Growth Analysis of Cotton in Competition with Velvetleaf (<i>Abutilon theophrasti</i>)

Ma, Xiaoyan; Yang, Jinyan; Wu, Hanwen; Jiang, Weili; Ma, Yu

doi:10.1614/wt-d-15-00050.1

Cited by 15 publications

(38 citation statements)

References 49 publications

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“…A doubling in weed density from five to 10 weeds m −2 increased weed biomass at 800 GDD by only 10% (Figure 2C) and the length of the dynamic CPWC by 3 to 6 d (Figure 4). This limited response to increasing weed density is consistent with the finding of Ma et al (2016), who observed yield reductions from as few as 0.25 velvetleaf plants m −2 , but recorded little change in cotton yield, with densities doubling from four to eight weeds m −2 .…”

Section: Plant Height and Biomasssupporting

confidence: 89%

“…There was little difference in weed height (Figure 2A) or weed biomass ( Figure 2C) with increasing weed density up until approximately 300 GDD. Later in the season, weed height and biomass per plant decreased as weed density increased, but the changes were far less than the changes in weed density, as was observed with velvetleaf in cotton (Ma et al 2016). At mid-season (800 GDD), weed biomass approximately doubled, from 850 g m −2 to 1,553 g m −2 , as weed density increased 50-fold ( Figure 2C).…”

Section: Plant Height and Biomassmentioning

confidence: 77%

“…Charles et al (1998) reported even lower densities of common cocklebur and large thornapple causing economic damage in cotton in Australia. As weed density increases, generally the level of competition also increases, further reducing crop yields (Buchanan and Burns 1971;Ma et al 2016;MacRae et al 2013). However, intraspecific competition between weed plants also increases with increasing weed density and there is often a concurrent decrease in weed biomass per plant, although at a slower rate than the increase in weed density (Ma et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…This failure to fully account for weed density and biomass in many previous studies may be one of the factors leading to the site and seasonal variability in the results of many of these competition experiments (Korres and Norsworthy 2015;Ma et al 2016). Other factors contributing to seasonal variability may include species differences and differences in weed emergence patterns (Robinson 1976a), environmental differences (Fast et al 2009), rainfall (Rogers et al 1976;Tingle et al 2003), the presence of plant diseases (Buchanan et al 1977), soil nutrition, and other soil constraints (Buchanan and McLaughlin 1975;Tursun et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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Determining the critical period for weed control in high-yielding cotton using common sunflower as a mimic weed

et al. 2019

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Field studies were conducted over six seasons to determine the critical period for weed control (CPWC) in high-yielding cotton, using common sunflower as a mimic weed. Common sunflower was planted with or after cotton emergence at densities of 1, 2, 5, 10, 20, and 50 plants m−2. Common sunflower was added and removed at approximately 0, 150, 300, 450, 600, 750, and 900 growing degree days (GDD) after planting. Season-long interference resulted in no harvestable cotton at densities of five or more common sunflower plants m−2. High levels of intraspecific and interspecific competition occurred at the highest weed densities, with increases in weed biomass and reductions in crop yield not proportional to the changes in weed density. Using a 5% yield-loss threshold, the CPWC extended from 43 to 615 GDD, and 20 to 1,512 GDD for one and 50 common sunflower plants m−2, respectively. These results highlight the high level of weed control required in high-yielding cotton to ensure crop losses do not exceed the cost of control.

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Section: Plant Height and Biomasssupporting

confidence: 89%

Section: Plant Height and Biomassmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Determining the critical period for weed control in high-yielding cotton using common sunflower as a mimic weed

et al. 2019

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“…The yield loss model that uses rectangular hyperbolic function has been incorporated into the R package drc that can be used for crop-weed interaction analysis as well as dose-response curves, which is its main function (Ritz et al, 2015). Ma et al (2016) used both the rectangular hyperbolic function and the two-parameter hyperbolic decay curve to relate weed density with cotton yield loss and yield, respectively. The hyperbolic decay curve was used to estimate the density of velvetleaf plants per square meter that would reduce cotton yield to 50% of weed-free control.…”

Section: Introductionmentioning

confidence: 99%

Influence of wild oat plant density on spring wheat yield

Ņečajeva¹,

Erdmane²,

Isoda-Krasovska³

et al. 2017

Zemdirbyste-Agriculture

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Wild oat (Avena fatua L.) is the most serious weed infesting cereal fields in Latvia. To predict possible yield loss at different wild oat densities field trials were established in four consecutive years, each year in a different spring wheat field in the southern part of Latvia. Growth dynamics and biomass of both crop and wild oat and grain yield were measured. Yield loss model developed by Cousens (1985) and exponential decay model were fitted to the data from each year. Grain yield and biomass of both spring wheat and wild oat significantly differed between the years. The average grain yield of spring wheat in all treatments was 4443.38-7127.02 kg ha -1 . The targeted wild oat density was 0, 1, 2, 4, 8, 16, 32, 100, 200 and 500 plants m -2 . The achieved density in the field trial reached from 0 to 332-466 plants m -2 . The emergence of wild oat seedlings lasted for 35 to 56 days after sowing, depending on the year. The initial hypothesis that low wild oat plant density may cause grain yield loss of spring wheat was supported by the results of the field trials. There was substantial variation in model parameters among the years of the trials, 5% yield loss was estimated to result from wild oat density ranging from 3 to 54 plants m -2 in different years. The variation of spring wheat yield loss and wild oat competitiveness might be explained by different meteorological conditions in the years 2013-2016 and different nutrient supply in the trial fields. Further research is necessary to find the most influential factors that determine yield loss caused by wild oat. The results are important to raise awareness of the harm caused by wild oat in cereals in the Baltic region.

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Changes in the herbicide sensitivity and competitive ability of Abutilon theophrasti over 28 years: Implications for hormesis and weed evolution

Ethridge

Chandra

Locke

et al. 2023

Pest Management Science

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BACKGROUNDThe potential of weed species to respond to selection forces affecting the evolution of weedy traits such as competitive ability is poorly understood. This research characterized evolutionary growth changes in a single Abutilon theophrasti Medik. population comparing multiple generations collected from 1988 to 2016. A competition study was performed to understand changes in competitive ability, and a herbicide dose–response study was carried out to assess changes in sensitivity to acetolactate synthase‐inhibiting herbicides and glyphosate over time.RESULTSWhen grown in monoculture, A. theophrasti biomass production per plant increased steadily across year‐lines while leaf number decreased. In replacement experiments, A. theophrasti plants from newer year‐lines were more competitive and produced more biomass and leaf area than the oldest year‐line. No clear differences in sensitivity to imazamox were observed among year‐lines. However, starting in 1995, this A. theophrasti population exhibited a progressive increase in growth in response to a sublethal dose of glyphosate (52 g a.e. ha−1), with the 2009 and 2016 year‐lines having more than 50% higher biomass than the nontreated control.CONCLUSIONThis study demonstrates that weeds can rapidly evolve increased competitive ability. Furthermore, the results indicate the possibility of changes in glyphosate hormesis over time. These results highlight the importance of the role that rapid (i.e., subdecadal) evolution of growth traits might have on the sustainability of weed management strategies. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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Growth Analysis of Cotton in Competition with Velvetleaf (Abutilon theophrasti)

Cited by 15 publications

References 49 publications

Determining the critical period for weed control in high-yielding cotton using common sunflower as a mimic weed

Determining the critical period for weed control in high-yielding cotton using common sunflower as a mimic weed

Influence of wild oat plant density on spring wheat yield

Changes in the herbicide sensitivity and competitive ability of Abutilon theophrasti over 28 years: Implications for hormesis and weed evolution

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