12 resultados para Simulation and modelling

em eResearch Archive - Queensland Department of Agriculture


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Highly productive sown pasture systems can result in high growth rates of beef cattle and lead to increases in soil nitrogen and the production of subsequent crops. The nitrogen dynamics and growth of grain sorghum following grazed annual legume leys or a grass pasture were investigated in a no-till system in the South Burnett district of Queensland. Two years of the tropical legumes Macrotyloma daltonii and Vigna trilobata (both self regenerating annual legumes) and Lablab purpureus (a resown annual legume) resulted in soil nitrate N (0-0.9 m depth), at sorghum sowing, ranging from 35 to 86 kg/ha compared with 4 kg/ha after pure grass pastures. Average grain sorghum production in the 4 cropping seasons following the grazed legume leys ranged from 2651 to 4012 kg/ha. Following the grass pasture, grain sorghum production in the first and second year was < 1900 kg/ha and by the third year grain yield was comparable to the legume systems. Simulation studies utilising the farming systems model APSIM indicated that the soil N and water dynamics following 2-year ley phases could be closely represented over 4 years and the prediction of sorghum growth during this time was reasonable. In simulated unfertilised sorghum crops grown from 1954 to 2004, grain yield did not exceed 1500 kg/ha in 50% of seasons following a grass pasture, while following 2-year legume leys, grain exceeded 3000 kg/ha in 80% of seasons. It was concluded that mixed farming systems that utilise short term legume-based pastures for beef production in rotation with crop production enterprises can be highly productive.

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It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated until late canopy expansion followed by rainfed) was used to compare effects of water stress on crop production in two maize (Zea mays L.) cultivars (Pioneer 34N43 and Pioneer 31H50). Water stress affected growth and yield more in Pioneer 34N43 than in Pioneer 31H50. A crop model APSIM-Maize, after having been calibrated for the two cultivars, was used to simulate maize growth and development under water stress. The predictions on leaf area index (LAI) dynamics, biomass growth and grain yield under rain fed and irrigated followed by rain fed treatments was reasonable, indicating that stress indices used by APSIM-Maize produced appropriate adjustments to crop growth and development in response to water stress. This study shows that Pioneer 31H50 is less sensitive to water stress and thus a preferred cultivar in dryland conditions, and that it is feasible to provide sound predictions and risk assessment for crop production in drier, more variable conditions using the APSIM-Maize model.

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This project aims to use simulatiion modelling to improve our understanding of the genetics and physiology of complex traits with a view to increasing the rate of genetic gain in plant breeding programs.

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Heat stress can cause sterility in sorghum and the anticipated increased frequency of high temperature events implies increasing risk to sorghum productivity in Australia. Here we summarise our research on specific varietal attributes associated with heat stress tolerance in sorghum and evaluate how they might affect yield outcomes in production environments by a crop simulation analysis. We have recently conducted a range of controlled environment and field experiments to study the physiology and genetics of high temperature effects on growth and development of sorghum. Sorghum seed set was reduced by high temperature effects (>36-38oC) on pollen germination around flowering, but genotypes differed in their tolerance to high temperature stress. Effects were quantified in a manner that enabled their incorporation into the APSIM sorghum crop model. Simulation analysis indicated that risk of high temperature damage and yield loss depended on sowing date, and variety. While climate trends will exacerbate high temperature effects, avoidance by crop management and genetic tolerance seems possible.

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Targets for improvements in water quality entering the Great Barrier Reef (GBR) have been set through the Reef Water Quality Protection Plan (Reef Plan). To measure and report on progress towards the targets set a program has been established that combines monitoring and modelling at paddock through to catchment and reef scales; the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (Paddock to Reef Program). This program aims to provide evidence of links between land management activities, water quality and reef health. Five lines of evidence are used: the effectiveness of management practices to improve water quality; the prevalence of management practice adoption and change in catchment indicators; long-term monitoring of catchment water quality; paddock & catchment modelling to provide a relative assessment of progress towards meeting targets; and finally marine monitoring of GBR water quality and reef ecosystem health. This paper outlines the first four lines of evidence. (C) 2011 Elsevier Ltd. All rights reserved.

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Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.

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In wheat, tillering and water-soluble carbohydrates (WSCs) in the stem are potential traits for adaptation to different environments and are of interest as targets for selective breeding. This study investigated the observation that a high stem WSC concentration (WSCc) is often related to low tillering. The proposition tested was that stem WSC accumulation is plant density dependent and could be an emergent property of tillering, whether driven by genotype or by environment. A small subset of recombinant inbred lines (RILs) contrasting for tillering was grown at different plant densities or on different sowing dates in multiple field experiments. Both tillering and WSCc were highly influenced by the environment, with a smaller, distinct genotypic component; the genotypeenvironment range covered 350750 stems m(2) and 25210mg g(1) WSCc. Stem WSCc was inversely related to stem number m(2), but genotypic rankings for stem WSCc persisted when RILs were compared at similar stem density. Low tilleringhigh WSCc RILs had similar leaf area index, larger individual leaves, and stems with larger internode cross-section and wall area when compared with high tilleringlow WSCc RILs. The maximum number of stems per plant was positively associated with growth and relative growth rate per plant, tillering rate and duration, and also, in some treatments, with leaf appearance rate and final leaf number. A common threshold of the red:far red ratio (0.390.44; standard error of the difference0.055) coincided with the maximum stem number per plant across genotypes and plant densities, and could be effectively used in crop simulation modelling as a ocut-off' rule for tillering. The relationship between tillering, WSCc, and their component traits, as well as the possible implications for crop simulation and breeding, is discussed.

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Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

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Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

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Effective study in the native range to identify potential agents underpins all efforts in classical biological control of weeds. Good agents that demonstrate both a high degree of host specificity and the potential to be damaging are a very limited resource and must therefore be carefully studied and considered. The overseas component is often operationally difficult and expensive but can contribute considerably more than a list of herbivores attacking a particular target. While the principles underlying this foreign component have been understood for some time, recently developed technologies and methods can make very significant contributions to foreign studies. Molecular and genetic characterisations of both target weed and agent organism can be increasingly employed to more accurately define the identity and phylogeny of them. Climate matching and modelling software is now available and can be utilised to better select agents for particular regions of concern. Relational databases can store collection information for analysis and future enquiry while quantification of sampling effort, employment of statistical survey methods and analysis by techniques such as rarefaction curves contribute to efficient and effective searching. Obtaining good and timely identifications for discovered agent organisms is perhaps the most serious issue confronting the modern explorer. The diminishing numbers of specialist taxonomists employed at the major museums while international and national protocols demand higher standards of identity exacerbates the issue. Genetic barcoding may provide a very useful tool to overcome this problem. Native-range work also offers under-exploited opportunities for contributing towards predicting safety, abundance and efficacy of potential agents in their target environment.

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The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

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The Mobulidae are zooplanktivorous elasmobranchs comprising two recognized species of manta rays (Manta spp.) and nine recognized species of devil rays (Mobula spp.). They are found circumglobally in tropical, subtropical and temperate coastal waters. Although mobulids have been recorded for over 400 years, critical knowledge gaps still compromise the ability to assess the status of these species. On the basis of a review of 263 publications, a comparative synthesis of the biology and ecology of mobulids was conducted to examine their evolution, taxonomy, distribution, population trends, movements and aggregation, reproduction, growth and longevity, feeding, natural mortality and direct and indirect anthropogenic threats. There has been a marked increase in the number of published studies on mobulids since c. 1990, particularly for the genus Manta, although the genus Mobula remains poorly understood. Mobulid species have many common biological characteristics although their ecologies appear to be species-specific, and sometimes region-specific. Movement studies suggest that mobulids are highly mobile and have the potential to rapidly travel large distances. Fishing pressure is the major threat to many mobulid populations, with current levels of exploitation in target fisheries unlikely to be sustainable. Advances in the fields of population genetics, acoustic and satellite tracking, and stable-isotope and fatty-acid analyses will provide new insights into the biology and ecology of these species. Future research should focus on the uncertain taxonomy of mobulid species, the degree of overlap between their large-scale movement and human activities such as fisheries and pollution, and the need for management of inter-jurisdictional fisheries in developing nations to ensure their long-term sustainability. Closer collaboration among researchers worldwide is necessary to ensure standardized sampling and modelling methodologies to underpin global population estimates and status.