Herbicides In Sugar Beet Research Articles

Joint action of some broadleaf herbicides in sugar beet

The mixture of herbicides is routinely used as part of modern weed management practices in intensive agriculture due to the reduction in herbicide application and the risk of side effects. Therefore, to detect the joint action of binary mixtures of the photosystem II, lipid biosynthesis and auxin inhibitor herbicides, additive dose model (ADM) was used as a reference model. Four species of Portulaca oleracea L., Solanum nigrum L., Amaranthus retroflexus L. and Chenopodium album L. were affected by desmedipham + phenmedipham + ethofumesate, chloridazon and clopyralid either single or in binary mixtures. Three binary mixtures of the three herbicides with seven doses of the herbicides were studied in four separate experiments. The values of ED50, ED80 and ED90 were calculated from the three- parameter log-logistic models dose–response curves for each herbicide applied alone or in mixtures of fixed ratios. Results showed that the mixtures efficacy of chloridazon and clopyralid were reduced more than predicted by ADM in all species. In contrast, at 80% and 90% response level, the mixtures of desmedipham + phenmedipham + ethofumesate and clopyralid were mainly synergistic on all species except P. oleracea. In addition, desmedipham + phenmedipham + ethofumesate and chloridazon binary mixtures followed ADM on S. nigrum and A. retroflexus and tended to be antagonistic on C. album and P. oleracea. Hence, there is a large potential for enhancing the specificity of herbicides by using mixtures of desmedipham + phenmedipham + ethofumesate and clopyralid (different site targets), delaying the development of herbicides resistance and diminishing the dose for weed control.

Herbicide options for glyphosate-resistant kochia (Bassia scoparia) management in the Great Plains

AbstractKochia is one of the most problematic weeds in the United States. Field studies were conducted in five states (Wyoming, Colorado, Kansas, Nebraska, and South Dakota) over 2 yr (2010 and 2011) to evaluate kochia control with selected herbicides registered in five common crop scenarios: winter wheat, fallow, corn, soybean, and sugar beet to provide insight for diversifying kochia management in crop rotations. Kochia control varied by experimental site such that more variation in kochia control and biomass production was explained by experimental site than herbicide choice within a crop. Kochia control with herbicides currently labeled for use in sugar beet averaged 32% across locations. Kochia control was greatest and most consistent from corn herbicide programs (99%), followed by soybean (96%) and fallow (97%) herbicide programs. Kochia control from wheat herbicide programs was 93%. With respect to the availability of effective herbicide options, glyphosate-resistant kochia control was easiest in corn, soybean, and fallow, followed by wheat; and difficult to manage with herbicides in sugar beet.

Differential sensitivity of Atriplex patula and Chenopodium album to sugar beet herbicides: a possible cause for the upsurge of A. patula in sugar beet fields

SummaryIn the last decade, the prevalence of Atriplex patula as a weed in the Belgian sugar beet area has increased. Possible reasons for its expansion in sugar beet fields, besides a poor implementation of the low‐dose phenmedipham/activator/soil‐acting herbicide (FAR) system, might be low sensitivity or evolved resistance to one or more herbicides used in sugar beet. Dose–response pot bioassays were conducted in the glasshouse to evaluate the effectiveness of five foliar‐applied sugar beet herbicides (metamitron, phenmedipham, desmedipham, ethofumesate and triallate) and three pre‐plant‐incorporated herbicides (metamitron, lenacil, dimethenamid‐P) for controlling five Belgian A. patula populations. Local metamitron‐susceptible and metamitron‐resistant populations of Chenopodium album were used as reference populations. Effective dosages and resistance indices were calculated. DNA sequence analysis of the photosystem II psbA gene was performed on putative resistant A. patula populations. Overall, A. patula exhibited large intraspecific variation in herbicide sensitivity. In general, A. patula populations were less susceptible to phenmedipham, desmedipham, ethofumesate and triallate relative to C. album populations. Two A. patula populations bear the leucine‐218 to valine mutation on the chloroplast psbA gene conferring low level to high level cross‐resistance to the photosystem II inhibitors phenmedipham, desmedipham, metamitron and lenacil. In order to avoid insufficient A. patula control and further spread, seedlings should preferentially be treated with FAR mixtures containing higher‐than‐standard doses of metamitron and phenmedipham/desmedipham and no later than the cotyledon stage.

Utilization of Chlorophyll Fluorescence Imaging Technology to Detect Plant Injury by Herbicides in Sugar Beet and Soybean

Sensor technologies are expedient tools for precision agriculture, aiming for yield protection while reducing operating costs. A portable sensor based on chlorophyll fluorescence imaging was used in greenhouse experiments to investigate the response of sugar beet and soybean cultivars to the application of herbicides. The sensor measured the maximum quantum efficacy yield in photosystem II (PS-II) (Fv/Fm). In sugar beet, the averageFv/Fmof 9 different cultivars 1 d after treatment of desmedipham plus phenmedipham plus ethofumesate plus lenacil was reduced by 56% compared to the nontreated control. In soybean, the application of metribuzin plus clomazone reducedFv/Fmby 35% 9 d after application in 7 different cultivars. Sugar beets recovered within few days from herbicide stress while maximum quantum efficacy yield in PS-II of soybean cultivars was reduced up to 28 d. At the end of the experiment, approximately 30 d after treatment, biomass was reduced up to 77% in sugar beet and 92% in soybean. Chlorophyll fluorescence imaging is a useful diagnostic tool to quantify phytotoxicity of herbicides on crop cultivars directly after herbicide application, but does not correlate with biomass reduction.

Agronomic Evaluation of Mechanical and Chemical Weed Management for Reducing Use of Herbicides in Single vs. Twin-Row Sugar Beet

Agronomic Evaluation of Mechanical and Chemical Weed Management for Reducing Use of Herbicides in Single vs. Twin-Row Sugar Beet

Results of the EPPO Survey on dose expression for seed treatment and authorized dose for plant protection products in general

Results of the <scp>EPPO</scp> Survey on dose expression for seed treatment and authorized dose for plant protection products in general

Control of annual broadleaf weeds by combinations of herbicides in sugar beet

Sugar beet is a poor competitor to weeds. Weeds are a major constraint to sugar beet productivity. Field experiments were conducted at Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry (55o23′ N, 23o51′ E) during the period 2010–2012 on a loamy Endocalcari-Epihypogleyic Cambisol (CMg-p-w-can) to determine the influence of tank-mixed herbicides phenmedipham + desmedipham + ethofumesate (136.5 + 106.5 + 168 g ha-1 a.i.) with chloridazon (624 g ha-1 a.i.), metamitron (700 g ha-1 a.i.) and triflusulfuron (3.75 g ha-1 a.i.) on broad leaf weeds. Phenmedipham + desmedipham + ethofumesate was applied at three doses, 1/1, 2/3 and 1/2 of the recommended dose. Metamitron was applied at two doses, 1/1 and 1/2 of the recommended dose. All herbicide combinations acted similarly in reducing these weed species: Chenopodium album, Thlaspi arvense, Tripleurospermum perforatum, Polygonum aviculare, Viola arvensis, Veronica arvensis, Lamium purpureum, Capsella bursa-pastoris and Euphorbia helioscopia. The efficacy of phenmedipham + desmedipham + ethofumesate at full (1/1) dose was similar to that applied in a tank mix with chloridazon, metamitron and triflusulfuron at full dose. There were no significant differences in weed weight. Having reduced the dose of phenmedipham + desmedipham + ethofumesate by 33% and 50% in a tank mix, the dry weight of C. album, T. perforatum and P. aviculare increased not significantly. The addition of chloridazon, metamitron and triflusulfuron at full dose had a similar impact on weeds. The action of triflusulfuron was longer because the weight of dominant weeds (C. album and T. perforatum) decreased (6–37%) during all crop growing period. Reducing the dose of metamitron from 525 to 350 g ha-1 a.i. (33%) in a tank mix with phenmedipfam + desmedipham + ethofumesate at 1/2 dose, the dry weight of C. album, T. perforatum, P. aviculare, V. arvensis and C. bursa-pastoris increased not significantly. By reducing the dose of herbicides in a tank mix, the number of active ingredients (a.i.) should be increased.

Contribution of groundkeepers vs. weed beet to gene escape from sugar beet (Beta vulgaris spp.). Consequences for growing genetically-modified sugar beet – A modelling approach

Weed beet cannot be controlled by herbicides in sugar beet (except via height-selective applicators) as it is a crop relative, descending from accidentally flowering sugar beet (Beta vulgaris) crop plants either because of vernalization during cold springs, or presence of a dominant bolting allele in sugar beet seed lots due to cross-pollination by annual wild beet (B. vulgaris ssp. maritima) in seed production areas. A second, minor source of weed beet are crop roots lost during harvest. These roots (“groundkeepers”) can reproduce in the year after sugar beet and potentially contribute to weed beet dynamics and gene flow. Bolting, flowering and seed production timing and potential of groundkeepers were measured in field experiments. Bolting and flowering were faster in groundkeepers vs. weed beet; flower and seed production was lower in groundkeepers but the latter were less sensitive to competitive crops. The measured parameters were used to introduce a ground-keeper life-cycle into the GeneSys-Beet model which quantifies the effects of cropping systems on weed beet in landscapes. Simulations over several years showed weed beet dynamics to be more sensitive to groundkeeper parameter values than to root loss at sugar beet harvest. Groundkeepers were identified as a key source of weed beet populations and of gene escape from novel sugar beet varieties (e.g. genetically-modified herbicide-tolerant varieties) in the absence of crop bolters. The control of the latter, either by manual weeding or by genetic improvement of sugar beet varieties, was shown to be essential for controlling weed beet populations and avoid the advent of herbicide-tolerant weed beet.

Impact of herbicide application intensity in relation to environment and tillage on earthworm population in sugar beet in Germany

The application of herbicides in sugar beet (Beta vulgaris L.) is essential to prevent yield loss due to weed competition. According to German regulations, herbicides can be applied in mixtures with variable intensities. The ecological impact of the resulting strategies is still poorly understood. However, it was hypothesized that the influence of herbicide strategies on earthworm abundance, biomass, and diversity is minor compared to environment and tillage intensity in sugar beet. Therefore, additional specific factor variation seemed to be a prerequisite for getting valuable results. The herbicide strategies were applied in a ploughing system and a mulching system in 19 environments (site×year) in Germany in 2008 and 2009. Earthworm expulsions were carried out in spring and autumn with 2204 samples in total.The earthworm population was determined by environment and tillage system rather than by herbicide strategies. The environments displayed the largest variability in earthworm abundance, ranging from 12 to 195individualsm−2, and a considerable variation in the occurrence of earthworm species. In spring, the deleterious impact of ploughing, with 80% lower mean earthworm abundance compared to the mulching system, was observed across all environments. During vegetation, the stronger increase in earthworm population in the ploughing system did not compensate for the initial differences. Regardless of intensity, the herbicide strategies were not accompanied by corresponding detrimental effects on earthworms between each other. In conclusion, the earthworm population was subjected to a multiplicity of influencing factors and the results markedly demonstrated for the first time the negligible effect of herbicide application intensity in sugar beet.

Pesticide environmental accounting: a decision-making tool estimating external costs of pesticides

In cost-benefit analyses of pesticide use an area-based measure of both costs and benefits is needed for spatial analysis of net benefits. The pesticide environmental accounting (PEA) tool provides a monetary estimate of environmental and health impacts per hectare-application of pesticide (Leach and Mumford 2008). The model combines the Environmental Impact Quotient method (rating human health and eco-toxicological behaviour of specific pesticides) with absolute estimates of external pesticide costs in the UK, USA and Germany. The model converts external costs of a pesticide to other countries using GDP per capita and % GDP from agriculture. For many countries, resources are not available for intensive assessments of external pesticide costs. Economic and policy applications include rationalising pesticide choice, estimating impacts of pesticide reduction policies or calculating benefits from technologies that replace pesticides [sterile insect technique (SIT) or biological pesticides such as Metarhizium]. PEA is a logical integration of diverse data and approaches. The assumptions provide transparency and consistency but at the cost of specificity and precision, a reasonable trade-off for a method that provides both comparative estimates of pesticide impacts and area-based assessments of absolute impacts. The method has been applied to cost-benefit analyses of SIT in fruit flies (two species) and pesticide choice in Desert Locust (DL) campaigns in Africa. An example of external cost calculations for sugar beet herbicides in Europe is presented. There are also planned uses in public health mosquito control.

Identifying key components of weed beet management using sensitivity analyses of the GeneSys-Beet model in GM sugar beet

Genetically-modified (GM) sugar beet varieties tolerant to non-selective herbicides would be useful for managing weed beet, an annual form of Beta vulgaris impossible to eliminate with herbicides in sugar beet. However, it is highly probable that the herbicide-tolerance transgene would be transmitted to the weed through pollen flow. It is therefore essential to study how weed beet. particularly Herbicide-Tolerant (HT) populations, develop in cropping systems and how to optimise crop succession and management for controlling these weeds. As multiple interactions and long-term effects make field experiments impractical, we carried out a simulation study with a deterministic and mechanistic model, GeneSys-Beet, which quantifies weed beet dynamics and gene flow in cropping systems with interactions with climate, soil structure and hydro-thermal conditions. The sensitivity analysis consisted of 250 000 random combinations of input variables to rank cropping system components according to their effect on both total and GM weed beet infestations. Frequency of sugar beet crops, crop succession, manual and mechanical weeding and tillage were identified as the most important variables. Several cultivation techniques must be combined to efficiently control weed beet. Our recommendations are complex, but a delayed return of sugar beet in the rotation. Harvest should be followed as soon as possible by a shallow tilling; tillage should always be as shallow and as early as possible, except before sugar beet where mouldboard ploughing is advisable. If possible, sowing dates should be delayed. Sugar beet should be weeded mechanically and/or manually, aiming at late and efficient, rather than early or frequent operations. Herbicides should be applied whenever possible and target all weed beet stages and genotypes. Set-aside must be cut as frequently and as late as possible.

Adsorption of sugar beet herbicides to Finnish soils

Three sugar beet herbicides, ethofumesate, phenmedipham and metamitron, are currently used on conventional sugar beet cultivation, while new varieties of herbicide resistant (HR) sugar beet, tolerant of glyphosate or glufosinate-ammonium, are under field testing in Finland. Little knowledge has so far been available on the adsorption of these herbicides to Finnish soils. The adsorption of these five herbicides was studied using the batch equilibrium method in 21 soil samples collected from different depths. Soil properties like organic carbon content, texture, pH and partly the phosphorus and oxide content of the soils were tested against the adsorption coefficients of the herbicides. In general, the herbicides studied could be arranged according to their adsorption coefficients as follows: glyphosate > phenmedipham > ethofumesate ≈ glufosinate-ammonium > metamitron, metamitron meaning the highest risk of leaching. None of the measured soil parameters could alone explain the adsorption mechanism of these five herbicides. The results can be used in model assessments of risk for leaching to ground water resulting from weed control of sugar beet in Finland.

Characterization of Spatial Variability Structure in Three Separate Field Trials on Pesticide Dissipation

Experiments were carried out on three Italian farms to assess the degree of spatial variation of pesticide field concentration during treatment and during dissipation trials. Test pesticides were chloridazon and metamitron (both sugar-beet herbicides) applied as a tank mix. The classical statistical technique and geostatistics were used to summarize and evaluate variable spatial data. The results show that the actual values of pesticide concentration for application rate and initial concentration in all three areas are lower than expected, thus indicating that under field conditions only a part of the pesticide reaches the soil during the distribution. The actual values for both herbicides in all three areas expressed as percentage of expected values ranged from 44·1% to 64·2% for application rate and from 40·5% to 99·5% for initial concentration. The coefficient of variation was similar for both pesticides and ranged from 23·8 to 74·1 for application rate, 24·1 and 58·8 for initial concentration and 11·1 and 110·0 for dissipation half-lives. The high variability in application rate and initial concentration could be ascribed to an uneven herbicide distribution, and in dissipation studies to variation in half-lives for the rate of herbicide loss from soil in different parts of the field. Geostatistic analysis indicated little spatial correlation, probably because the sampling sites were widely spaced on the field. In all cases, the data were not sufficient to estimate the range of influence, probably because of the size of the experimental fields and the sampling strategy. © 1997 SCI.

Characterization of Spatial Variability Structure in Three Separate Field Trials on Pesticide Dissipation

Experiments were carried out on three Italian farms to assess the degree of spatial variation of pesticide field concentration during treatment and during dissipation trials. Test pesticides were chloridazon and metamitron (both sugar-beet herbicides) applied as a tank mix. The classical statistical technique and geostatistics were used to summarize and evaluate variable spatial data. The results show that the actual values of pesticide concentration for application rate and initial concentration in all three areas are lower than expected, thus indicating that under field conditions only a part of the pesticide reaches the soil during the distribution. The actual values for both herbicides in all three areas expressed as percentage of expected values ranged from 44·1% to 64·2% for application rate and from 40·5% to 99·5% for initial concentration. The coefficient of variation was similar for both pesticides and ranged from 23·8 to 74·1 for application rate, 24·1 and 58·8 for initial concentration and 11·1 and 110·0 for dissipation half-lives. The high variability in application rate and initial concentration could be ascribed to an uneven herbicide distribution, and in dissipation studies to variation in half-lives for the rate of herbicide loss from soil in different parts of the field. Geostatistic analysis indicated little spatial correlation, probably because the sampling sites were widely spaced on the field. In all cases, the data were not sufficient to estimate the range of influence, probably because of the size of the experimental fields and the sampling strategy. © 1997 SCI.

Determination of sugarbeet herbicides in soil samples by hplc

Determination of sugarbeet herbicides such as chloridazon, metamitron and phenmedipham in soil samples is described. After extraction with acetone, pesticides were determined by HPLC on an RP-18 column using methanol/water as mobile phase. Average recoveries were 82% for chloridazon, 93% for metamitron and 77% for phenmedipham. Quantification limits were 3·5 μg kg−1 for chloridazon, 6·3 μg kg−1 for metamitron and 3·6 μg kg−1 for phenmedipham.

Velvetleaf (Abutilon theophrasti) Control in Sugarbeet (Beta vulgaris)

Velvetleaf control in sugarbeet by clomazone and commercially available sugarbeet herbicides was investigated in greenhouse and field studies. In greenhouse studies, clomazone at 0.07 and 0.04 kg ai ha-1controlled 97 and 69% of velvetleaf, respectively, with little visible sugarbeet injury. Adding clomazone to pyrazon, TCA, ethofumesate, pyrazon plus TCA, or TCA plus ethofumesate increased velvetleaf control but increased visible sugarbeet injury. In field studies, clomazone at 0.07 kg ha-1did not enhance sugarbeet injury. However, velvetleaf was not controlled by clomazone alone or clomazone plus pyrazon, ethofumesate, combinations of pyrazon plus TCA, pyrazon plus ethofumesate, or pyrazon plus TCA plus ethofumesate. Cycloate preplant incorporated plus pyrazon preemergence followed by postemergence herbicides controlled velvetleaf in all 3 yr of research. Postemergence herbicides increased velvetleaf control from soil-applied herbicides in 1987 and 1988.

Potential for Weeds to Develop Resistance to Sugar Beet Herbicides in North America

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Evaluation of pre-emergence and post-emergence herbicides in fodder beet and sugar beet in Canterbury

Abstract Fodder beet and sugar beet crops grown in Canterbury were treated with pre-emergence and post-emergence herbicides alone or in sequence during the 1980–81 and 1981–82 seasons. High levels of weed control and maximum yields of beet roots were achieved with sequences of pre-and post-emergence herbicides, whereas pre-emergence or post-emergence herbicides alone failed to give the necessary level of weed control for maximum yields.

Sugar beet herbicides and soil nitrification

The effects of phenmedipham, propham, carbetamide, lenacil and benzthiazuron on soil nitrification was studied in the laboratory using a perfusion technique. The nitrification process was markedly retarded at a phenmedipham concentration of 50–500μg g −1 soil, so that 55–150 days were required for complete oxidation of supplied NH + 4-N as compared with 33 days for the untreated control. Phenmedipham caused a reduction in both the maximum population and the proliferation rate of nitrifying organisms, as evaluated from kinetic parameters. These inhibitory effects showed a low persistance probably due to herbicide breakdown. The effects of 100 μg g −1 soil of propham, carbetamide, lenacil or benzthiazuron on the nitrification process was very weak, although the kinetics of the nitrification process was affected by all these herbicides.

Cultivar ✕ Herbicide Interaction in Sugarbeet1

Eight commercial sugarbeet (Beta vulgaris L.) cultivars consisting of both diploid 2N = 2X = 18 and triploid 2N = 3X = 27 hybrids were studied for 2 years for their response to three herbicide regimes. The specific registered sugarbeet herbicides consisted of preplanting applications of 1) cycloate (S‐ethyl‐N‐ethylthiocyclohexanecarbamate) (3.4 kg/ha), 2) ethofumesate [(± &gt;2‐ethoxy‐2,3‐dihydro‐3,3‐dimethyl‐ 5‐benzofuranyl methanesulfonate] (2.2 kg/ha), and 3) a mixture of ethofumesate (2.2 kg/ha) + diclofop |2‐{4‐{2,4‐dichlorophenoxy) phenoxy] propanoic acidsj (1.7 kg/ha), each followed by a post‐emergence mixture of desmedipham [ethyl m‐hydroxycarbanilate carbanilate (ester)] and phenmedipham (methyl m‐hydroxycarbanilate m‐methylcarbanilate) both applied at 0.6 kg/ha. A fourth treatment regime was that of no herbicide application. The six characters examined were 45‐day plant dry weight, harvest root weight, foliar suppression, stand count, sucrose, and purity. Differential herbicide and cultivar response was evidenced by significant year ✕ herbicide, year ✕ cultivar, and herbicide ✕ cultivar interactions for several of the six characters analyzed. Although a significant second order interaction was detected for foliar suppression, none of the yield components (root weight, sucrose, purity) exhibited significant second order interactions. Certain cultivars were suppressed significantly less than others at 45 days and recovered the most by harvest time. Under favorable soil moisture and temperature conditions, the eight commercial cultivars showed reductions in total 45‐day plant weight of 39 to 55% of their nontreated equivalent controls. In both years, early season suppression was mostly, but not entirely, overcome by harvest. Reductions averaged about 5%.