2015
DOI: 10.1007/s13593-014-0279-5
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Management of wireworm damage in maize fields using new, landscape-scale strategies

Abstract: Crop-damaging wireworms-the soil-dwelling larvae of click beetles-have resurged in Europe over the past 15 years, particularly in French maize crops. There is currently no curative treatment available to control wireworms, and preventive treatments are mainly chemical. We therefore need to better understand factors that rule damage for developing agroecological control strategies. In this investigation, we tested the effect of agricultural practices and local landscape on wireworm damage in maize crops. We sur… Show more

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Cited by 27 publications
(23 citation statements)
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“…These results confirm observations reported by other authors (Blackshaw and Hicks 2013; Benefer et al 2012; Hermann et al 2013; Saussure et al 2015). …”
Section: Resultssupporting
confidence: 92%
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“…These results confirm observations reported by other authors (Blackshaw and Hicks 2013; Benefer et al 2012; Hermann et al 2013; Saussure et al 2015). …”
Section: Resultssupporting
confidence: 92%
“…

“Area-wide” risk assessment: the results of this work enable each cultivated region to be mapped, and high-risk areas to be pinpointed. Mapping the risk factors found in this survey and that of Saussure et al (2015) outside Italy may enable us to prove that the cost-benefit analysis of past soil-insecticide use was extremely negative. The first layer of the map would include the main soil characteristics (organic matter content, pH, texture); the second would include the key agronomic characteristics (rotation, drainage); and the third, the available entomological information, such as click beetle population levels for the main Agriotes species, or wireworm presence/density assessed with bait traps over the years.

…”
Section: Resultsmentioning
confidence: 69%
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“…Abdel-Rahman et al (2013) used random forest regression to build predictive models of sugarcane leaf nitrogen levels from hyperspectral satellite images, while Philibert et al (2013) were able to identify nitrogen fertilization, crop type, and experiment duration as the most important predictor variables of N 2 O emissions. Saussure et al (2015) incorporated random forests as part of a data processing framework to develop preventive solutions for the sustainable control of wireworms and Everingham et al (2007b) successfully used random forests to classify sugarcane variety and the number of times the sugarcane has been harvested and allowed to regrow.…”
Section: Introductionmentioning
confidence: 99%