Risks of post-emergence weed control strategies in sugar beet: development and application of a bio-economic model

Buck, Alexander; Schoorlemmer, H.B.; Wossink, G.A.A.; Janssens, S.R.M.

doi:10.1016/s0308-521x(99)00010-4

Cited by 8 publications

(6 citation statements)

References 26 publications

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“…Inter-row hoeing has been proven to be an effective post-emergent weed control method in wide row crops [25][26][27]. High weed control efficacy results can be obtained if the mechanical treatments are applied at the right stage of the weed development and under good weather conditions [28]. This could be confirmed in the present study.…”

Section: Discussionsupporting

confidence: 79%

Sensor-Based Intrarow Mechanical Weed Control in Sugar Beets with Motorized Finger Weeders

et al. 2021

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The need for herbicide usage reduction and the increased interest in mechanical weed control has prompted greater attention to the development of agricultural robots for autonomous weeding in the past years. This also requires the development of suitable mechanical weeding tools. Therefore, we devised a new weeding tool for agricultural robots to perform intrarow mechanical weed control in sugar beets. A conventional finger weeder was modified and equipped with an electric motor. This allowed the rotational movement of the finger weeders independent of the forward travel speed of the tool carrier. The new tool was tested in combination with a bi-spectral camera in a two-year field trial. The camera was used to identify crop plants in the intrarow area. A controller regulated the speed of the motorized finger weeders, realizing two different setups. At the location of a sugar beet plant, the rotational speed was equal to the driving speed of the tractor. Between two sugar beet plants, the rotational speed was either increased by 40% or decreased by 40%. The intrarow weed control efficacy of this new system ranged from 87% to 91% in 2017 and from 91% to 94% in 2018. The sugar beet yields were not adversely affected by the mechanical treatments compared to the conventional herbicide application. The motorized finger weeders present an effective system for selective intrarow mechanical weeding. Certainly, mechanical weeding involves the risk of high weed infestations if the treatments are not applied properly and in a timely manner regardless of whether sensor technology is used or not. However, due to the increasing herbicide resistances and the continuing bans on herbicides, mechanical weeding strategies must be investigated further. The mechanical weeding system of the present study can contribute to the reduction of herbicide use in sugar beets and other wide row crops.

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Section: Discussionsupporting

confidence: 79%

Sensor-Based Intrarow Mechanical Weed Control in Sugar Beets with Motorized Finger Weeders

et al. 2021

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“…Most DSS are devoted to typical annual weeds in wheat based rotations (Cousens et al, 1986;Doyle et al, 1986;Berti et al, 2003;Pannell et al, 2004;Parsons et al, 2009), but other crops, such as soybean and sugar beet, have also been modeled (Berti and Zanin, 1997;De Buck et al, 1999;Rydahl, 2004). Most systems were also designed in European countries (Cousens et al, 1986;Fernández-Quintanilla, 1991, 2004;Berti and Zanin, 1997;Falconer and Hodge, 2001;Berti et al, 2003;Colbach et al, 2007;Parsons et al, 2009;Torra et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Operational planning of herbicide-based weed management

Lodovichi

Blanco

Chantre

et al. 2013

Agricultural Systems

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“…While in the last 20 years the number of bio‐economic models for weeds has increased (Goddard et al. , 1995; De Buck et al. , 1999; Monjardino et al.…”

Section: Introductionmentioning

confidence: 99%

“…This requires a wide array of information, including weed biology, crop yield potential, efficacy of herbicides and mechanical control practices, economics, labour requirements, environmental risks and other factors (Buhler et al, 1996). While in the last 20 years the number of bio-economic models for weeds has increased (Goddard et al, 1995;De Buck et al, 1999;Monjardino et al, 2003;Mullen et al, 2003;Pannell et al, 2004), few of them have taken into account different tillage practices and their effects on population dynamics of herbicide resistant weeds in winter cereals in Mediterranean conditions. The objectives of this paper are to describe the Poppy Integrated Management (PIM) model developed for P. rhoeas management in Spanish winter cereals for dryland areas under Mediterranean conditions.…”

Section: Introductionmentioning

confidence: 99%

PIM (Poppy Integrated Management): a bio‐economic decision support model for the management of Papaver rhoeas in rain‐fed cropping systems

et al. 2010

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Torra J, Cirujeda A, Recasens J, Taberner A & Powles SB (2010). PIM (Poppy Integrated Management): a bio‐economic decision support model for the management of Papaver rhoeas in rain‐fed cropping systems. Weed Research50, 127–139. Summary A bio‐economic model for Papaver rhoeas designed for dry‐land cropping systems in Spain was developed. The model included four seed bank layers to simulate seed movement in the soil profile resulting from tillage, with different emergence rates and seed bank mortalities depending on soil cultivation and burial depth. Users of Poppy Integrated Management (PIM) might specify the crop sequence and any feasible combination of 38 different weed management practices (herbicide and non‐herbicide options) each year over 10 or 20 years. Weed treatment options included selective herbicides (14), non‐selective herbicides (1), non‐herbicide treatments (11) and user‐defined treatments (1). PIM represented weed and seed bank population dynamics, weed–crop competition, weed treatment impacts, agronomic practices and financial details. The bio‐economic model could be used to evaluate weed management scenarios by investigating the implications of different tillage, fallow and cereal rotational sequences and of constraints on herbicide availability. Model validation combined available data from literature with our own data, to show that PIM was sufficiently accurate for predicting P. rhoeas population dynamics. Sensitivity analyses indicated that economics associated with fuel, fertiliser and seed costs, as well as grain yield and price, were primary drivers of management decisions, whereas seedling emergence and initial seed bank size were of secondary importance.

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Risks of post-emergence weed control strategies in sugar beet: development and application of a bio-economic model

Cited by 8 publications

References 26 publications

Sensor-Based Intrarow Mechanical Weed Control in Sugar Beets with Motorized Finger Weeders

Sensor-Based Intrarow Mechanical Weed Control in Sugar Beets with Motorized Finger Weeders

Operational planning of herbicide-based weed management

PIM (Poppy Integrated Management): a bio‐economic decision support model for the management of Papaver rhoeas in rain‐fed cropping systems

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