Identification and characterization of Colletotrichum species causing apple bitter rot in New York and description of C. noveboracense sp. nov.
Bibliographic record
Abstract
Apple bitter rot caused by Colletotrichum species is a growing problem worldwide. Colletotrichum spp. are economically important but taxonomically un-resolved. Identification of Colletotrichum spp. is critical due to potential species-level differences in pathogenicity-related characteristics. A 400-isolate collection from New York apple orchards were morphologically assorted to two groups, C. acutatum species complex (CASC) and C. gloeosporioides species complex (CGSC). A sub-sample of 44 representative isolates, spanning the geographical distribution and apple varieties, were assigned to species based on multi-locus phylogenetic analyses of nrITS, GAPDH and TUB2 for CASC, and ITS, GAPDH, CAL, ACT, TUB2, APN2, ApMat and GS genes for CGSC. The dominant species was C. fioriniae, followed by C. chrysophilum and a novel species, C. noveboracense, described in this study. This study represents the first report of C. chrysophilum and C. noveboracense as pathogens of apple. We assessed the enzyme activity and fungicide sensitivity for isolates identified in New York. All isolates showed amylolytic, cellulolytic and lipolytic, but not proteolytic activity. C. chrysophilum showed the highest cellulase and the lowest lipase activity, while C. noveboracense had the highest amylase activity. Fungicide assays showed that C. fioriniae was sensitive to benzovindiflupyr and thiabendazole, while C. chrysophilum and C. noveboracense were sensitive to fludioxonil, pyraclostrobin and difenoconazole. All species were pathogenic on apple fruit with varying lesion sizes. Our findings of differing pathogenicity-related characteristics among the three species demonstrate the importance of accurate species identification for any downstream investigations of Colletotrichum spp. in major apple growing regions.
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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 | 0.002 | 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) | 0.001 | 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".