Effect of Synthetic Fungicides Used in Conventional Strawberry Growing System on Hirsutella sp., an Entomopathogenic Fungus of Cyclamen Mite
Bibliographic record
Abstract
The study investigated the effect of 17 synthetic fungicides used in strawberry fields in Québec (Canada) on the in vitro growth of Hirsutella sp., an entomopathogenic fungus. Isolates collected from cyclamen mites from farms with a conventional growing system (Hirsutella sp. H94 and Hirsutella nodulosa H98) and from a farm with an organic growing system (H. nodulosa H0) were selected for the study. All the fungicides tested strongly inhibited the mycelial growth of the three isolates, although slight differences in sensitivity were observed. Fullback® 125 SC (A.I.: flutriafol), Mettle® 125 ME (A.I.: tetraconazole), NovaTM (A.I.: myclobutanil), and Quadris top® (A.I.: azoxystrobin and difenoconazole) were the most effective at inhibiting the growth of the three isolates. Property® 300SC (A.I.: pyriofenone) was the fungicide with the lowest inhibiting effect on the growth of the three isolates. Isolates H94 and H98 obtained from farms with a conventional growing system, and thus frequently exposed to synthetic fungicides, did not show resistance to the fungicides tested. The study suggests that fungicides might negatively impact the natural populations of the entomopathogenic fungi of the genus Hirsutella on strawberry plants.
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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) | 0.001 | 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".