Management of wireworm damage in maize fields using new, landscape-scale strategies

Saussure, Stéphanie; Plantegenest, Manuel; Thibord, Jean-Baptiste; Larroudé, Philippe; Poggi, Sylvain

doi:10.1007/s13593-014-0279-5

Cited by 26 publications

(23 citation statements)

References 32 publications

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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%

“…Therefore, the information has no practical implications on risk assessment. Saussure et al (2015), however, did not find that higher soil OM content led to increased damage risk, but they did not provide absolute data analyses. Consequently, it is not possible to ascertain whether OM values in France ranged below or above the threshold found in this study.…”

Section: Resultsmentioning

confidence: 97%

“…Due to lack of fields with plant damage over 15 %, it was impossible to calculate RR in this case. Saussure et al (2015) found that the number of tillage operations, especially in spring, raised damage probability, but did not make clear whether these operations were part of conventional procedures, including ploughing. In our case, the number of tillage operations (cultivation, harrowing, hoeing) did not vary significantly between farms in the area studied, which meant that this factor could not be used to evaluate damage risk.…”

Section: Resultsmentioning

confidence: 99%

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Risk assessment of maize damage by wireworms (Coleoptera: Elateridae) as the first step in implementing IPM and in reducing the environmental impact of soil insecticides

Furlan

Contiero

Chiarini

et al. 2016

Environ Sci Pollut Res

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A survey of maize fields was conducted in northeast Italy from 1986 to 2014, resulting in a dataset of 1296 records including information on wireworm damage to maize, plant-attacking species, agronomic characteristics, landscape and climate. Three wireworm species, Agriotes brevis Candeze, A. sordidus Illiger and A. ustulatus Schäller, were identified as the dominant pest species in maize fields. Over the 29-year period surveyed, no yield reduction was observed when wireworm plant damage was below 15 % of the stand. A preliminary univariate analysis of risk assessment was applied to identify the main factors influencing the occurrence of damage. A multifactorial model was then applied by using the significant factors identified. This model allowed the research to highlight the strongest factors and to analyse how the main factors together influenced damage risk. The strongest factors were: A. brevis as prevalent damaging species, soil organic matter content >5 %, rotation including meadows and/or double crops, A. sordidus as prevalent damaging species, and surrounding landscape mainly meadows, uncultivated grass and double crops. The multifactorial model also showed how the simultaneous occurrence of two or more of the aforementioned risk factors can conspicuously increase the risk of wireworm damage to maize crops, while the probability of damage to a field with no-risk factors is always low (<1 %). These results make it possible to draw risk maps to identify low-risk and high-risk areas, a first step in implementing bespoke IPM procedures in an attempt to reduce the impact of soil insecticides significantly.

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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%

“…

…”

Section: Resultsmentioning

confidence: 69%

Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Risk assessment of maize damage by wireworms (Coleoptera: Elateridae) as the first step in implementing IPM and in reducing the environmental impact of soil insecticides

Furlan

Contiero

Chiarini

et al. 2016

Environ Sci Pollut Res

View full text Add to dashboard Cite

show abstract

“…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%

Accurate prediction of sugarcane yield using a random forest algorithm

Everingham

Sexton

Skocaj

et al. 2016

Agron. Sustain. Dev.

219

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Foreknowledge about sugarcane crop size can help industry members make more informed decisions. There exists many different combinations of climate variables, seasonal climate prediction indices, and crop model outputs that could prove useful in explaining sugarcane crop size. A data mining method like random forests can cope with generating a prediction model when the search space of predictor variables is large. Research that has investigated the accuracy of random forests to explain annual variation in sugarcane productivity and the suitability of predictor variables generated from crop models coupled with observed climate and seasonal climate prediction indices is limited. Simulated biomass from the APSIM (Agricultural Production Systems sIMulator) sugarcane crop model, seasonal climate prediction indices and observed rainfall, maximum and minimum temperature, and radiation were supplied as inputs to a random forest classifier and a random forest regression model to explain annual variation in regional sugarcane yields at Tully, in northeastern Australia. Prediction models were generated on 1 September in the year before harvest, and then on 1 January and 1 March in the year of harvest, which typically runs from June to November. Our results indicated that in 86.36 % of years, it was possible to determine as early as September in the year before harvest if production would be above the median. This accuracy improved to 95.45 % by January in the year of harvest. The R-squared of the random forest regression model gradually improved from 66.76 to 79.21 % from September in the year before harvest through to March in the same year of harvest. All three sets of variables-(i) simulated biomass indices, (ii) observed climate, and (iii) seasonal climate prediction indices-were typically featured in the models at various stages. Better crop predictions allows farmers to improve their nitrogen management to meet the demands of the new crop, mill managers could better plan the mill's labor requirements and maintenance scheduling activities, and marketers can more confidently manage the forward sale and storage of the crop. Hence, accurate yield forecasts can improve industry sustainability by delivering better environmental and economic outcomes.

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Three years of surveillance associates agro‐environmental factors with wireworm infestations in Manitoba, Canada

Drahun

Wiebe

Gohl

et al. 2021

Pest Management Science

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BACKGROUND Wireworms, the soil‐dwelling larvae of click beetles, are a major threat to global agricultural production. This is largely due to their generalist polyphagous feeding capabilities, extended and cryptic life cycles, and limited management options available. Although wireworms are well‐documented as economically important pests in the Canadian Prairies, including Manitoba, there are gaps in knowledge on species distributions, subterranean behaviour and life cycles, feeding ecology and damage capacity, and economic thresholds for crop yield loss. Results We carried out 3 years (2018–2020) of intensive surveillance of larval populations across Manitoba. A total of 31 fields (24 in ≥ 2 consecutive years) were surveyed in early spring using standardized bait trapping approaches. Wireworms were present in 94% of surveyed sites, but the catch within fields varied year to year. While Hypnoidus bicolor predominated (94% of larvae), several other pest species were identified. We then explored the relationships between wireworm trap numbers and agro‐environmental factors. The larval catch tended to decrease under conditions of low soil temperatures and increased clay content, coupled with high soil moisture and precipitation during the trapping period. Treatment and cultural methods appeared less influential; however, wheat production in either of the previous two growing seasons was associated with increased wireworm catch. Our models failed to predict a relationship between wireworm catch and crop yields, although infestations were rare in our region. Conclusion Our findings better infer the risks posed by wireworms to crop production in the Canadian Prairies, and the agro‐environmental factors that represent the greatest contributors to these risks. This information should be incorporated into future integrated pest management (IPM) strategies for wireworms. © 2021 Her Majesty the Queen in Right of Canada Pest Management Science © 2021 Society of Chemical Industry Reproduced with the permission of the Minister of Agriculture and Agri‐Food Canada.

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Management of wireworm damage in maize fields using new, landscape-scale strategies

Cited by 26 publications

References 32 publications

Risk assessment of maize damage by wireworms (Coleoptera: Elateridae) as the first step in implementing IPM and in reducing the environmental impact of soil insecticides

Risk assessment of maize damage by wireworms (Coleoptera: Elateridae) as the first step in implementing IPM and in reducing the environmental impact of soil insecticides

Accurate prediction of sugarcane yield using a random forest algorithm

Three years of surveillance associates agro‐environmental factors with wireworm infestations in Manitoba, Canada

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