910 resultados para Integrated Crop-Livestock Systems


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Enterprise Systems (ES) provide standardized, off-theshelf support for operations and management within organizations. With the advent of ES based on a serviceoriented architecture (SOA) and an increasing demand of IT-supported interorganizational collaboration, implementation projects face paradigmatically new challenges. The configuration of ES is costly and error-prone. Dependencies between business processes and business documents are hardly explicit and foster component proliferation instead of reuse. Configurative modeling can support the problem in two ways: First, conceptual modeling abstracts from technical details and provides more intuitive access and overview. Second, configuration allows the projection of variants from master models providing manageable variants with controlled flexibility. We aim at tackling the problem by proposing an integrated model-based framework for configuring both, processes and business documents, on an equal basis; as together, they constitute the core business components of an ES.

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The Beyond Compliance project, which began in July 2011 with funding from the Standards and Trade Development Facility for 2 years, aims to enhance competency and confidence in the South East Asian sub-region by applying a Systems Approach for pest risk management. The Systems Approach involves the use of integrated measures, at least two of which are independent, that cumulatively reduce the risk of introducing exotic pests through trade. Although useful in circumstances where single measures are inappropriate or unavailable, the Systems Approach is inherently more complicated than single-measure approaches, which may inhibit its uptake. The project methodology is to take prototype decision-support tools, such as Control Point-Bayesian Networks (CP-BN), developed in recent plant health initiatives in other regions, including the European PRATIQUE project, and to refine them within this sub-regional context. Case studies of high-priority potential agricultural trade will be conducted by National Plant Protection Organizations of participating South East Asian countries in trials of the tools, before further modifications. Longer term outcomes may include: more robust pest risk management in the region (for exports and imports); greater inclusion of stakeholders in development of pest risk management plans; increased confidence in trade negotiations; and new opportunities for trade.

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Agriculture is responsible for a significant proportion of total anthropogenic greenhouse gas emissions (perhaps 18% globally), and therefore has the potential to contribute to efforts to reduce emissions as a means of minimising the risk of dangerous climate change. The largest contributions to emissions are attributed to ruminant methane production and nitrous oxide from animal waste and fertilised soils. Further, livestock, including ruminants, are an important component of global and Australian food production and there is a growing demand for animal protein sources. At the same time as governments and the community strengthen objectives to reduce greenhouse gas emissions, there are growing concerns about global food security. This paper provides an overview of a number of options for reducing methane and nitrous oxide emissions from ruminant production systems in Australia, while maintaining productivity to contribute to both objectives. Options include strategies for feed modification, animal breeding and herd management, rumen manipulation and animal waste and fertiliser management. Using currently available strategies, some reductions in emissions can be achieved, but practical commercially available techniques for significant reductions in methane emissions, particularly from extensive livestock production systems, will require greater time and resource investment. Decreases in the levels of emissions from these ruminant systems (i.e., the amount of emissions per unit of product such as meat) have already been achieved. However, the technology has not yet been developed for eliminating production of methane from the rumen of cattle and sheep digesting the cellulose and lignin-rich grasses that make up a large part of the diet of animals grazing natural pastures, particularly in arid and semi-arid grazing lands. Nevertheless, the abatement that can be achieved will contribute significantly towards reaching greenhouse gas emissions reduction targets and research will achieve further advances.

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This paper explores the possibility of using grid side inverter as an interface to connect energy storage systems. A dual inverter system, formed by cascading two 2-level inverters through a coupling transformer, is used as the testing model. The inverters are named as “main inverter” and “auxiliary inverter”. The main inverter is powered by the rectified output of the wind generator while the auxiliary inverter is attached to a Battery Energy Storage System (BESS). If there is a surplus of wind power compared to the demand, then that would be stored in BESS while if there is a deficit in wind power then the demand will be satisfied by supplying power from the BESS. This enables constant power dispatch to the grid irrespective of wind changes. Novel modulation and control techniques are proposed to address the problem of non-integer, dynamically-varying dc-link voltage ratio, which is due to random wind changes. Furthermore, a maximum power tracking controller for this unique system is explained in detail. Simulation results verify the efficacy of proposed modulation and control techniques in suppressing random power fluctuations.

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An increasing concern over the sustainability credentials of food and fiber crops require that farmers and their supply chain partners have access to appropriate and industry-friendly tools to be able to measure and improve the outcomes. This article focuses on one of the sustainability indicators, namely, greenhouse gas (GHG) emissions, and nine internationally accredited carbon footprint calculators were identified and compared on an outcomes basis against the same cropping data from a case study cotton farm. The purpose of this article is to identify the most “appropriate” methodology to be applied by cotton suppliers in this regard. From the analysis of the results, we subsequently propose a new integrated model as the basis for an internationally accredited carbon footprint tool for cotton and show how the model can be applied to evaluate the emission outcomes of different farming practices.

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There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

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Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

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BACKGROUND: Glyphosate-resistant cotton varieties are an important tool for weed control in Australian cotton production systems. To increase the sustainability of this technology and to minimise the likelihood of resistance evolving through its use, weed scientists, together with herbicide regulators, industry representatives and the technology owners, have developed a framework that guides the use of the technology. Central to this framework is a crop management plan (CMP) and grower accreditation course. A simulation model that takes into account the characteristics of the weed species, initial gene frequencies and any associated fitness penalties was developed to ensure that the CMP was sufficiently robust to minimise resistance risks. RESULTS: The simulations showed that, when a combination of weed control options was employed in addition to glyphosate, resistance did not evolve over the 30 year period of the simulation. CONCLUSION: These simulations underline the importance of maintaining an integrated system for weed management to prevent the evolution of glyphosate resistance, prolonging the use of glyphosate-resistant cotton.

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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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This project aims to develop integrated irrigation and nutrition management strategies under limited water for irrigators currently investing in overhead irrigation systems (CPLM) to minimize the learning lag in their use and optimize crop and economic performance.

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Dairy farms located in the subtropical cereal belt of Australia rely on winter and summer cereal crops, rather than pastures, for their forage base. Crops are mostly established in tilled seedbeds and the system is vulnerable to fertility decline and water erosion, particularly over summer fallows. Field studies were conducted over 5 years on contrasting soil types, a Vertosol and Sodosol, in the 650-mm annual-rainfall zone to evaluate the benefits of a modified cropping program on forage productivity and the soil-resource base. Growing forage sorghum as a double-crop with oats increased total mean annual production over that of winter sole-crop systems by 40% and 100% on the Vertosol and Sodosol sites respectively. However, mean annual winter crop yield was halved and overall forage quality was lower. Ninety per cent of the variation in winter crop yield was attributable to fallow and in-crop rainfall. Replacing forage sorghum with the annual legume lablab reduced fertiliser nitrogen (N) requirements and increased forage N concentration, but reduced overall annual yield. Compared with sole-cropped oats, double-cropping reduced the risk of erosion by extending the duration of soil water deficits and increasing the time ground was under plant cover. When grown as a sole-crop, well fertilised forage sorghum achieved a mean annual cumulative yield of 9.64 and 6.05 t DM/ha on the Vertosol and Sodosol, respectively, being about twice that of sole-cropped oats. Forage sorghum established using zero-tillage practices and fertilised at 175 kg N/ha. crop achieved a significantly higher yield and forage N concentration than did the industry-standard forage sorghum (conventional tillage and 55 kg N/ha. crop) on the Vertosol but not on the Sodosol. On the Vertosol, mean annual yield increased from 5.65 to 9.64 t DM/ha (33 kg DM/kg N fertiliser applied above the base rate); the difference in the response between the two sites was attributed to soil type and fertiliser history. Changing both tillage practices and N-fertiliser rate had no affect on fallow water-storage efficiency but did improve fallow ground cover. When forage sorghum, grown as a sole crop, was replaced with lablab in 3 of the 5 years, overall forage N concentration increased significantly, and on the Vertosol, yield and soil nitrate-N reserves also increased significantly relative to industry-standard sorghum. All forage systems maintained or increased the concentration of soil nitrate-N (0-1.2-m soil layer) over the course of the study. Relative to sole-crop oats, alternative forage systems were generally beneficial to the concentration of surface-soil (0-0.1 m) organic carbon and systems that included sorghum showed most promise for increasing soil organic carbon concentration. We conclude that an emphasis on double-or summer sole-cropping rather than winter sole-cropping will advantage both farm productivity and the soil-resource base.

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Echinochloa colona is the most common grass weed of summer fallows in the grain-cropping systems of the subtropical region of Australia. Glyphosate is the most commonly used herbicide for summer grass control in fallows in this region. The world's first population of glyphosate-resistant E. colona was confirmed in Australia in 2007 and, since then, >70 populations have been confirmed to be resistant in the subtropical region. The efficacy of alternative herbicides on glyphosate-susceptible populations was evaluated in three field experiments and on both glyphosate-susceptible and glyphosate-resistant populations in two pot experiments. The treatments were knockdown and pre-emergence herbicides that were applied as a single application (alone or in a mixture) or as part of a sequential application to weeds at different growth stages. Glyphosate at 720 g ai ha−1 provided good control of small glyphosate-susceptible plants (pre- to early tillering), but was not always effective on larger susceptible plants. Paraquat was effective and the most reliable when applied at 500 g ai ha−1 on small plants, irrespective of the glyphosate resistance status. The sequential application of glyphosate followed by paraquat provided 96–100% control across all experiments, irrespective of the growth stage, and the addition of metolachlor and metolachlor + atrazine to glyphosate or paraquat significantly reduced subsequent emergence. Herbicide treatments have been identified that provide excellent control of small E. colona plants, irrespective of their glyphosate resistance status. These tactics of knockdown herbicides, sequential applications and pre-emergence herbicides should be incorporated into an integrated weed management strategy in order to greatly improve E. colona control, reduce seed production by the sprayed survivors and to minimize the risk of the further development of glyphosate resistance.

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Reducing crop row spacing and delaying time of weed emergence may provide crops a competitive edge over weeds. Field experiments were conducted to evaluate the effects of crop row spacing (11, 15, and 23-cm) and weed emergence time (0, 20, 35, 45, 55, and 60 days after wheat emergence; DAWE) on Galium aparine and Lepidium sativum growth and wheat yield losses. Season-long weed-free and crop-free treatments were also established to compare wheat yield and weed growth, respectively. Row spacing and weed emergence time significantly affected the growth of both weed species and wheat grain yields. For both weed species, the maximum plant height, shoot biomass, and seed production were observed in the crop-free plots, and delayed emergence decreased these variables. In weed-crop competition plots, maximum weed growth was observed when weeds emerged simultaneously with the crop in rows spaced 23-cm apart. Less growth of both weed species was observed in narrow row spacing (11-cm) of wheat as compared with wider rows (15 and 23-cm). These weed species produced less than 5 seeds plant-1 in 11-cm wheat rows when they emerged at 60 DAWE. Presence of weeds in the crop especially at early stages was devastating for wheat yields. Therefore, maximum grain yield (4.91tha-1) was recorded in the weed-free treatment at 11-cm row spacing. Delay in time of weed emergence and narrow row spacing reduced weed growth and seed production and enhanced wheat grain yield, suggesting that these strategies could contribute to weed management in wheat.

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Lower water availability coupled with labor shortage has resulted in the increasing inability of growers to cultivate puddled transplanted rice (PTR). A field study was conducted in the wet season of 2012 and dry season of 2013 to evaluate the performance of five rice establishment methods and four weed control treatments on weed management, and rice yield. Grass weeds were higher in dry-seeded rice (DSR) as compared to PTR and nonpuddled transplanted rice (NPTR). The highest total weed density (225-256plantsm-2) and total weed biomass (315-501gm-2) were recorded in DSR while the lowest (102-129plantsm-2 and 75-387gm-2) in PTR. Compared with the weedy plots, the treatment pretilachlor followed by fenoxaprop plus ethoxysulfuron plus 2,4-D provided excellent weed control. This treatment, however, had a poor performance in NPTR. In both seasons, herbicide efficacy was better in DSR and wet-seeded rice. PTR and DSR produced the maximum rice grain yields. The weed-free plots and herbicide treatments produced 84-614% and 58-504% higher rice grain yield, respectively, than the weedy plots in 2012, and a similar trend was observed in 2013.