Morphological characterization and pathogenicity of <i>Colletotrichum aenigma</i> and <i>C. siamense</i> causing anthracnose on <i>Euonymus japonicus</i> in Beijing, China
Bibliographic record
Abstract
Abstract Euonymus japonicus plays important roles in the process of urban landscape construction as an evergreen shrub. Anthracnose is an important limiting factor affecting the healthy growth of E . japonicus , seriously influencing improvement of urban landscape ecosystems. However, the Colletotrichum species associated with anthracnose on E . japonicus are unclear. In this study, diseased leaves of E . japonicus with typical anthracnose symptoms were collected in five nurseries in Beijing, China. Among 45 Colletotrichum isolates obtained, there were two distinct morphotypes, which were identified as C . aenigma or C . siamense by morphological characteristics and multilocus phylogenetic analysis. The growth rates of these two species were determined at different incubation temperatures, and the results showed that both species grew well at 10–35°C, particularly at 25 or 30°C, while C . aenigma isolates were adapted to high growth rates at a wider range of temperatures than C . siamense . Pathogenicity assays indicated that the two species showed varying degrees of pathogenicity on E . japonicus. Wounding was conducive to the pathogenicity of C . aenigma or C . siamense on E . japonicus either by inoculation with mycelial discs or conidial suspensions. This study presents the first report of C . aenigma causing anthracnose on E . japonicus worldwide and of C . siamense in north China causing anthracnose on E . japonicus . The morphological features of Colletotrichum spp. associated with anthracnose on E . japonicus were also compared in detail in this study. The findings provide a contribution to the prevention and control of anthracnose on E . japonicus by better understanding the species involved.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".