Dataset Information

The potential of decision support systems to improve risk assessment for pollen beetle management in winter oilseed rape.

ABSTRACT:

Background

The reliance on and extensive use of pyrethroid insecticides have led to pyrethroid resistance in pollen beetle (Meligethes aeneus). Widespread adoption of best practice in pollen beetle management is therefore needed. Decision support systems (DSSs) that identify the risk period(s) for pest migration can help to target monitoring and control efforts, but they must be accurate and labour efficient to gain the support of growers. Weather data and the phenology of pollen beetles in 44 winter oilseed rape crops across England over 4 years were used to compare the performance of two risk management tools: the DSS proPlant expert, which predicts migration risk according to a phenological model and local weather data, and 'rule-based advice', which depends on crop growth stage and a temperature threshold.

Results

Both risk management tools were effective in prompting monitoring that would detect breaches of various control thresholds. However, the DSS more accurately predicted migration start and advised significantly fewer days of migration risk, consultation days and monitoring than did rule-based advice.

Conclusion

The proPlant expert DSS reliably models pollen beetle phenology. Use of such a DSS can focus monitoring effort to when it is most needed, facilitate the practical use of thresholds and help to prevent unnecessary insecticide applications and the development of insecticide resistance.

SUBMITTER: Ferguson AW

PROVIDER: S-EPMC5049606 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Publications

The potential of decision support systems to improve risk assessment for pollen beetle management in winter oilseed rape.

Ferguson Andrew W AW Skellern Matthew P MP Johnen Andreas A von Richthofen Julia-Sophie JS Watts Nigel P NP Bardsley Eileen E Murray Darren A DA Cook Samantha M SM

Pest management science 20150826 3

<h4>Background</h4>The reliance on and extensive use of pyrethroid insecticides have led to pyrethroid resistance in pollen beetle (Meligethes aeneus). Widespread adoption of best practice in pollen beetle management is therefore needed. Decision support systems (DSSs) that identify the risk period(s) for pest migration can help to target monitoring and control efforts, but they must be accurate and labour efficient to gain the support of growers. Weather data and the phenology of pollen beetles ...[more]

PMID: 26112069

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Project description:Heavy reliance on pesticide inputs to maintain crop yields has been an important aspect of agricultural intensification. Insecticide use has had detrimental impacts on pollinators and natural pest control agents, contributing to a decline in associated ecosystem services, and has also led to resistance development in pest populations. Throughout Europe, in oilseed rape (Brassica napus L.) crops, prophylactic use of insecticides against pollen beetles (Meligethes aeneus F. also known as Brassicogethes aeneus) has led to such issues, and there is an urgent need to develop more sustainable pest management practices for the crop. Although advice is available to oilseed rape growers regarding control thresholds, it may not be adhered to due to the expense of pollen beetle monitoring relative to the inexpensive cost of pyrethroid insecticides. Thus, the key to reducing prophylactic insecticide applications may lie with improved, less labour intensive methods of pollen beetle monitoring. For these to be realized, a better understanding is needed of the effects of agri-landscape features and meteorological conditions on pollen beetle immigration into the crop. In this study, based on data from four years of pollen beetle monitoring on a total of 41 field sites, we model the effects of meteorological (wind speed and direction, rainfall and accumulated temperature) and landscape (areas of woodland, residential gardens, the current and previous seasons' oilseed rape crops, and lengths of hedgerows and treelines) variables on directional sticky trap catches, at both the single trap and field scales. Meteorological variables, particularly accumulated temperature and wind speed were more important than landscape variables in predicting the abundance of pollen beetles immigrating into OSR fields. Sticky traps that were facing downwind caught more beetles than those that were facing across-wind or upwind; this is the first study to show at a landscape-scale, direct evidence for use of upwind anemotaxis by pollen beetles at the point of entry during immigration into the crop. At the field scale, the area of oilseed rape grown in the previous season was found to be positively related to trap catch, but no relationships with other landscape variables were found. Optimally-placed monitoring traps could complement existing decision support systems to reduce pollen beetle monitoring effort and encourage use of insecticides only when control thresholds are breached, thus enhancing the sustainability of oilseed rape production. Knowledge of the area of oilseed rape crops grown during the previous season in the surrounding landscape could contribute to risk assessment of potential pest pressure for individual OSR crops.

Project description:Because sulfur (S) depletion in soil results in seed yield losses and grain quality degradation, especially in high S-demanding crops such as oilseed rape (Brassica napus L.), monitoring S fertilisation has become a central issue. Crop models can be efficient tools to conduct virtual experiments under different fertilisation management strategies. Using the process-based model SuMoToRI, we aimed to analyse the impact of different S fertilisation strategies coupled with the variablility observed in major plant characteristics in oilseed rape i.e. radiation use efficiency (RUE), carbon (C) allocation to the leaves (?) and specific leaf area (SLA) on plant performance-driven variables encompassing total biomass (TDW), S in the photosynthetic leaves (QSmobile.GL) and leaf area index (LAIGL). The contrasting S supply conditions differed in the amount of S (5 levels), and the timing of application (at bolting and/or at flowering, which included a fractioned condition). For this purpose, we performed a global sensitivity analysis (GSA) and calculated two sensitivity indices i.e. the Partial Raw Correlation Coefficient (PRCC) and the Sobol index. The results showed that whatever the timing of S supply, TDW, LAIGL and QSmobile.GL increased as S input increased. For a given S supply, there was no difference in TDW, LAIGL and QSmobile.GL between a single and a fractioned supply. Moreover, delaying the supply until flowering reduced the TDW and LAIGL whereas QSmobile.GL increased. Results showed that RUE had the greatest impact on TDW under all levels of S supply and all application timings, followed by ? and SLA. RUE mostly impacted on QSmobile.GL, depending on S supply conditions, whereas it was the parameter with the least impact on LAIGL. Ultimately, our results provide strong evidence of optimised S fertilisation timings and plant characteristics that will guide producers in their agricultural practices by using specific varieties under constrained S fertilisation strategies.

Project description:Oilseed rape (OSR) is the second largest source of vegetable oil globally and the most important biofuel feedstock in the European Union (EU) but the production of this important crop is threatened by a small insect, Psylliodes chrysocephala - the cabbage stem flea beetle (CSFB). The EU ban on use of neonicotinoid seed treatments and resistance of CSFB to pyrethroid insecticides have left farmers with limited control options resulting in drastic reductions in production. Integrated pest management (IPM) may offer a solution. We review the lifecycle of CSFB and the current options available, or in the research pipeline, for the eight IPM principles of the EU Sustainable Use of Pesticides Directive (Directive-2009/128/EC). A full IPM strategy for CSFB barely exists. Although there are a range of preventative measures, these require scientific validation; critically, resistant/tolerant OSR cultivars are not yet available. Existing monitoring methods are time-consuming and there are no commercial models to enable decision support based on predictions of migration timing or population size. Available thresholds are not based on physiological tolerances of the plant making it hard to adapt them to changing market prices for the crop and costs of control. Non-synthetic alternatives tested and registered for use against CSFB are lacking, making resistance management impossible. CSFB control is therefore dependent upon conservation biocontrol. Natural enemies of CSFB are present, but quantification of their effects is needed and habitat management strategies to exploit their potential. Although some EU countries have local initiatives to reduce insecticide use and encourage use of 'greener' alternatives, there is no formal process for ranking these and little information available to help farmers make choices. We summarize the main knowledge gaps and future research needed to improve measures for CSFB control and to facilitate development of a full IPM strategy for this pest and sustainable oilseeds production.

Dataset Information

The potential of decision support systems to improve risk assessment for pollen beetle management in winter oilseed rape.

Background

Results

Conclusion

Publications

The potential of decision support systems to improve risk assessment for pollen beetle management in winter oilseed rape.

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