Identification, characterization and pathogenicity of <i>Colletotrichum asianum</i>,<i> C</i>.<i> fructicola</i>, and <i>C</i>.<i> laticiphilum</i> causing mango anthracnose in Vietnam
Bibliographic record
Abstract
Mango ( Mangifera indica L.) is famous for its flavor, aroma, and nutritional value. However, anthracnose caused by Colletotrichum is the most destructive postharvest disease of mango, causing significant economic losses. This study aimed to identify and characterize Colletotrichum species associated with mango anthracnose in Vietnam and evaluate their pathogenicity and cross-infection potential. Through examination of colony characteristics, conidia, and appressorial morphology, along with phylogenetic analysis based on the ITS region and five genetic markers ( gapdh, act, tub2, chs-1, and cal), five isolates were classified into three distinct species: C. asianum (MH32, MH24, and MC76), C. fructicola (MC32), and C. laticiphilum (MC81). Notably, C. fructicola and C. laticiphilum are the two species identified for the first time on mangoes in Vietnam. Pathogenicity tests demonstrated that C. fructicola MC32 and C. laticiphilum MC81 caused anthracnose in mango, banana, guava, and tomato. Among the C. asianum isolates, differences in aggressiveness were observed: isolate MH32 caused anthracnose on mango, banana, guava, and tomato; isolate MC76 caused anthracnose on mango, banana, and tomato; and isolate MH24 affected only mango and tomato.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".