Adverse effects of the Bordeaux mixture copper‐based fungicide on the non‐target vineyard pest <scp><i>Lobesia botrana</i></scp>
Bibliographic record
Abstract
BACKGROUND: Bordeaux mixture is a copper-based fungicide commonly used in vineyards to prevent fungal and bacterial infections in grapevines. However, this fungicide may adversely affect the entomological component, including insect pests. Understanding the impacts of Bordeaux mixture on the vineyard pest Lobesia botrana is an increasing concern in the viticultural production. RESULTS: Bordeaux mixture had detrimental effects on the development and reproductive performance of L. botrana. Several physiological traits were adversely affected by copper-based fungicide exposure, including a decrease in larval survival and a delayed larval development to moth emergence, as well as a reduced reproductive performance through a decrease in female fecundity and fertility and male sperm quality. However, we did not detect any effect of Bordeaux mixture on the measured reproductive behaviors (mating success, pre-mating latency and mating duration). CONCLUSION: Ingestion by larvae of food contaminated with Bordeaux mixture had a negative effect on the reproductive performance of the pest L. botrana, which could affect its population dynamics in vineyards. Although this study highlighted collateral damage of Bordeaux mixture on L. botrana, the potential impact of copper-based fungicides on vineyard diversity, including natural predators is discussed and needs to be taken in consideration in integrated pest management. © 2024 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) | 0.002 | 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".