Olfactory preference in chemical host plant recognition by male and female click beetles and its implications for pest management
Bibliographic record
Abstract
BACKGROUND: Plants emit volatile organic compounds (VOCs), which serve as critical cues for herbivorous insects to locate hosts for feeding and oviposition. Understanding how adults identify host plants is essential to develop pest management strategies, particularly for hemiedaphic insects like click beetles, the larvae of which are significant soil-dwelling pests. To investigate click beetle attraction towards plant VOCs and their relevance for oviposition, we tested the attractiveness of constitutive VOCs (emitted by intact plants) and damage-induced VOCs (released by chopped plants) from 11 plant species to male and female Agriotes sputator beetles. RESULTS: Agriotes sputator beetles exhibit plant species-specific olfactory preferences, which are influenced by beetle sex and female maturity and differ between constitutive and damage-induced VOCs. Female beetles showed the greatest attraction to buckwheat VOCs, especially during their main oviposition period, whereas males were more attracted to clover and ryegrass. EAG recordings show strong female antennal responses to ryegrass, carrot, maize, wild carrot, barley, and buckwheat VOCs, while male antennae responded significantly only to peas. Antennae from female beetles show overall stronger responses to constitutive VOCs than those of males (P = 0.02). CONCLUSION: These findings facilitate the development of new approaches for Agriotes pest management. Understanding preferred plant VOCs aids in identifying attractive semiochemicals that can be used for monitoring female beetles. Additionally, recognizing attractive plants aids wireworm management by either avoiding them in crop rotations before sensitive crops (thus reducing oviposition) or by attracting beetles to specific areas where they can be targeted by control measures. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".