GWM: General weed management model

Wiles, Lori J.; King, Robert P.; Schweizer, Edward E.; Lybecker, Donald W.; Swinton, Scott M.

doi:10.1016/0308-521x(95)00016-x

Cited by 48 publications

(52 citation statements)

References 27 publications

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“…Computerised decision models help farmers to define the need for weed control and support an optimal choice of herbicides and doses (Wiles et al 1996). The first group of models (efficacy-based models) includes large and updated databases with herbicide performances in different crops, as well as prices to select the most efficient herbicides with the lowest costs.…”

Section: Introductionmentioning

confidence: 99%

Precision farming for weed management: techniques

et al. 2008

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Site-specific weed control techniques have gained interest in the precision farming community over the last years. Managing weeds on a subfield level requires measuring the varying density of weeds within a field. Decision models aid in the selection and adjustment of the treatments, depending on the weed infestation. The weed control can be done either with herbicides or mechanically. A site-specific herbicide application technology can save large amounts of herbicides. Mechanical weed control techniques adapting to the weed situation in the field are applicable to a wide spectrum of crops.Site-specific techniques for the detection and management of weeds are presented. A system for the discrimination of different weed species and crops from images is described, which generates weed maps automatically. Models for the yield effect of weeds are developed and applied in onfarm-research experimental setups. Economic weed thresholds are derived and used for a herbicide application with a patch sprayer.

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Section: Introductionmentioning

confidence: 99%

Precision farming for weed management: techniques

et al. 2008

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“…Efficacybased modeling involves the assessment of control measures and their effectiveness (Wiles et al 1996). It helps in making decisions about herbicide choice and dose for appropriate weed control.…”

Section: Precision Weed Managementmentioning

confidence: 99%

Nonconventional Weed Management Strategies for Modern Agriculture

2015

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Weeds are a significant problem in crop production and their management in modern agriculture is crucial to avoid yield losses and ensure food security. Intensive agricultural practices, changing climate, and natural disasters affect weed dynamics and that requires a change in weed management protocols. The existing manual control options are no longer viable because of labor shortages; chemical control options are limited by ecodegradation, health hazards, and development of herbicide resistance in weeds. We are therefore reviewing some potential nonconventional weed management strategies for modern agriculture that are viable, feasible, and efficient. Improvement in tillage regimes has long been identified as an impressive weed-control measure. Harvest weed seed control and seed predation have been shown as potential tools for reducing weed emergence and seed bank reserves. Development in the field of allelopathy for weed management has led to new techniques for weed control. The remarkable role of biotechnological advancements in developing herbicide-resistant crops, bioherbicides, and harnessing the allelopathic potential of crops is also worth mentioning in a modern weed management program. Thermal weed management has also been observed as a useful technique, especially under conservation agriculture systems. Last, precision weed management has been elaborated with sufficient details. The role of remote sensing, modeling, and robotics as an integral part of precision weed management has been highlighted in a realistic manner. All these strategies are viable for today's agriculture; however, site-specific selection and the use of right combinations will be the key to success. No single strategy is perfect, and therefore an integrated approach may provide better results. Future research is needed to explore the potential of these strategies and to optimize them on technological and cultural bases. The adoption of such methods may improve the efficiency of cropping systems under sustainable and conservation practices.

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“…growth stage, vigour), weed species, weed densities, weed growth stages, herbicide and application costs, the expected price for the crop and the expected yield without weed competition (Gutjahr & Gerhards, 2010). Wiles et al (1996) distinguished between efficacy-based and population-based DSSs for weed control. The former provide herbicide recommendations and in some cases recommendations for the optimal herbicide dose for the actual weed infestation of a field.…”

Section: Decision Rules and Decision Support Systemsmentioning

confidence: 99%

“…In addition, population-based DSS incorporate information about weed biology, ecology and management through deterministic models Wiles et al, 1996). Examples are HERB (Wilkerson et al, 1991) or GESTINF (Berti & Zanin, 1997).…”

Section: Or Crop Protectionmentioning

confidence: 99%