Seasonal abundance, species composition, fruit damage, and attracticidal control of stink bugs (Hemiptera: Pentatomidae) in apple orchards in Québec, Canada
Bibliographic record
Abstract
Apple (Malus domestica Borkhausen, Rosaceae, Rosales) orchards in Québec (Canada) have recently experienced increases in both stink bug populations and associated fruit damage. Even in the absence of the brown marmorated stink bug, Halyomorpha halys (Stål), stink bugs are jeopardizing Integrated Pest Management (IPM) programs since few environment-friendly control options are available. The objectives of this study were thus to (i) acquire knowledge on the seasonal abundance and species composition of Pentatomidae in 4 apple orchards using baited pyramid traps and beating trays and (ii) adapt and test an attract-and-kill (AK) strategy based on the knowledge acquired. Twenty species of stink bugs were collected over 3 years. Euschistus servus euschistoides (Vollenhoven) represented 80% of individuals captured overall and peaked at the end of August. Chinavia hilaris (Say), Euschistus tristigmus (Say), and H. halys came in second, third, and fourth place, respectively. Trece's multi-species pheromone lures (Pherocon CSB+GSB+BMSB) commercialized for Euschistus sp., C. hilaris and H. halys respectively, caught the highest numbers of species and individuals, and were thus chosen for the AK trial. Lures were used in combination with sticky-coated yellow panel traps deployed at the periphery of the orchards. AK resulted in high stink bug mortality (numbers equivalent to ca. 10,000 individuals/ha) and damage was reduced by 25% overall for the 4 orchards, but not enough to translate into a statistically significant effect. Visual appearance of damage to fruit caused by phytophagous stink bugs on different cultivars is described.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".