Grapevine Trunk Diseases in British Columbia: Incidence and Characterization of the Fungal Pathogens Associated with Esca and Petri Diseases of Grapevine
Bibliographic record
Abstract
Esca and Petri disease are two economically important grapevine diseases worldwide. This study reports for the first time the occurrence of both diseases on grapevines in British Columbia (BC) and subsequently in Canada. Visual assessment of 55,699 vines in 118 vineyards revealed a low incidence of esca with only 104 (0.2%) vines showing foliar symptoms. Young vine decline (YVD) was observed in 1,910 (7.8%) of 24,487 monitored young vines and in 52 (8%) of 654 young vines used as re-plants in mature vineyards. In 8 of 51 monitored young vineyards, YVD-affected vines ranged between 15 and 55%. Morphological studies along with DNA analyses of the ITS1-5.8S-ITS2, and part of the β-tubulin, actin, and translation elongation factor 1-α gene regions, allowed us to identify Cadophora luteoolivacea, Phaeomoniella chlamydospora, Phaeoacremonium iranianum, Togninia fraxinopennsylvanica, Togninia minima, and the novel species Phaeoacremonium canadense and Phaeoacremonium roseum from esca and Petri disease infected vines in BC. This study includes for the first time the EF1-α DNA marker in Phaeoacremonium spp. delineation. Pathogenicity studies showed all seven fungi to cause vascular symptoms similar to those observed in esca and Petri disease infected vines. Additionally, the "tiger-stripes" foliar symptom of esca was successfully reproduced when healthy potted vines were inoculated with BC isolates of Pa. chlamydospora, Pm. canadense, Pm. iranianum, T. fraxinopennsylvanica, and T. minima.
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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 | 0.001 | 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) | 0.001 | 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".