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Despite several decades of modern weed control practices, weeds continue to be a constant threat to agricultural productivity. Herbicide-resistant weeds and weed population shifts continue to generate new challenges for agriculture. Because of weed community complexity, integrated approaches to weed management may help reduce economic effects and improve weed control practices. Integrated weed management emphasizes the combination of management techniques and scientific knowledge in a manner that considers the causes of weed problems rather than reacts to existing weed populations. The goal of weed management is the integration of the best options and tools to make cropping systems unfavorable for weeds and to minimize the effect of weeds that survive. No single practice should be considered as more than a portion of an integrated weed management strategy. The best approach may be to integrate cropping system design and weed control strategies into a comprehensive system that is environmentally and economically viable. Management decisions must also be made on a site- and time-specific basis. Considering weeds in a broader ecological and management context may lead to the use of a wider range of cultural and management practices to regulate weed communities and prevent the buildup of adapted species. This will help producers manage herbicides and other inputs in a manner that preserves their effectiveness and move weed scientists toward the development of more diverse and integrated approaches to weed management.
Data containing many variables are often collected in weed science research, but until recently few weed scientists have used multivariate statistical methods to examine such data. Multivariate analysis can be used for both descriptive and predictive modeling. This paper provides an intuitive geometric introduction to the more commonly used and relevant multivariate methods in weed science research, including ordination, discriminant analysis, and canonical analysis. These methods are illustrated using a simple artificial data set consisting of abundance measures of six weed species and two soil variables over 12 sample plots.
Studies were conducted to evaluate absorption, translocation, and metabolism of 14C-CGA 362622 when foliar applied to cotton, peanut, jimsonweed, and sicklepod. Differential metabolism is the basis for tolerance in cotton and jimsonweed. In addition, cotton absorbs less herbicide compared with the other three species, thus aiding in tolerance. Only jimsonweed translocated appreciable herbicide (25%) out of treated leaves and acropetally to the meristematic tissue where the herbicide was quickly metabolized. No plant species translocated over 2% of applied radioactivity below the treated leaves. Most of the metabolites formed by the four species were more polar than CGA 362622 and averaged 51, 48, 30, and 25% of the radioactivity detected in the treated leaves of cotton, jimsonweed, peanut, and sicklepod, respectively. The half-life of CGA 362622 was estimated to be 0.8, 1.9, 4, and 6 d in treated leaves of cotton, jimsonweed, sicklepod, and peanut, respectively.
Nomenclature: CGA 362622, N-[(4,6-dimethoxy-2-pyrimidinyl)carbamoyl]-3-(2,2,2-trifluoroethoxy)-pyridin-2-sulfonamide sodium salt; jimsonweed, Datura stramonium L. DATST; sicklepod, Senna obtusifolia (L.) Irwin and Barnaby CASOB; cotton, Gossypium hirsutum L. ‘Stoneville 474’; peanut, Arachis hypogaea L. ‘NC 10C’.
A population of giant ragweed not controlled by cloransulam was identified near Seymour, IN, during the first year of that herbicide's commercialization in 1998. Results from acetolactate synthase (ALS) activity assays performed by Dow AgroSciences showed that resistance was caused by an altered ALS. Studies were conducted to define more precisely the molecular basis of resistance and to determine cross-resistance to other ALS-inhibiting herbicides. Sixteen greenhouse-grown giant ragweed plants from the Seymour population were tested individually with postemergence (POST) applications of cloransulam, imazethapyr, or chlorimuron, or by using a nondestructive leaf disk assay to determine resistant or sensitive herbicide responses. All plants identified from the Seymour population as resistant to cloransulam were cross-resistant to imazethapyr and chlorimuron. Two DNA fragments, totaling 804 nucleotide base pairs, within ALS were sequenced from each of the 16 plants. Sequence data, combined with phenotypic data, showed that a tryptophan to leucine substitution at amino acid position 574 of ALS (based on numbering of the Arabidopsis ALS) was responsible for ALS-inhibitor resistance. Among 11 resistant and 5 sensitive giant ragweed plants analyzed from the Seymour population, at least 15 different ALS alleles were identified. Of these 15 alleles, two alleles, at an average frequency of 0.25, contained a leucine at position 574 and conferred resistance. The 13 alleles that conferred susceptibility to ALS-inhibiting herbicides occurred at an average frequency of 0.04.
As a follow-up to greenhouse studies, acetolactate synthase (ALS) (EC 22.214.171.124) was extracted from one imidazolinone (IMI)-susceptible (S) and three IMI-resistant (R1, R2, and R3) smooth pigweed populations, and activity was assayed in the presence of imazethapyr, chlorimuron, thifensulfuron, and pyrithiobac. ALS inhibitor concentrations, required to reduce enzyme activity by a specified percentage compared with the untreated control (Ip), were determined for each herbicide using regression analysis, and resistance ratios were calculated from these values. An I50 value of >35 μM imazethapyr was calculated for all R populations compared with a value of 3.4 μM for the S population. With chlorimuron, thifensulfuron, and pyrithiobac data sets, pairwise comparisons of regression coefficients were used to determine significant differences between regression lines. Using this technique, it was established that ALS from R3 was more sensitive than ALS from S to inhibition by chlorimuron and thifensulfuron. Also, ALS from R2 and R3 displayed increased sensitivity to pyrithiobac compared with ALS extracted from the S population. We have confirmed enzyme-level resistance to imazethapyr in all R populations and have documented negative cross-resistance in some R populations to ALS inhibitors other than imazethapyr.
Wild oat continues to reduce spring wheat yields and profits despite the wide spread use of herbicides. Further reductions in the occurrence of wild oat could be achieved with the development of competitive cropping systems. Field studies were conducted to investigate the effects of wheat seed size and seeding rate on wild oat demographic processes under a range of wild oat densities. Spring wheat competitiveness increased as seed size and seeding rate increased, significantly reducing wild oat biomass and seed production. Averaged across all other factors, spring wheat plants derived from large seed reduced wild oat panicle numbers 15% and biomass and seed production 25% compared with small seed. Increasing spring wheat seeding rate from 175 to 280 plants m−2 reduced the number of panicles 10% and wild oat biomass and seed production 20%. The combined effect of large seed plus increased seeding rate reduced wild oat biomass and seed production 45%. Results demonstrate that the use of large seed size and increased seeding rates can improve wheat competitiveness and provide an effective means to reduce wild oat biomass and seed production.
Nomenclature: Wild oat, Avena fatua L. AVEFA; spring wheat, Triticum aestivum L. ‘McNeal’.
Two separate field experiments were conducted to quantify the degree of plant-to-plant outcrossing and pollen-mediated gene flow (PMGF) in wild oat. The purpose of the study was to determine the extent to which pollen movement could contribute to the spread of herbicide resistance in this species. In both experiments, an acetyl-CoA carboxylase inhibitor–resistant (R) wild oat genotype (UM1) was used as the pollen donor and a susceptible (S) genotype (UM5) was used as the pollen receptor. Hybrid progeny resulting from a cross between UM1 and UM5 were identified using the herbicide resistance trait as a marker. In the plant-to-plant outcrossing experiment, single UM5 plants were closely surrounded by 20 homozygous R UM1 plants in hills. By screening seed from the S parent for resistance, outcrossing was determined to range from 0 to 12.3%, with a mean of 5.2% over 10 hills. In the PMGF experiment, single homozygous R UM1 plants were surrounded by UM5 plants arranged in a hexagonal pattern at low and high densities (total of 19 and 37 wild oat plants m−2), growing within spring wheat and flax crops. In the wheat crop, mean wild oat outcrossing was 0.08 and 0.05% at low and high densities, respectively. In the less competitive flax, corresponding outcrossing values were 0.07 and 0.16% at low and high densities, respectively. Distance from the pollen source was a significant factor only for the high-density planting arrangement in flax. Up to 77 R hybrid seeds were recovered from 6 m2 in the PMGF experiment, indicating that PMGF contributes to the evolution of resistance in wild oat populations. However, the contribution of pollen movement to resistance evolution and the spread of resistance in wild oat populations would be relatively small when compared with R seed production and dispersal from a resistant plant.
EDITOR'S NOTE: This manuscript was reviewed by six colleagues whose recommendations varied widely. Lack of repetition was a major concern. The authors address the problem in the last paragraph of the results section. Factors favoring publication included the worldwide importance of wild oats, the minimal data on gene flow in the species, and the fact that the results are consistent with those of other studies cited in this manuscript. The points raised by reviewers who did not favor publication, especially the role of the environment in pollen production and viability, are acknowledged.
R. L. Zimdahl, Editor
Nomenclature: Sethoxydim; wild oat, Avena fatua L. AVEFA; flax, Linum usitatissimum L. ‘Norlin’; spring wheat, Triticum aestivum L. ‘Roblin’.
Studies were conducted to determine the effect of interference between ladysthumb and cotton on plant growth and productivity. Ladysthumb remained shorter than cotton until at least 70 d after cotton planting. However, ladysthumb grew over twice as tall as cotton and, depending on plant density, produced between 179 and 681 g dry biomass per plant by cotton harvest. Ladysthumb biomass per plant was not affected by weed density when grown with cotton. When grown alone, ladysthumb produced over 2,000 g dry biomass per plant, which was over four times greater than biomass produced by plants grown with cotton. Cotton lint yield decreased between 0.7 and 0.9 kg ha−1 with each gram increase in weed dry biomass per meter of the row. The relationship between ladysthumb density and cotton percent yield loss was described by the rectangular hyperbola model with the asymptote (coefficient a) constrained to 100% maximum yield loss. The estimated coefficient i (yield loss per unit density as density approaches zero) was 35 ± 5 and 14 ± 2 in 1998 and 2000, respectively. Ladysthumb seed production was also described by the hyperbolic function. Estimated seed production at 1 plant m−1 of cotton row was 33,000 and 47,000 seed m−2 in 1998 and 2000, respectively.
Nomenclature: Ladysthumb, Polygonum persicaria var. persicaria L. POLPE; cotton, Gossypium hirsutum L. ‘BXN 47’.
Red rice is a major weed in rice production in the southern United States. Red rice and rice intercross because they are the same species. Our objectives were to determine the genetic diversity represented by accessions of red rice and to identify DNA markers that might be useful in identifying hybrids between red and cultivated rice. Red rice accessions were collected from Arkansas and other rice-producing states. Seventy-nine red rice accessions, 10 known or putative hybrid derivatives of red rice and cultivated rice (RC hybrids), and seven rice cultivars were analyzed using microsatellite DNA markers developed for cultivated rice. Microsatellite markers differentiated awned and awnless red rice accessions, six of the seven rice cultivars, and all 10 RC hybrids tested. Thus, these markers were useful in identifying red rice types and RC hybrids.
Nomenclature: Red rice, Oryza sativa L. ORYSA; rice, Oryza sativa L.
A field experiment was conducted between 1988 and 1993 to determine the number of wild-proso millet seed that could be returned to the soil without increasing future soil seed bank populations. The first seed bank (1988) was 15,300 seed m−2 and ranged from 14,000 to 21,000 seed m−2, which represented a high seed population for the area. Seed rain treatments of 0, 3, 6, 12, 24, and 48% of the 1988 soil seed bank were returned each fall. By 1993, more than 90% of the original millet seed bank had been depleted for all treatments. It was estimated that 77% of the seed rain and 68% of the spring seed bank were lost each year. As a result, wild-proso millet must produce approximately three times the seed in the soil to maintain a constant seed bank population.
Nomenclature: Wild-proso millet, Panicum miliaceum L. PANMI; corn, Zea mays L.; soybean, Glycine max (L) Merr.
Wild radish is a prevalent annual weed throughout the cropping regions of southern Australia. Field experiments were conducted at Wagga Wagga, New South Wales, in 1998 and 1999 to determine the effect of various densities and emergence times of wild radish on yield and quality of canola and on wild radish seed production. As few as 4 wild radish m−2 emerging with canola reduced canola yield 9 to 11%, whereas 64 wild radish m−2 reduced canola yield 77 to 91%. Wild radish interference in canola was greatly affected by its time of emergence relative to canola. At 64 wild radish m−2, canola yield was reduced 77, 54, 33, and 19% in 1998 and 91, 65, 56, and 19% in 1999 when wild radish emerged 0, 2, 4, and 7 wk after canola, respectively. Wild radish that emerged 10 wk after canola did not reduce canola yield. Maximum wild radish seed production ranged from 24,183 to 32,167 seed m−2 when they emerged with canola at high densities. Wild radish that emerged later than canola produced much less seed, but some seed production still occurred in one of the 2 yr when it emerged as late as 10 wk after canola. Wild radish did not directly reduce canola quality in either year, but if wild radish seed were not separated from canola seed, the amount of erucic acid and glucosinolates was increased above marketable levels in some cases. The results of this study will be used to advise growers on wild radish control in canola and will aid the development of a multiyear management strategy for this troublesome weed in annual cropping systems.
Nomenclature: Wild radish, Raphanus raphanistrum L. RAPRA; canola, Brassica napus L. ‘Oscar’.
Studies were conducted to determine the effect of interference between Pennsylvania smartweed and cotton on plant growth and productivity. Pennsylvania smartweed remained shorter than cotton until at least 80 d after cotton planting. However, Pennsylvania smartweed produced considerable dry biomass by cotton harvest. Pennsylvania smartweed biomass per plant was not affected by weed density when grown with cotton. When grown alone, Pennsylvania smartweed produced 1,640 and 2,060 g dry biomass plant−1 depending on the year. This biomass was over four times greater than the biomass produced by plants grown with cotton. Cotton lint yield decreased between 1.3 and 1.1 kg ha−1 with each gram increase in weed dry biomass per meter of row. The relationship between Pennsylvania smartweed density and cotton percent yield loss was described by the hyperbolic function. The estimated coefficients a (maximum yield loss as density approaches infinity) and i (yield loss per unit density as density approaches zero) were 102 ± 23 and 51 ± 12, respectively, in 1998 and 53 ± 1 and 98 ± 5, respectively, in 2000. Pennsylvania smartweed achene production was also described by the hyperbolic function. Estimated achene production at 1 plant m−1 cotton row was 18,000 and 26,000 achenes m−2 in 1998 and 2000, respectively.
Nomenclature: Pennsylvania smartweed, Polygonum pensylvanicum var. laevigatum Fern. POLPY; cotton, Gossypium hirsutum L. ‘Stoneville BXN 47’.
Field studies were conducted at two North Carolina locations to determine the effect of interference between pale smartweed and cotton on plant growth and productivity. Pale smartweed remained shorter than cotton until at least 70 d after cotton planting. However, pale smartweed grew over twice as tall as cotton and produced considerable dry biomass by cotton harvest. Pale smartweed biomass per plant was not affected by weed density up to 3.5 plants m−1 of row when grown with cotton. Cotton competition reduced pale smartweed dry biomass per plant at least 400%. The relationship between pale smartweed and cotton percent yield loss was described by the rectangular hyperbola model with the asymptote (coefficient a) constrained to 100% maximum yield loss. The estimated coefficient i (yield loss per unit density as density approaches zero) was 29 ± 4 and 23 ± 4 in 1998 and 2000, respectively. Pale smartweed achene production was also described by the hyperbolic function. Estimated achene production of smartweed at 1 plant m−1 cotton row was 63,000 and 25,000 achenes m−2 in 1998 and 2000, respectively.
Nomenclature: Pale smartweed, Polygonum lapathifolium var. lapathifolium L. POLPE; cotton, Gossypium hirsutum L. ‘Stoneville BXN 47’.
Knowledge of how reduction in the rate of herbicide application or rotation of their mode of action influences weed growth will provide insight into how successful these practices will be in an integrated weed management program. Field experiments were conducted in 1996 and 1997 to quantify velvetleaf growth response to three postemergence herbicides, each with a different mode of action. A monoculture of velvetleaf was treated with halosulfuron, dicamba, and flumiclorac at 0, 0.10, 0.25, 0.50, 0.75, and 1.0 × the labeled rate for weed control in corn. Percent plant mortality increased with rate of application; the greatest mortality occurred in flumiclorac treatments in 1996 and in halosulfuron and flumiclorac treatments in 1997. Growth rate temporarily decreased as application rate increased. Maximum height decreased as rate of application increased, with the dicamba treatment resulting in the greatest (27%) reduction. Early-season leaf area index decreased with increasing rate of application, the greatest reduction occurring with halosulfuron (1997) and flumiclorac (1996 and 1997) treatments. The number of leaves produced per plant was temporarily reduced by all treatments, but treatment with dicamba later resulted in larger numbers of small leaves. The number of velvetleaf seed capsules produced per surviving plant was not reduced by any treatment, but the number of capsules per square meter was reduced by the 0.5 × rate of flumiclorac (1996) and the 0.5- and 1.0 × rates of halosulfuron (1997). Research is needed to evaluate whether the temporary suspension of velvetleaf growth after herbicide treatment is sufficient to prohibit crop yield reduction and velvetleaf capsule production.
Field experiments were conducted in 1996 and 1997 to evaluate the effect of EPTC (S-ethyl dipropyl carbamothioate) plus ethalfluralin at 2.4 plus 0.83 kg ai ha−1, rotary hoeing, in-row cultivation, rotary hoeing plus in-row cultivation, and dry bean canopy on weed seedling emergence. Cumulative weed emergence in 1996 and 1997 was similar in cropped and noncropped areas. Herbicides were more effective than mechanical cultivation in reducing weed emergence 91% in 1996 and 88% in 1997. Weed emergence was similar in both rotary hoed area and cultivated area in 1996 but weed emergence was 44% lower in rotary hoed plots than in cultivated plots in 1997. The Gompertz equation did not adequately predict weed seedling emergence in the untreated control and with in-row cultivation in 1996. Initial weed seedling emergence was observed at about 120 growing degree-days with 3 to 9% cumulative emergence among treatments. In 1997, the Gompertz equation adequately described weed seedling emergence in plots with or without disturbed soil. Weed emergence was first observed at 80 growing degree-days with 6 to 16% cumulative emergence among treatments. Predicted percent weed emergence closely approximated observed emergence in 1996 and 1997. Rotary hoeing plus in-row cultivation reduced maximum percent emergence rate 37% on an average. The greater maximum percent emergence rate obtained with in-row cultivation suggests that this treatment increased weed seedling emergence in 1997. On average, weed seedling emergence in the untreated check was lower in cropped areas than in noncropped areas, implying a competitive effect by the dry bean crop. Although weed seedling emergence occurred throughout the growing season, more weed seedlings emerged in June and early July than in late July and August.
Nomenclature: EPTC (S-ethyl dipropyl carbamothioate); ethalfluralin; redroot pigweed, Amaranthus retroflexus L. AMARE; common lambsquarters, Chenopodium album L. CHEAL; hairy nightshade, Solanum sarrachoides Sendt. SOLSA; wild proso millet, Panicum miliaceum L. PANMI; dry bean, Phaseolus vulgaris cv; Great Northern ‘Beryl’.
Experiments were conducted in Lewiston, NC, in 1999 and 2000 and Rocky Mount, NC, in 1999 to evaluate weed management systems in strip- and conventional-tillage peanut. The peanut cultivars grown were ‘NC 10C’, ‘NC 12C’, and ‘NC 7’, respectively. Weed management systems consisted of different combinations of preemergence (PRE) herbicides including diclosulam and flumioxazin plus commercial postemergence (POST) herbicide systems. Dimethenamid plus diclosulam or flumioxazin PRE controlled common lambsquarters, eclipta, and prickly sida at least 91%. Diclosulam and flumioxazin provided variable control of three Ipomoea species (59 to 91%) and bentazon plus acifluorfen POST provided > 90% control. Only diclosulam systems controlled yellow nutsedge 90% late season. Annual grass control required clethodim late POST, regardless of tillage system. Dimethenamid plus diclosulam or flumioxazin PRE produced equivalent yields and net returns with no significant differences between the two PRE options. Both systems produced higher yields and net returns than dimethenamid regardless of the POST herbicide option. The tillage production system did not influence weed control of eight weeds, peanut yields, or net returns. The addition of diclosulam or flumioxazin to dimethenamid PRE improved weed control compared with dimethenamid PRE alone.
Nomenclature: Acifluorfen; bentazon; clethodim; diclosulam; dimethenamid; flumioxazin; common lambsquarters, Chenopodium album L. CHEAL; eclipta, Eclipta prostrata L. ECLAL; prickly sida, Sida spinosa L. SIDSP; yellow nutsedge, Cyperus esculentus L. CYPES; peanut, ‘NC-7’, ‘NC-10’, ‘NC-12’, Arachis hypogaea L.
The effects of MT-101 and its herbicidally active form, NOP, on the germination and seedling growth of hemp sesbania and rice were investigated. MT-101 decreased the germination of hemp sesbania by 57 and 90% at 0.05 and 0.5 mM, respectively, 1 d after treatment (DAT) in petri dishes. The germination, however, recovered such that there was no significant difference between treatments 4 to 6 DAT. NOP completely inhibited the germination of hemp sesbania at both 0.05 and 0.5 mM 1 DAT. However, germination also similarly recovered, and there was no difference between treatments 4 to 6 DAT. Neither MT-101 nor NOP decreased the germination of rice 3 to 6 DAT. In greenhouse trials preemergence (PRE) application of MT-101 at 2.25 kg ai ha−1 decreased the density (number of plants pot−1), plant height, and dry weight of hemp sesbania by 85, 67, and 91%, respectively. When applied postemergence (POST), MT-101 at 2.25 kg ha−1 decreased the density, plant height, and dry weight by a maximum of 58, 61, and 82%, respectively, indicating that MT-101 may have greater activity when applied PRE. NOP had greater activity than MT-101 on hemp sesbania. NOP at 2.25 kg ai ha−1 decreased the density, plant height, and dry weight of hemp sesbania 99, 78, and 97%, respectively, with PRE application. A POST application of NOP at 2.25 kg ha−1 decreased the dry weight of hemp sesbania 91 to 94%. A PRE application of NOP at 2.25 kg ha−1 decreased the dry weight of rice by 58%. Rice was not affected by POST applications of MT-101 but was affected slightly by NOP. These results suggest that MT-101 is a possible weed control agent in rice.
Nomenclature: MT-101, (naproanilide—common name approved by the Japanese Ministry for Agriculture, Forestry and Fisheries), 2-(2-naphthyloxy)propionanilide; NOP, 2-(2-naphthyloxy) propionic acid; hemp sesbania, Sesbania exaltata (Raf.) Rydb. ex A. W. Hill SEBEX; rice, Oryza sativa L. ‘Lemont’; cotton, Gossypium hirsutum L. ‘Deltapine 5415’.
Striga hermonthica reduces cereal yields in large areas of sub-Saharan Africa. Recent research has shown that transplanting maize seedlings that are more than 15 d old reduced Striga emergence and improved crop yields. Field experiments were conducted in 1998 and 1999 to determine whether maize varieties with different maturity periods and susceptibility to Striga parasitism respond similarly to transplanting. There was a considerable difference in Striga emergence between varieties in direct-seeded maize, but transplanting clearly reduced Striga emergence for all varieties. Transplanting of maize in plastic tubes gave the best Striga control until 8 wk after transplanting, whereas transplants from nurseries provided better season-long control. Transplanting improved grain yields 50 to 100% compared with direct seeding for three of the four varieties tested. Only the early-maturing variety ‘Morogoro’ had lower yields with transplanting than with direct seeding, indicating that transplanting caused more stress on the plants than was alleviated by the lower Striga infestation. The two varieties (‘Pioneer 3251’ and ‘H622’) most susceptible to Striga parasitism profited the most from transplanting, and the concomitant reduction in Striga induced stresses. Increases in productivity because of transplanting were associated with increases in biomass or harvest index. Transplanting of different maize varieties under rain-fed conditions has proven to be a biologically efficient method to improve maize yield and reduce Striga infestation within one season.
Nomenclature:Striga hermonthica (Del.) Benth; maize (corn), Zea mays L.
Growth chamber and field experiments were conducted to assess the potential of Pseudomonas syringae pv. tagetis (Pst) as a biocontrol agent for Canada thistle. Silwet L-77, an organosilicone surfactant, was required to facilitate Pst penetration into Canada thistle leaves. Growth chamber experiments indicated that maximum Pst populations inside leaves were obtained with a Silwet L-77 concentration of 0.3% (v/v) or greater. High Pst populations (109 colony-forming units [cfu] per gram fresh weight) were found in leaves 48 h after treatment with 108 or 109 cfu ml−1 Pst plus Silwet L-77 (0.3%, v/v). In growth chamber experiments, foliar application of Pst (109 cfu ml−1) plus Silwet L-77 (0.3%, v/v) on 4- to 5-wk-old Canada thistle reduced shoot dry weight by 52% (measured 14 d after treatment) and chlorophyll content of emerging leaves by 92% (measured 10 d after treatment). In field trials conducted in 1999 and 2000, Pst (109 cfu ml−1) plus Silwet L-77 (0.3%, v/v) were applied at 700 L ha−1, and the method of application (paint gun, backpack sprayer, boom) and the number of applications (one or two separated by 14 d) were examined. Averaged over 2 yr, two applications with a backpack sprayer resulted in 67% disease incidence (apical chlorosis) of treated plants measured 4 wk after the initial treatment (WAIT). At the time of flower bud formation (8 WAIT), there was little or no disease incidence, 31% reduction in plant height, 81% reduction in number of flower buds, and 20% reduction in shoot survival during 1999 but no effect on survival in 2000.
Nomenclature: Canada thistle, Cirsium arvense (L.) Scop. CIRAR; soybean, Glycine max L. ‘Lambert’, ‘Kato’.
Clomazone dissipation was examined in four soils in field experiments. Field half-lives were 6 to 59 d (average of four field sites was 35 d) for ferrosol (clay loam), kurosol (loamy sand), sodosol (silt loam), and vertosol (light clay). The Hoerl equation provided a better fit to the measured field concentration at all four sites than did a first-order equation. The order of clomazone dissipation rate was ferrosol > sodosol > kurosol > vertosol. Clomazone desorption varied with soil type, with apparent Kd values of 3.6, 1.7, 1.8, and 2.4 for ferrosol, sodosol, kurosol, and vertosol, respectively. Clomazone residues became more strongly sorbed with time, as indicated by desorption hysteresis, but detectable concentrations were present in all soils 1 yr after application. The data indicate that the potential for carryover injury to crops is greatest in the kurosol and least in the ferrosol.