<i>Colletotrichum brevisporum</i> causing anthracnose of papaya ( <i>Carica papaya</i> L.) in Mexico
Bibliographic record
Abstract
Papaya fruit cv. Maradol showing typical symptoms of anthracnose were observed in a commercial orchard located in the municipality of Pinotepa Nacional at the coastal region of Oaxaca, Mexico in September 2020. The incidence rate of anthracnose reached 60%. The symptoms consisted of sunken, water-soaked lesions with salmon-coloured conidia masses on the surface of papaya fruit. The aim of this study was to identify the causal agent of papaya anthracnose based on the phylogenetic analysis of four concatenated datasets. The isolate exhibited sparse white to greyish aerial mycelium and clearly shaped concentric rings with exudate of orange conidia on potato dextrose agar. The fungus was identified as Colletotrichum brevisporum using sequence data of the internal transcribed spacer (ITS) region, and part of the actin (act), glyceraldehyde-3-phosphate dehydrogenase (gapdh), and chitin synthase (chs-1) genes. The fungus isolated from diseased fruit produced lesions on wounded fruit and unwounded fruit. The pathogen was re-isolated from lesions on inoculated fruit to fulfill Koch’s postulates. To our knowledge, this is the first report of C. brevisporum causing anthracnose disease on papaya fruit in Mexico.
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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) | 0.000 | 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".