Epidemiological and molecular study on ‘<i>Candidatus</i> Phytoplasma prunorum’ in Austria and Hungary
Bibliographic record
Abstract
Abstract The epidemiology of ‘ Candidatus Phytoplasma prunorum’ was studied in Austria and Hungary from 2014 to 2018. Testing of root samples showed average infections rates of 61 and 40% of the Austrian Prunus spinosa and Prunus domestica spp. insititia samples, respectively. In Hungary, on average 21% of the P. spinosa and 13% of the feral Prunus cerasifera samples were infected. The pathogen was found in 18 out of 19 apricot orchards and PCR positive Cacopsylla pruni were observed at 11 out of 17 sampling locations in both countries. In cage experiments with C. pruni remigrants successful pathogen transmission to Prunus armeniaca , P. domestica and P. spinosa seedlings in budding and foliated developmental stages was recorded, an inoculation access period of 4 hr was sufficient for transmission. A field experiment with ungrafted apricot seedlings planted in 2012 and 2014 indicated a prominent role of the insect vectors for disease spread. In 2017, 40 and 28% of the trees planted in 2012 and 2014, respectively, were infected. Molecular characterisation based on the genes aceF and imp allowed the discrimination between 10 phytoplasma types in apricots. Around 70% of the phytoplasma types in apricots were also common in P. spinosa , in P. domestica spp. insititia and in remigrant C. pruni pointing to a possible pathogen exchange by insects between wild and cultivated Prunus spp. For disease control, vector management over the entire flight period of the remigrants seems necessary; when selecting active compounds, the short inoculation access period of not more than 4 hr should be considered.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".