Population dynamics of the leafhopper <i>Jacobiasca lybica</i> (Hemiptera: Cicadellidae) within vineyards and citrus orchards of Morocco
Bibliographic record
Abstract
The population dynamics of Jacobiasca lybica were monitored in different grapevines cultivars, citrus trees, and windbreak trees and the planning of insecticide treatments based on the recorded degree days (DD) was investigated. The study was conducted in Berkane province of Morocco during 2019, 2020 and 2021, using five yellow sticky traps for each experimental unit that were collected weekly for identification and counting of leafhopper adults. The leafhopper population fluctuated within vineyards, citrus trees and windbreak trees according to temperature recorded where three to seven overlapping peaks of adult flight were observed until September in 2019 and 2021, while a total of ten generations were predicted according to DD until December in 2020. The incidence started to appear clearly on Carignan during July of each year, but on Syrah it appeared only at August to reach 100% of incidence. These periods coincide with the nymph peaks that were higher on Carignan than Syrah. The leafhopper preference to Acacia trees over Cypress trees was observed for all years. Finally, the leafhopper population was decreased after the insecticides applications that were planned mostly after the week following the achieved DD. This technique is discussed as a promising technique to apply the control measures at the correct time.
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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) | 0.000 | 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".