and adaptable for use in many fisheries. Application of such “tried-and-tested” empirical systems will allow improved management of both data-limited and data-rich fisheries.

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Phage therapy is becoming increasingly important as a means of eradicating or controlling microbial populations and has been raised as a potential strategy to reduce methane emissions from ruminants. To date, very little is currently known about phages which may infect the methane-producing archaeal strains (methanogens) dominant within the rumen of Australian cattle, such as the Methanobrevibacter ruminantium. This project aimed to assemble a collection of phages to be employed in phage therapy. A range of animal-derived and environmental source samples were tested using culture-based methodology, however no lytic phages of methanogens were isolated. Given the dearth of knowledge regarding phages of rumen methanogens, this project established that these naturally-occurring phages may be present in very low concentrations within the rumen and this will need to be considered in future methanogen-phage isolation investigations. The project has begun the process of developing and adapting new methodologies for detecting and examining these phages

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This project will define the plant pathogen incursion risk posed by people returning from overseas and interstate travel. This will be achieved through the development of technically sound sample/survey methodologies. The project will initially focus on cereal rusts. An assessment of the current level of human mediated rust entries into Australia will be determined through the sampling of travellers who have been known to have visited grain production regions overseas.

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Resistance to phosphine in target pests threatens market access for Australian grain. While the grains industry is now attempting to develop an effective and sustainable strategy to manage this resistance, action is severely limited by significant gaps in our knowledge of the key ecological factors that influence the development of resistance. There is a need to research this information as a foundation for a rational approach to managing phosphine resistance in the Australian grains industry. Research outcomes: The project has provided critical research methodologies and preliminary data to fill the large gaps in our knowledge of the ecology of two key pests, Rhyzopertha dominica and Tribolium castaneum, and how this may drive the development of phosphine resistance. This information will contribute to the groundwork for future research needed to provide a scientific basis for a rational resistance management strategy.

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Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.