The impact of cover crops on the predatory mite <i>Anystis baccarum</i> (Acari, Anystidae) and the leafhopper pest <i>Empoasca onukii</i> (Hemiptera, Cicadellidae) in a tea plantation
Bibliographic record
Abstract
BACKGROUND: Empoasca onukii, the tea green leafhopper, is a key pest of tea whose control often requires the extensive use of insecticides. As a predator of the tea green leafhopper, the mite Anystis baccarum is a potential biological control agent worldwide, though little is known about how intercropping cover crops can impact its suppressing effect on E. onukii. Therefore, we conducted a field experiment to investigate how the relationship of the abundance of the predatory mite and its leafhopper prey is influenced by two different cover crops and a manually weeded inter-row treatment as a contrast to naturally growing vegetation in a tea plantation in China. RESULTS: The abundance of A. baccarum was significantly higher in tea canopies of intercropped treatments than in canopies over natural ground cover. Litter samples showed higher abundances of A. baccarum when tea was intercropped with Paspalum notatum than with natural ground cover in the first year of treatment. The abundance of E. onukii in tea canopies was higher over the bare ground treatment in the first year but the opposite was observed in the second year. CONCLUSIONS: Results suggest that the abundance of A. baccarum in a tea plantation is influenced by intercropping and it can affect its leafhopper prey, albeit with varying levels of suppression. For informing biological control and suppression of pests, long-term experiments are needed to investigate the interactions of both pest and predator with cover crop treatments. © 2019 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".