Effect of leaf scar age, chilling and freezing-thawing on infection of <i>Pseudomonas syringae</i> pv. <i>syringae</i> through leaf scars and lenticels in stone fruits
Why this work is in the frame
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Bibliographic record
Abstract
Introduction . Bacterial canker, caused by P. syringae pv. syringae , is an important disease of stone fruit worldwide. The possibility of P. syringae pv. syringae infection through leaf scars and lenticels was evaluated in cherry, peach and prune. Materials and methods . Laboratory and field inoculations were performed using cherry, peach and prune stems to evaluate leaf scar age, chilling and freezing-thawing on bacterial infection through leaf scars and lenticels. Results and discussion . Increasing leaf scar age was associated with significant decreases in disease incidence and length of lesions resulting from leaf scar inoculation with Pseudomonas syringae pv. syringae in cherry, peach and prune. A significant reduction in incidence and lesion length was observed after 4 h of air exposure, and both measures of infection were reduced to essentially 0 by 2 days of exposure. Prolonged chilling temperature (2.2 °C) prior to leaf removal had no clear effect on disease incidence of leaf scar infection, but significantly decreased lesion length due to leaf scar infection. Cherry was more susceptible to P. syringae pv. syringae infection through leaf scars than peach and ‘French’ prune. The leaf scar inoculation results were consistent with the previous studies. The disease incidence of lenticel infection caused by bacterial inoculation in ‘French’ prune was very low, but significantly higher than the water control. Freezing-thawing significantly increased both the disease incidence and the lesion size via lenticel infection. The lenticel inoculation data suggest that P. syringae pv. syringae infection through lenticels is possible under field conditions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it