999 resultados para weed resistance
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Agronomia (Proteção de Plantas) - FCA
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Auxyn type herbicides such as dicamba and 2,4-D are alternative herbicides that can be used to control glyphosate-resistant hairy fleabane. With the forthcoming possibility of releasing dicamba-resistant and 2,4-D-resistant crops, use of these growth regulator herbicides will likely be an alternative that can be applied to the control of glyphosate resistant hairy fleabane (Conyza bonariensis). The objective of this research was to model the efficacy, through dose-response curves, of glyphosate, 2,4-D, isolated dicamba and glyphosate-dicamba combinations to control a brazilian hairy fleabane population resistant to glyphosate. The greenhouse dose-response studies were conducted as a completely randomized experimental design, and the rates used for dose response curve construction were 0, 120, 240, 480, 720 and 960 ga.i. ha(-1) for 2,4-D, dicamba and the dicamba combination, with glyphosate at 540 g a. e. ha(-1). The rates for glyphosate alone were 0, 180, 360, 540, 720 and 960 g a. e. ha(-1). Herbicides were applied when the plants were in a vegetative stage with 10 to 12 leaves and height between 12 and 15 cm. Hairy fleabane had low sensitivity to glyphosate, with poor control even at the 960 g a. e. ha(-1) rate. Dicamba and 2,4-D were effective in controlling the studied hairy fleabane. Hairy fleabane responds differently to 2,4-D and dicamba. The combination of glyphosate and dicamba was not antagonistic to hairy fleabane control, and glyphosate may cause an additive effect on the control, despite the population resistance.
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Auxyn type herbicides such as dicamba and 2,4-D are alternative herbicides that can be used to control glyphosate-resistant hairy fleabane. With the forthcoming possibility of releasing dicamba-resistant and 2,4-D-resistant crops, use of these growth regulator herbicides will likely be an alternative that can be applied to the control of glyphosate resistant hairy fleabane (Conyza bonariensis). The objective of this research was to model the efficacy, through dose-response curves, of glyphosate, 2,4-D, isolated dicamba and glyphosatedicamba combinations to control a brazilian hairy fleabane population resistant to glyphosate. The greenhouse dose-response studies were conducted as a completely randomized experimental design, and the rates used for dose response curve construction were 0, 120, 240, 480, 720 and 960 g a.i. ha-1 for 2,4-D, dicamba and the dicamba combination, with glyphosate at 540 g a.e. ha-1. The rates for glyphosate alone were 0, 180, 360, 540, 720 and 960 g a.e. ha-1. Herbicides were applied when the plants were in a vegetative stage with 10 to 12 leaves and height between 12 and 15 cm. Hairy fleabane had low sensitivity to glyphosate, with poor control even at the 960 g a.e. ha-1 rate. Dicamba and 2,4-D were effective in controlling the studied hairy fleabane. Hairy fleabane responds differently to 2,4-D and dicamba. The combination of glyphosate and dicamba was not antagonistic to hairy fleabane control, and glyphosate may cause an additive effect on the control, despite the population resistance.
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The effect of different methods of soil preparation on soil moisture loss, weed growth and soil resistance to penetration has been quantified for the Latosols of Bebedouro experiment station of CPATSA-EMBRAPA, Petrolina,PE, Brazil. The methods studied are manual preparation, preparation by animal drawn wheeled tool carrier and tractorized implements. The drying characteristics of three fields with different soil physical properties were studied prior to conducting the experiment. The different methods of soil preparation caused the soil moisture loss differently. The plot prepared by animal drawn tool carrier retained more moisture for longer time even at deeper layers. The soil resistance to penetration on the surface increased with time with little variation at deeper layers.
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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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The main weeds and weed management practices undertaken in broad acre dryland cropping areas of north-eastern Australia have been identified. The information was collected in a comprehensive postal survey of both growers and agronomists from Dubbo in New South Wales (NSW) through to Clermont in central Queensland, where 237 surveys were returned. A very diverse weed flora of 105 weeds from 91 genera was identified for the three cropping zones within the region (central Queensland, southern Queensland and northern NSW). Twenty-three weeds were common to all cropping zones. The major common weeds were Sonchus oleraceus, Rapistrum rugosum, Echinochloa spp. and Urochloa panicoides. The main weeds were identified for both summer and winter fallows, and sorghum, wheat and chickpea crops for each of the zones, with some commonality as well as floral uniqueness recorded. More genera were recorded in the fallows than in crops, and those in summer fallows exceeded the number in winter. Across the region, weed management relied heavily on herbicides. In fallows, glyphosate and mixes with glyphosate were very common, although the importance of the glyphosate mix partner differed among the cropping zones. Use and importance of pre-emergence herbicides in-crop varied considerably among the zones. In wheat, more graminicides were used in northern NSW than in southern Queensland, and virtually none were used in central Queensland, reflecting the differences in winter grass weed flora across the region. Atrazine was the major herbicide used in sorghum, although metolachlor was also used predominantly in northern NSW. Fallow and inter-row cultivation were used more often in the southern areas of the region. Grazing of fallows was more prominent in northern NSW. High crop seeding rates were not commonly recorded indicating that growers are not using crop competition as a tool for weed management. Although many management practices were recorded overall, few growers were using integrated weed management, and herbicide resistance has been and continues to be an issue for the region.
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Growing agricultural crops in wide row spacings has been widely adopted to conserve water, to control pests and diseases, and to minimise problems associated with sowing into stubble. The development of herbicide resistance combined with the advent of precision agriculture has resulted in a further reason for wide row spacings to be adopted: weed control. Increased row spacing enables two different methods of weed control to be implemented with non-selective chemical and physical control methods utilised in the wide inter-row zone, with or without selective chemicals used on the on-row only. However, continual application of herbicides and tillage on the inter-row zone brings risks of herbicide resistance, species shifts and/or changes in species dominance, crop damage, increased costs, yield losses, and more expensive weed management technology.
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Background and Aims: The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods: The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results: Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions: This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.
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This project will develop and deliver improved integrated weed management strategies for weeds at risk of glyphosate resistance and species shift in transgenic farming landscapes. It will also facilitate the stewarship of glyphosate and transgenic technology, improving the sustainability of both the herbicide and the genes.
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This project will develop better understanding of resistance to glyphosate, paraquat and Group I herbicides to better inform weed management. The project will develop a range of tools for farm advisors to improve their confidence in decision making with respect to reducing the risk of glyphosate, Group I and paraquat resistance. These will include risk assessments, case studies and scenario exploring tools. The project will discuss with commercial providers the potential for new herbicide registrations. The project will establish farm advisor learning groups to work on the application of the research in local areas where resistance is already a major problem and to improve adoption of research outcomes from this and other projects.
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The threat and management of glyphosate# resistant weeds are major issues facing northern region growers. At present five weeds are confirmed glyphosate-resistant: barnyard grass, liverseed grass, windmill grass, annual ryegrass and flaxleaf fleabane. This project used 25 experiments to investigate the ecology of the grass weeds, plus new or improved chemical and non-chemical control tactics for them. The refined glyphosate resistance model developed in this project used the experiments' findings to predict the long-term impacts on evolution of resistance and on seed bank numbers of resistant weeds. These data led to revised management and resistance avoidance strategies, which were published in the Reporter newsletter, and via an on-line risk assessment tool. - See more at: http://finalreports.grdc.com.au/UQ00054#sthash.oTkCN4Sk.dpuf
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The introduction of glyphosate tolerant cotton has significantly improved the flexibility and management of a number of problem weeds in cotton systems. However, reliance on glyphosate poses risks to the industry in term of glyphosate resistance and species shift. The aims of this project were to identify these risks, and determine strategies to prevent and mitigate the potential for resistance evolution. Field surveys identified fleabane as the most common weed now in both irrigated and dryland system. Sowthistle has also increased in prevalence, and bladder ketmia and peachvine remained common. The continued reliance on glyphosate has favoured small seeded, and glyphosate tolerant species. Fleabane is both of these, with populations confirmed resistant in grains systems in Queensland and NSW. When species were assessed for their resistance risk, fleabane, liverseed grass, feathertop Rhodes grass, sowthistle and barnyard grass were determined to have high risk ratings. Management practices were also determined to rely heavily on glyphosate and therefore be high risk in summer fallows, and dryland glyphosate tolerant and conventional cotton. Situations were these high risk species are present in high risk cropping phases need particular attention. The confirmation of a glyphosate resistance barnyard grass population in a dryland glyphosate tolerant cotton system means resistance is now a reality for the cotton industry. However, experiments have shown that resistant populations can be managed with other herbicide options currently available. However, the options for fleabane management in cotton are still limited. Although some selective residual herbicides are showing promise, the majority of fleabane control tactics can only be used in other phases of the cotton rotation. An online glyphosate resistance tool has been developed. This tool allows growers to assess their individual glyphosate resistance risks, and how they can adjust their practices to reduce their risks. It also provides researchers with current information on weed species present and practices used across the industry. This tool will be extremely useful in tailoring future research and extension efforts. Simulations from the expanded glyphosate resistance model have shown that glyphosate resistance can be prevented and managed in glyphosate-tolerant cotton farming systems. However, for strategies to be successful, some effort is required. Simulations have shown the importance of controlling survivors of glyphosate applications, using effective glyphosate alternatives in fallows, and combining several effective glyphosate alternatives in crop, and these are the key to the prevention and management of glyphosate resistance.
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In the last decade, Conyza bonariensis has become a widespread and difficult-to-control weed in Australian broad-acre cropping, particularly in glyphosate-based zero-tilled fallows of the subtropical grain region. The first Australian populations of C. bonariensis, where it is known as flaxleaf fleabane, were confirmed resistant to glyphosate in 2010. Control with alternative herbicides in fallows has been inconsistent, with earlier research indicating that weed age could be a potential contributing factor. In two field experiments, the impact of weed age (one, two and three months) was measured on the efficacy of six non-selective herbicide mixtures and sequential applications for control in fallows. In another two experiments we evaluated 11 non-selective herbicides, mixtures and sequential applications applied to one and three month old weeds using higher rates on older weeds. When herbicide rates were consistent for different weed ages, efficacy was reduced only by an average of 1% when two month old weeds were treated compared to one month old weeds. However when applied to three month old weeds, efficacy of treatments was significantly (P < 0.001) reduced by 3-30%. When herbicide rates were increased, weed age had no adverse effect on efficacy, which ranged from 90 to 100%, for amitrole, glyphosate mixed with 2,4-D amine plus picloram, and three sequential application treatments of glyphosate mixtures followed with bipyridyl products. Thus, this problem weed can be controlled effectively and consistently at the rosette stage of one to two months old, or three month old weeds with several different treatments at robust rates. These effective glyphosate alternatives and sequential-application tactics will minimise replenishment of the soil seed-bank and further reduce the risk for further evolution of glyphosate resistance. (C) 2012 Elsevier Ltd. All rights reserved.