First report of <i>Colletotrichum spaethianum</i> causing anthracnose disease on <i>Bletilla striata</i>
Bibliographic record
Abstract
Bletilla striata is a traditional Chinese medicine plant. Guizhou Province is the largest producer of B. striata, with the biggest cultivation area and highest yield in China. Anthracnose is the main disease affecting the crop. In July 2021, an anthracnose outbreak occurred in Shibing County, Guizhou Province, seriously affecting the yield and quality of B. striata. Thirty samples of B. striata anthracnose were collected from Shuangjing, Niudachang, and Yangliutang towns in three main planting areas of Shibing County to clarify the causal agent of B. striata anthracnose. Fifty anthracnose strains were isolated by tissue isolation and single-conidium culture. Through morphological observation and multigene phylogenetic analysis of the internal transcribed spacer, actin, beta-tubulin, glyceraldehyde-3-phosphate dehydrogenase and chitin synthase genes, the isolated strains were identified as Colletotrichum spaethianum. The infection process of C. spaethianum on B. striata leaves was observed by cell tissue staining. The results showed that at 25°C, the conidia of C. spaethianum on B. striata leaves began to germinate after 3 h, and the peak period of conidia germination was 8 h. Appressoria formation peaked after 24 h. During 48–72 h, the hyphae randomly expanded horizontally and vertically on the host surface, gradually forming a reticular distribution. This study is the first report of C. spaethianum causing anthracnose in B. striata. Our study clarifies the infection and development process of C. spaethianum on B. striata leaves, thus providing a theoretical basis for further study on the monitoring of B. striata anthracnose.
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) | 0.001 | 0.001 |
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".