• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 4
  • Tagged with
  • 9
  • 9
  • 5
  • 5
  • 5
  • 4
  • 4
  • 4
  • 4
  • 4
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Herbicide Screen for Melons

Umeda, K., MacNeil, D., Lund, N., Roberts, D. 08 1900 (has links)
Seventeen herbicides recently gaining registrations in corn, soybeans, or other major crops were evaluated in screening tests for potential use in melons. In a preemergence herbicide screening test, flumioxazin, dimethenamid, halosulfuron, and s-metolachlor demonstrated melon crop safety at rates higher than rates for effective weed control. In a postemergence screening test, halosulfuron and rimsulfuron gave acceptable weed control with adequate crop safety. Flumetsulam and thifensulfuron appeared to offer some acceptable weed control with a very narrow margin of crop safety. Herbicides that did not offer adequate melon crop safety or acceptable weed control in the screening tests were carfentrazone, sulfentrazone, cloransulam, flumiclorac, fluthiamide/metribuzin, imazamox, isoxaflutole, triflusulfuron, primisulfuron/prosulfuron, and clomazone.
2

Evaluation of Herbicides for Nutsedge Control in Carrots

Umeda, Kai 08 1900 (has links)
Halosulfuron and sulfentrazone were not safe to carrots at the lowest rates tested at 0.025 and 0.188 lb AI/A, respectively. At 20 DAT, halosulfuron at 0.038 to 0.075 lb AI/A gave better than 92% control of nutsedge in carrots. Nutsedge control was 77 to 80% at 20 DAT sulfentrazone applied at 0.188 to 0.375 lb AI/A. Both herbicides demonstrated slow activity against nutsedge during the first 7 DAT and then progressed to reduce weed growth at 13 to 20 DAT. Sulfentrazone appeared to act slightly faster than halosulfuron but showed maximum activity at 13 to 20 DAT.
3

Halosulfuron for Weed Control in Watermelon

Umeda, K., MacNeil, D., Roberts, D., Lund, N. 08 1900 (has links)
Halosulfuron at rates ranging from 0.05 to 0.10 lb AI/A with no adjuvant added to the POST application spray did not cause any injury to watermelons. Halosulfuron did not appear to cause significant crop injury earlier in the season to reduce marketable fruit yield at harvest. Halosulfuron was highly effective against London rocket but did not control purslane or groundcherry. Weed control efficacy was improved significantly when Latron CS-7 or Activator-90 was added to halosulfuron at either 0.05 or 0.075 lb AI/A. LI-700 did not improve the activity of halosulfuron over the treatments without an adjuvant.
4

Screening New Herbicides for Weed Control in Head and Leaf Lettuces and Broccoli

Umeda, Kai 08 1900 (has links)
In preemergence (PREE) herbicide testing, all three lettuces, head, romaine, and red leaf, exhibited some tolerance to carfentrazone, sulfentrazone, flumetsulam, rimsulfuron, and thifensulfuron while giving effective weed control. In postemergence (POST) testing, cloransulam and flumetsulam controlled weeds at the lowest applied rates while lettuces were safe to cloransulam at 0.01 lb AI/A and flumetsulam at 0.03 lb AI/A. Imazamox was safe on lettuces at 0.01 lb AI/A and controlled weeds at 0.007 lb AI/A. For broccoli, sulfentrazone, fluroxypyr, and thifensulfuron applied PREE demonstrated reasonable safety and weed control. Cloransulam, flumetsulam, and fluroxypyr applied POST on broccoli exhibited adequate crop safety and good weed control.
5

Weed resistance risk management in glyphosate-resistant cotton

Werth, Jeff Alan January 2006 (has links)
The introduction of glyphosate resistance into Australian cotton systems will have an effect on conventional weed management practices, the weed species present and the risk of glyphosate resistance evolving in weed species. Therefore, it is important that the effects of these management practices, particularly a potential reduction in Integrated Weed Management (IWM) practices, be examined to determine their impact on weed population dynamics and resistance selection. The study began in 2003 with a survey of 40 growers in four major cotton growing regions in Australia to gain an understanding of how adoption of glyphosate resistance had influenced the weed spectrum, weed management practices and herbicide use after three years of glyphosate-resistant cotton being available. The 10 most common weeds reported on cotton fields were the same in glyphosate-resistant and conventional fields. In this survey, herbicide use patterns were altered by the adoption of glyphosate-resistant cotton with up to six times more glyphosate being applied and with 21% fewer growers applying pre-emergence herbicides in glyphosate-resistant cotton fields. Other weed control practices, such as the use of post-emergence herbicides, inter-row cultivation and hand hoeing, were only reduced marginally. A systems experiment was conducted to determine differences in the population dynamics of Echinochloa crus-galli (barnyardgrass) and Urochloa panicoides (liverseed grass) under a range of weed management regimes in a glyphosate-resistant cotton system. These treatments ranged from a full IWM system to a system based soley on the use of glyphosate. The experiment investigated the effect of the treatments on the soil seed bank, weed germination patterns and weed numbers in the field. All applied treatments resulted in commercially acceptable control of the two grass weeds. However, the treatments containing soil-applied residual herbicides proved to be more effective over the period of the experiment. The treatment with a reduced residual herbicide program supplemented with glyphosate had a level of control similar to the full IWM treatments with less input, providing a more economical option. The effectiveness of these treatments in the long-term was examined in a simulation model to determine the likelihood of glyphosate resistance evolving using barnyardgrass and liverseed grass as model weeds. Seed production and above-ground biomass of barnyardgrass and liverseed grass in competition with cotton were measured. In all experiments, seed production and biomass plant⁻¹ decreased as weed density increased while seed production and biomass m⁻¹ tended to increase. Seed production m⁻¹ reached 40,000 and 60,000 for barnyardgrass and liverseed grass, respectively. In 2004-05, weeds were also planted 6 weeks and 12 weeks after the cotton was planted. Biomass and seed production of the two weeds planted 6 weeks after cotton were significantly reduced with seed production declining to 12,000 and 2,500 seeds m⁻¹ row for barnyardgrass and liverseed grass, respectively. Weeds planted 12 weeks after cotton planting failed to emerge. This experiment highlighted the importance of early season weed control and effective management of weeds that are able to produce high seed numbers. A glyphosate dose-mortality experiment was conducted in the field to determine levels of control of barnyardgrass and liverseed grass. Glyphosate provided effective control of both species with over 85% control when the rate applied was greater than 690 g ae ha⁻¹. Dose-mortality curves for both species were obtained for use in the glyphosate resistance model. Data from the experimental work were combined to develop a glyphosate resistance model. Outputs from this model suggest that if glyphosate were used as the only form of weed control, resistance in weeds is likely to eventuate after 12 to 17 years, depending on the characteristics of the weed species, initial resistance gene frequencies and any associated fitness penalties. If glyphosate was used in conjunction with one other weed control method, resistance was delayed but not prevented. The simulations suggested that when a combination of weed control options was employed in addition to glyphosate, resistance would not evolve over the 30-year period of the simulation. These simulations underline the importance of an integrated strategy in weed management to prevent glyphosate resistance evolving from the use of glyphosate-resistant cotton. Current management conditions of growing glyphosate-resistant (Roundup Ready &reg) cotton should therefore prevent glyphosate resistance evolution. / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2006.
6

Weed resistance risk management in glyphosate-resistant cotton

Werth, Jeff Alan January 2006 (has links)
The introduction of glyphosate resistance into Australian cotton systems will have an effect on conventional weed management practices, the weed species present and the risk of glyphosate resistance evolving in weed species. Therefore, it is important that the effects of these management practices, particularly a potential reduction in Integrated Weed Management (IWM) practices, be examined to determine their impact on weed population dynamics and resistance selection. The study began in 2003 with a survey of 40 growers in four major cotton growing regions in Australia to gain an understanding of how adoption of glyphosate resistance had influenced the weed spectrum, weed management practices and herbicide use after three years of glyphosate-resistant cotton being available. The 10 most common weeds reported on cotton fields were the same in glyphosate-resistant and conventional fields. In this survey, herbicide use patterns were altered by the adoption of glyphosate-resistant cotton with up to six times more glyphosate being applied and with 21% fewer growers applying pre-emergence herbicides in glyphosate-resistant cotton fields. Other weed control practices, such as the use of post-emergence herbicides, inter-row cultivation and hand hoeing, were only reduced marginally. A systems experiment was conducted to determine differences in the population dynamics of Echinochloa crus-galli (barnyardgrass) and Urochloa panicoides (liverseed grass) under a range of weed management regimes in a glyphosate-resistant cotton system. These treatments ranged from a full IWM system to a system based soley on the use of glyphosate. The experiment investigated the effect of the treatments on the soil seed bank, weed germination patterns and weed numbers in the field. All applied treatments resulted in commercially acceptable control of the two grass weeds. However, the treatments containing soil-applied residual herbicides proved to be more effective over the period of the experiment. The treatment with a reduced residual herbicide program supplemented with glyphosate had a level of control similar to the full IWM treatments with less input, providing a more economical option. The effectiveness of these treatments in the long-term was examined in a simulation model to determine the likelihood of glyphosate resistance evolving using barnyardgrass and liverseed grass as model weeds. Seed production and above-ground biomass of barnyardgrass and liverseed grass in competition with cotton were measured. In all experiments, seed production and biomass plant⁻¹ decreased as weed density increased while seed production and biomass m⁻¹ tended to increase. Seed production m⁻¹ reached 40,000 and 60,000 for barnyardgrass and liverseed grass, respectively. In 2004-05, weeds were also planted 6 weeks and 12 weeks after the cotton was planted. Biomass and seed production of the two weeds planted 6 weeks after cotton were significantly reduced with seed production declining to 12,000 and 2,500 seeds m⁻¹ row for barnyardgrass and liverseed grass, respectively. Weeds planted 12 weeks after cotton planting failed to emerge. This experiment highlighted the importance of early season weed control and effective management of weeds that are able to produce high seed numbers. A glyphosate dose-mortality experiment was conducted in the field to determine levels of control of barnyardgrass and liverseed grass. Glyphosate provided effective control of both species with over 85% control when the rate applied was greater than 690 g ae ha⁻¹. Dose-mortality curves for both species were obtained for use in the glyphosate resistance model. Data from the experimental work were combined to develop a glyphosate resistance model. Outputs from this model suggest that if glyphosate were used as the only form of weed control, resistance in weeds is likely to eventuate after 12 to 17 years, depending on the characteristics of the weed species, initial resistance gene frequencies and any associated fitness penalties. If glyphosate was used in conjunction with one other weed control method, resistance was delayed but not prevented. The simulations suggested that when a combination of weed control options was employed in addition to glyphosate, resistance would not evolve over the 30-year period of the simulation. These simulations underline the importance of an integrated strategy in weed management to prevent glyphosate resistance evolving from the use of glyphosate-resistant cotton. Current management conditions of growing glyphosate-resistant (Roundup Ready &reg) cotton should therefore prevent glyphosate resistance evolution. / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2006.
7

Weed resistance risk management in glyphosate-resistant cotton

Werth, Jeff Alan January 2006 (has links)
The introduction of glyphosate resistance into Australian cotton systems will have an effect on conventional weed management practices, the weed species present and the risk of glyphosate resistance evolving in weed species. Therefore, it is important that the effects of these management practices, particularly a potential reduction in Integrated Weed Management (IWM) practices, be examined to determine their impact on weed population dynamics and resistance selection. The study began in 2003 with a survey of 40 growers in four major cotton growing regions in Australia to gain an understanding of how adoption of glyphosate resistance had influenced the weed spectrum, weed management practices and herbicide use after three years of glyphosate-resistant cotton being available. The 10 most common weeds reported on cotton fields were the same in glyphosate-resistant and conventional fields. In this survey, herbicide use patterns were altered by the adoption of glyphosate-resistant cotton with up to six times more glyphosate being applied and with 21% fewer growers applying pre-emergence herbicides in glyphosate-resistant cotton fields. Other weed control practices, such as the use of post-emergence herbicides, inter-row cultivation and hand hoeing, were only reduced marginally. A systems experiment was conducted to determine differences in the population dynamics of Echinochloa crus-galli (barnyardgrass) and Urochloa panicoides (liverseed grass) under a range of weed management regimes in a glyphosate-resistant cotton system. These treatments ranged from a full IWM system to a system based soley on the use of glyphosate. The experiment investigated the effect of the treatments on the soil seed bank, weed germination patterns and weed numbers in the field. All applied treatments resulted in commercially acceptable control of the two grass weeds. However, the treatments containing soil-applied residual herbicides proved to be more effective over the period of the experiment. The treatment with a reduced residual herbicide program supplemented with glyphosate had a level of control similar to the full IWM treatments with less input, providing a more economical option. The effectiveness of these treatments in the long-term was examined in a simulation model to determine the likelihood of glyphosate resistance evolving using barnyardgrass and liverseed grass as model weeds. Seed production and above-ground biomass of barnyardgrass and liverseed grass in competition with cotton were measured. In all experiments, seed production and biomass plant⁻¹ decreased as weed density increased while seed production and biomass m⁻¹ tended to increase. Seed production m⁻¹ reached 40,000 and 60,000 for barnyardgrass and liverseed grass, respectively. In 2004-05, weeds were also planted 6 weeks and 12 weeks after the cotton was planted. Biomass and seed production of the two weeds planted 6 weeks after cotton were significantly reduced with seed production declining to 12,000 and 2,500 seeds m⁻¹ row for barnyardgrass and liverseed grass, respectively. Weeds planted 12 weeks after cotton planting failed to emerge. This experiment highlighted the importance of early season weed control and effective management of weeds that are able to produce high seed numbers. A glyphosate dose-mortality experiment was conducted in the field to determine levels of control of barnyardgrass and liverseed grass. Glyphosate provided effective control of both species with over 85% control when the rate applied was greater than 690 g ae ha⁻¹. Dose-mortality curves for both species were obtained for use in the glyphosate resistance model. Data from the experimental work were combined to develop a glyphosate resistance model. Outputs from this model suggest that if glyphosate were used as the only form of weed control, resistance in weeds is likely to eventuate after 12 to 17 years, depending on the characteristics of the weed species, initial resistance gene frequencies and any associated fitness penalties. If glyphosate was used in conjunction with one other weed control method, resistance was delayed but not prevented. The simulations suggested that when a combination of weed control options was employed in addition to glyphosate, resistance would not evolve over the 30-year period of the simulation. These simulations underline the importance of an integrated strategy in weed management to prevent glyphosate resistance evolving from the use of glyphosate-resistant cotton. Current management conditions of growing glyphosate-resistant (Roundup Ready &reg) cotton should therefore prevent glyphosate resistance evolution. / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2006.
8

Weed resistance risk management in glyphosate-resistant cotton

Werth, Jeff Alan January 2006 (has links)
The introduction of glyphosate resistance into Australian cotton systems will have an effect on conventional weed management practices, the weed species present and the risk of glyphosate resistance evolving in weed species. Therefore, it is important that the effects of these management practices, particularly a potential reduction in Integrated Weed Management (IWM) practices, be examined to determine their impact on weed population dynamics and resistance selection. The study began in 2003 with a survey of 40 growers in four major cotton growing regions in Australia to gain an understanding of how adoption of glyphosate resistance had influenced the weed spectrum, weed management practices and herbicide use after three years of glyphosate-resistant cotton being available. The 10 most common weeds reported on cotton fields were the same in glyphosate-resistant and conventional fields. In this survey, herbicide use patterns were altered by the adoption of glyphosate-resistant cotton with up to six times more glyphosate being applied and with 21% fewer growers applying pre-emergence herbicides in glyphosate-resistant cotton fields. Other weed control practices, such as the use of post-emergence herbicides, inter-row cultivation and hand hoeing, were only reduced marginally. A systems experiment was conducted to determine differences in the population dynamics of Echinochloa crus-galli (barnyardgrass) and Urochloa panicoides (liverseed grass) under a range of weed management regimes in a glyphosate-resistant cotton system. These treatments ranged from a full IWM system to a system based soley on the use of glyphosate. The experiment investigated the effect of the treatments on the soil seed bank, weed germination patterns and weed numbers in the field. All applied treatments resulted in commercially acceptable control of the two grass weeds. However, the treatments containing soil-applied residual herbicides proved to be more effective over the period of the experiment. The treatment with a reduced residual herbicide program supplemented with glyphosate had a level of control similar to the full IWM treatments with less input, providing a more economical option. The effectiveness of these treatments in the long-term was examined in a simulation model to determine the likelihood of glyphosate resistance evolving using barnyardgrass and liverseed grass as model weeds. Seed production and above-ground biomass of barnyardgrass and liverseed grass in competition with cotton were measured. In all experiments, seed production and biomass plant⁻¹ decreased as weed density increased while seed production and biomass m⁻¹ tended to increase. Seed production m⁻¹ reached 40,000 and 60,000 for barnyardgrass and liverseed grass, respectively. In 2004-05, weeds were also planted 6 weeks and 12 weeks after the cotton was planted. Biomass and seed production of the two weeds planted 6 weeks after cotton were significantly reduced with seed production declining to 12,000 and 2,500 seeds m⁻¹ row for barnyardgrass and liverseed grass, respectively. Weeds planted 12 weeks after cotton planting failed to emerge. This experiment highlighted the importance of early season weed control and effective management of weeds that are able to produce high seed numbers. A glyphosate dose-mortality experiment was conducted in the field to determine levels of control of barnyardgrass and liverseed grass. Glyphosate provided effective control of both species with over 85% control when the rate applied was greater than 690 g ae ha⁻¹. Dose-mortality curves for both species were obtained for use in the glyphosate resistance model. Data from the experimental work were combined to develop a glyphosate resistance model. Outputs from this model suggest that if glyphosate were used as the only form of weed control, resistance in weeds is likely to eventuate after 12 to 17 years, depending on the characteristics of the weed species, initial resistance gene frequencies and any associated fitness penalties. If glyphosate was used in conjunction with one other weed control method, resistance was delayed but not prevented. The simulations suggested that when a combination of weed control options was employed in addition to glyphosate, resistance would not evolve over the 30-year period of the simulation. These simulations underline the importance of an integrated strategy in weed management to prevent glyphosate resistance evolving from the use of glyphosate-resistant cotton. Current management conditions of growing glyphosate-resistant (Roundup Ready &reg) cotton should therefore prevent glyphosate resistance evolution. / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2006.
9

Development and evaluation of an automated tactical tillage tool to control weeds in row-crop production systems

Friday, Grace McCormick 12 May 2023 (has links) (PDF)
Weed control is an integral part of a successful overall production strategy in row- cropping systems and has the potential to reduce or eliminate yield losses that negatively affect profitability. Timely and correctly selected herbicide applications are the major keys for effective weed control in a majority of instances. However, there are negative factors that contribute to ineffectiveness and weed escape issues that currently lack viable options for management. Sparsely populated late-season weeds that emerge after lay-by herbicide applications and weeds that have become tolerant and resistant to traditional herbicide chemistries are of greatest concern. Historically, these weeds would have been pulled or chopped by hand or removed by cultivation, but with current production strategies built around conservation tillage and herbicide management practices, blanket disturbance of the soil through plowing is not a viable option. There is an immediate need for site-specific weed management to address these weed escapes while minimizing soil disturbance that reduces residual herbicide efficacy and lessens moisture losses that negatively effects the growing crop

Page generated in 0.064 seconds