Investigating biopesticides for the control of cabbage stem flea beetle (Psylliodes chrysocephala)
Bibliographic record
Abstract
The cabbage stem flea beetle (CSFB, Psylliodes chrysocephala, L.) is an economically important pest of oilseed rape crops in the UK and the rest of Europe. This pest was controlled through the use of neonicotinoid seed dressings until they were placed under a moratorium and subsequently banned by the European Union in 2013 and 2018, respectively. In response, oilseed rape growers initially increased their reliance on foliar applications of pyrethroid insecticides to control CSFB, which led to the increase of resistance to this type of insecticides \nin CSFB populations. There is then an urgent need for growers to find alternative effective solutions to control CSFB in oilseed rape crops. \nThis study aimed to investigate the potential of biopesticides to effectively control CSFB in oilseed rape crops. A review of the knowledge on CSFB and related flea beetle control is \npresented in Chapter 1. A range of methods to effectively rear CSFB under laboratory conditions are presented in Chapter 2. The efficacy of fatty acids, entomopathogenic fungi, entomopathogenic bacteria, the botanical insecticide zadirachtin and pyrethroid insecticides, under laboratory conditions is investigated in Chapter 3. Chapter 3 also investigated the potential of adjuvants to improve the persistence of fatty acids on oilseed rape leaves. Fatty \nacids and entomopathogenic fungi were found to significantly increase CSFB adult mortality but entomopathogenic bacteria and azadirachtin were not effective. The potential of various \nspecies of entomopathogenic nematodes to control CSFB adults under laboratory conditions is investigated in Chapter 4. All nematode species significantly increased CSFB mortality \ncompared to a water control. The potential of the biopesticides tested in Chapters 3 and 4 under field conditions is tested in Chapter 5. However, here none of the biopesticides tested \nwere found to significantly reduce CSFB feeding damage on oilseed rape leaves or larval numbers. A sentiment analysis of the UK farming press before and after the neonicotinoid insecticides moratorium is presented in Chapter 6. Finally, the key findings from this study are discussed more broadly to reflect the international effort to combat this pest in Chapter 7. The overall aim of this study, which was to evaluate the potential of biopesticides to control CSFB, was met in terms of laboratory testing. However, more work is needed to confirm whether biopesticides are a viable option as part of an Integrated Pest Management programme to control CSFB in oilseed rape crops.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".