Effects of Phytoplasma Infection on Aster Leafhopper ( <i>Macrosteles quadrilineatus</i> ) Settling Behavior and Development on <i>Brassica napus</i>
Bibliographic record
Abstract
ABSTRACT Aster yellows phytoplasma (AYp) is a mollicute that infects numerous crops, including canola ( Brassica napus L.), in which it is pathogenic, and is transmitted by the aster leafhopper ( Macrosteles quadrilineatus Forbes). Understanding how AYp infection alters vector behavior and development is critical for predicting disease dynamics in agricultural systems. We used two‐choice and no‐choice bioassays to assess settling preferences and developmental performance of AYp‐infected and uninfected leafhoppers on AYp‐infected and uninfected B. napus . Arabidopsis thaliana L. was included as a reference host for developmental comparisons. At 2 weeks post‐infection, leafhoppers showed a significant preference for AYp‐infected plants; by 4 weeks, this preference disappeared. Uninfected leafhoppers produced significantly more nymphs on AYp‐uninfected plants than on AYp‐infected plants, although survival on B. napus was poor, and no individuals completed development. Phytoplasma titers in plants increased over time and corresponded with symptom severity. These results show that while AYp infection briefly influences vector settling behavior, B. napus is a marginal host that does not support full development, providing insight into vector–pathogen interactions and disease epidemiology in canola systems.
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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".