Systemic colonization of potato plants resulting from potato haulm inoculation with <i>Dickeya solani</i> or <i>Pectobacterium parmentieri</i>
Bibliographic record
Abstract
In two glasshouse experiments, colonization of potato (Solanum tuberosum L.) plants by the bacterial pathogens Dickeya solani and Pectobacterium parmentieri was studied after leaf infection. Leaves, whether or not artificially wounded, were spray-inoculated with various densities of green-fluorescent protein tagged strains of the pathogens, avoiding contamination of soil during inoculation. Microscopy analysis indicated that both pathogens were able to penetrate and colonize hydathodes, stomata and wounds of inoculated leaves. Dickeya solani was detected at 42 days after inoculation in leaves, stems, stolons and occasionally in tubers, whereas P. parmentieri was restricted to leaves, stems and stolons, and could not be detected in tubers. The infection percentage was higher for plants with wounded leaves than for plants with untouched leaves, and higher at higher inoculum densities. Nevertheless, infection of leaves could also occur at low densities of D. solani (102 cfu mL−1). We further investigated the risks for translocation of the pathogens from infected haulms through soil into progeny tubers after haulm destruction. In a glasshouse experiment, populations of the pathogens increased in haulms in the first week after chemical or mechanical destruction, but decreased in the second week. For P. parmentieri, transmission occurred from destroyed haulms via soil into progeny tubers in soil, but not for D. solani.
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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 | 0.001 |
| 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".