Field evaluation of a decision support system for herbicidal control of <i>Avena sterilis</i> ssp. <i>ludoviciana</i> in winter wheat

González-Andújar, José L.; Fernández‐Quintanilla, César; Bastida, Fernando; Calvo, Rosa; González-Díaz, L.; Izquierdo, Jordi; Lezáun, Juan Antonio; Perea, F.; Arco, María Jesús Sánchez del; Urbano, J. M.

doi:10.1111/j.1365-3180.2009.00744.x

Cited by 22 publications

(13 citation statements)

References 26 publications

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“…Thus, this bioeconomic model could be further developed by integrating it within a DSS framework (Gonzalez-Andujar et al, 2010) to help decision-making by both farmers and technicians. Strategy T2: 100% and 0% control of the early and late cohorts, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Growers and consultants can manage the integration of these factors using Decision Support Systems (DSS) (Gonzalez-Andujar et al, 2010). DSS can provide a structure upon which farmers can base their decisions and offer hypotheses for tackling weed management problems.…”

Section: Simulation Of Control Strategies For Decision-making Regardingmentioning

confidence: 99%

“…A bioeconomic model can be used as a component of DSS. The use of bioeconomic models is a useful technique that integrates biological, agronomic and economic knowledge, thereby producing a framework that can be used to evaluate the economic performance provided by various management scenarios (Gonzalez-Andujar and Fernandez-Quintanilla, 1993;Swinton and King, 1994;Gonzalez-Andujar et al, 2010).…”

Section: Simulation Of Control Strategies For Decision-making Regardingmentioning

confidence: 99%

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Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans

2012

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Cien. Inv. Agr. 39(2): 299-308. A bioeconomic model was developed for decision-making regarding large crabgrass (Digitaria sanguinalis) control in glyphosate-resistant soybeans in the Rolling Pampas of Argentina. The model was used to evaluate the economic returns of four different glyphosate-based strategies for weed control. In the absence of herbicide application (T1), the soil seed bank increases to an equilibrium density of 12,079 seeds m -2 in three years. A single herbicide application during the early stages of the crop (T2), which was intended to be highly effective in the control of an early weed cohort, allows a late, unaffected cohort to produce sufficient seeds to maintain population densities in the soil seed bank. A single, delayed herbicide application (T3), which was intended to control both early and late cohorts, results in a soil seed bank increase up to an equilibrium density similar to that achieved without treatment. Two sequential herbicide applications per year (T4), targeting the two cohorts, leads to a soil seed bank density after 10 years of 107 seeds m -2 . Model predictions indicate that in the absence of control measures, a 93% reduction in soybean yield was predicted due to weed interference. The lowest reduction in crop yield (27%) was predicted using strategy T4, which is the most common control measure used by local farmers. This strategy clearly outperforms the other options tested, leading to lower D. sanguinalis seed bank densities and higher soybean yields and economic returns compared to those obtained using the alternative strategies.

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Section: Resultsmentioning

confidence: 99%

Section: Simulation Of Control Strategies For Decision-making Regardingmentioning

confidence: 99%

Section: Simulation Of Control Strategies For Decision-making Regardingmentioning

confidence: 99%

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Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans

2012

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“…Increasing public awareness and concern about the impact of herbicides on the environment, development of herbicide‐resistant weeds and the high economic cost of herbicides have increased the need to reduce the amount of herbicides used in agriculture (Kim et al. , 2001; Gonzalez‐Andujar et al. , 2010).…”

Section: Introductionmentioning

confidence: 99%

Interactions between reduced rate of imazethapyr and multiple weed species–soyabean interference in a semi‐arid environment

Yousefi¹,

González‐Andújar²,

Mohammad-Alizadeh³

et al. 2012

Weed Research

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Yousefi AR, Gonzalez‐Andujar JL, Alizadeh H, Baghestani MA, Rahimian H & Karimmojeni H (2012). Interactions between reduced rate of imazethapyr and multiple weed species–soyabean interference in a semi‐arid environment. Weed Research.52, 242–251. Summary Field experiments were conducted to evaluate Xanthium strumarium and Amaranthus retroflexus competitive ability with soyabean under unsprayed and sprayed (half the recommended rate of imazethapyr) conditions. Weed density combinations of 0, 4, 8 or 12 plants m−1 of row for A. retroflexus and 0, 2, 4 or 8 plants m−1 of row for X. strumarium were established alone, and in all possible combinations. When X. strumarium and A. retroflexus were grown at the same density, X. strumarium contributed 60–69% of the total weed biomass depending on weed density. The half rate of imazethapyr reduced the biomass of both weed species by 90% as compared with untreated plots. Untreated A. retroflexus and X. strumarium reduced soyabean yields to 1911 kg and 1656 kg ha−1, respectively, while with the reduced rate of herbicide, the yield only decreased to 3612 kg and 3453 kg ha−1 respectively. The total weed density required to cause a 5% soyabean yield loss was 0.16 and 0.32 plants m−1 of row with no‐herbicide treatment, while with the half rate of imazethapyr, it increased up to 2.78 and 4.32 plants m−1 in 2007 and 2008 respectively. Owing to the higher competitive ability of X. strumarium, it should be given a greater priority for control than A. retroflexus in soyabean grown in a semi‐arid environment. The half rate of herbicide significantly decreased the competitive ability of X. strumarium and A. retroflexus indicating that, in soyabean, application of this rate might be more cost‐effective and more environment‐friendly than the recommended ones.

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“…it has been stated that reduction in herbicide dose rates does not significantly reduce herbicide efficacy [5,6,7]. However, GonzalezAndujar et al [8] demonstrated that Avena sterilis plants produce more panicles at reduced herbicide dose rates. This might cause a shift in weed population towards less herbicide-sensitive individuals in the following generations [9,10].…”

Section: Introductionmentioning

confidence: 99%

Winter wheat yield loss in response to Avena fatua competition and effect of reduced herbicide dose rates on seed production of this species

2017

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Avena fatua is one of the most abundant and competitive grass weed species in cereal cropping systems worldwide. Despite its main occurrence in summer annual cereals, A. fatua is suspected to cause significant yield losses in winter wheat as well. Five yield loss experiments were conducted over the course of five years to investigate the impact of A. fatua on winter wheat yield. Two additional field studies were conducted to assess the efficacy of two ALS-inhibiting herbicides as well as of two ACCaseinhibiting herbicides at variable dose rates on A. fatua seed production. Avena fatua caused significant winter wheat yield losses of up to 40% at densities of approximately 250 plants m -2 . Winter wheat yield losses did not differ between years and sites. Relative A. fatua biomass was a better predictor for winter wheat yield loss as A. fatua density and biomass. Three out of four herbicides showed high efficacy against A. fatua, even at reduced dose rates, but A. fatua seed production was not directly related to herbicide efficacy. Seed production was rather influenced by the mode of action and the competitiveness of the winter wheat stand. The results showed that A. fatua can be a serious threat for winter wheat production in the local conditions, leading to high yield losses if not controlled. We did not find a general potential for reducing herbicide dose rates for the control of A. fatua in winter wheat due to variable effects on A. fatua seed production. The potential is highly dependent on the winter wheat competitiveness and herbicide mode of action.

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Field evaluation of a decision support system for herbicidal control of Avena sterilis ssp. ludoviciana in winter wheat

Cited by 22 publications

References 26 publications

Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans

Simulation of control strategies for decision-making regarding Digitaria sanguinalis in glyphosate-resistant soybeans

Interactions between reduced rate of imazethapyr and multiple weed species–soyabean interference in a semi‐arid environment

Winter wheat yield loss in response to Avena fatua competition and effect of reduced herbicide dose rates on seed production of this species

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