Identification and Characterization of <i>Colletotrichum</i> Species Associated with Mango Anthracnose in Guangxi, China
Bibliographic record
Abstract
Mango (Mangifera indica) is widely grown across southern China, especially in the provinces of Guangxi, Hainan, Yunnan, Sichuan, and Taiwan. Guangxi itself has over 86,667 ha of mango production. The purpose of this study was to identify Colletotrichum species associated with mango in different parts of Guangxi and examine their pathogenicity on leaves and fruits of mango in vitro. Diseased leaves were collected from 25 mango orchards in different areas of Guangxi province. Sixty-five isolates were obtained from mango leaves with anthracnose symptoms, and these were further characterized based on morphology and DNA sequencing. Twenty-nine isolates from different areas were selected for sequencing and analyses of the internal transcribed spacer region, glyceraldehyde-3-phosphate dehydrogenase, partial actin, β-tubulin, and chitin synthase genomic regions. The most common fungal isolates were these three species: Colletotrichum asianum, C. fructicola, and C. siamense. C. asianum was the most common and widely distributed in Guangxi (51.7%), followed by C. fructicola (37.9%) and C. siamense (10.2%), both found in Tiandong, Tianyang, and Wuming counties. There was no evidence of geographical specialization of the different species. Pathogenicity assays showed that all isolates were pathogenic to mango leaves and fruit (cultivar Tainong). No relationship was found between origin of isolates and their virulence. This is the first description of C. asianum, C. fructicola, and C. siamense as causal agents of mango leaf anthracnose from Guangxi province, China.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".