2017
DOI: 10.1017/wsc.2017.9
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Effect of Seeding Rate on Dose Response of Wild Mustard (Sinapis arvensis) to Fluthiacet-Methyl

Abstract: Concern over the development of herbicide-resistant weeds has led to interest in integrated weed management systems that reduce selection pressure by utilizing mechanical and cultural weed control practices in addition to herbicides. Increasing crop seeding rate increases crop competitive ability and thus can enhance herbicide efficacy. However, it is unknown how increasing the seeding rate affects an herbicide’s efficacy. The objective of this study was to examine the interaction between increasing seeding ra… Show more

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Cited by 4 publications
(8 citation statements)
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“…The estimated doses required to achieve 50% visible control (ED 50 ), reduce kochia biomass by 50% (GR 50 ), or reduce kochia plant survival by 50% (LD 50 ) relative to the untreated control for each corresponding population and crop density, were extracted. The ED 50 and LD 50 values were regressed against wheat density using linear regression to assess the relationship between wheat density and phenotypic response to fluroxypyr treatment [19]. The relative differences (estimated ratios or R/S) in ED 50 , GR 50 , or LD 50 among the putative resistant populations (RockyView18 and Vulcan17) and the susceptible control [Lethbridge18(S)], and among the crop densities, were determined and compared using a t-test at α = 0.05 [40].…”
Section: Statistical Analysesmentioning
confidence: 99%
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“…The estimated doses required to achieve 50% visible control (ED 50 ), reduce kochia biomass by 50% (GR 50 ), or reduce kochia plant survival by 50% (LD 50 ) relative to the untreated control for each corresponding population and crop density, were extracted. The ED 50 and LD 50 values were regressed against wheat density using linear regression to assess the relationship between wheat density and phenotypic response to fluroxypyr treatment [19]. The relative differences (estimated ratios or R/S) in ED 50 , GR 50 , or LD 50 among the putative resistant populations (RockyView18 and Vulcan17) and the susceptible control [Lethbridge18(S)], and among the crop densities, were determined and compared using a t-test at α = 0.05 [40].…”
Section: Statistical Analysesmentioning
confidence: 99%
“…The kochia biomass DW data did not pass the lack-of-fit test for nonlinear regression (i.e., p < 0.05), although visualization of these data shows greater variability in response of RockyView18 to fluroxypyr rate compared with Lethbridge18(S), and a consistent biomass reduction in response to increasing wheat interference when fluroxypyr rates were inadequate for complete control (Figure S2). Augmented herbicide performance in response to increased crop seeding rate has been well documented in wheat and other crops [17][18][19]30]. For example, a range of post-emergence herbicides were more effective at reducing wild oat (Avena fatua L.) biomass and seed in the soil seedbank when wheat was seeded at 150 kg ha −1 compared with 75 kg ha −1 [18].…”
Section: Impact Of Crop Interferencementioning
confidence: 99%
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“…The importance of plant densities to crop productivity, particularly under weed interference, is well known in soybean (Arce et al 2009;Nice et al 2001) and other crops (Ball et al 1997;Fradgley et al 2017;O'Donovan et al 1999). The doseresponse work by Redlick et al (2017a) eloquently showed the trade-off between plant densities and herbicides for effective weed management and the importance of plant stand densities for improving herbicide efficacy and reducing the necessity for herbicides for weed management in lentil (Lens culinaris Medik.) (Redlick et al 2017b).…”
Section: Target Density Experimentsmentioning
confidence: 99%