Diversity, Virulence, and Fungicide Sensitivity of <i>Colletotrichum</i> Species Associated with Apple Bitter Rot in Nova Scotia
Bibliographic record
Abstract
To date, 21 distinct Colletotrichum species have been identified as causal agents of bitter rot on apple fruit. However, whereas bitter rot occurs in nearly all apple-growing regions, the Colletotrichum species responsible for this disease are not globally prevalent and have distinct regional distributions. Because Colletotrichum species can differ in pathogenicity, virulence, and fungicide sensitivities, characterizing the species present in a growing region is essential for effective disease management. In this study, we obtained 130 Colletotrichum isolates from symptomatic fruit collected in five apple orchards in Nova Scotia and one in New Brunswick, Canada. Using morphological characteristics and multilocus phylogenetic analysis of beta tubulin, internal transcribed spacer, glyceraldehyde 3-phosphate dehydrogenase, actin, and chitin synthase 1, we identified three Colletotrichum species: C. fioriniae (97.6% of isolates), C. salicis (1.5%), and C. nymphaeae (0.8%). We observed that C. salicis was the most aggressive species on detached ‘Honeycrisp’ apple fruit. The in vitro fungicide sensitivity assays revealed that C. nymphaeae was significantly less sensitive to thiabendazole and difenoconazole than the other two species. For C. fioriniae, pyraclostrobin was the most effective fungicide in vitro, followed by difenoconazole, fludioxonil, and thiabendazole. Taken together, these findings provide critical insights for managing bitter rot in Nova Scotia and underscore the need for ongoing monitoring of Colletotrichum species prevalence to inform control strategies effectively.
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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 | 0.001 |
| 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".