<i>Diplodia sapinea</i> as the pathogen causing trunk canker on <i>Pinus bungeana</i> trees in China
Bibliographic record
Abstract
Pinus bungeana belonging to the genus Pinus is a pine tree species endemic to China. It plays vital roles in afforestation, forest regeneration, landscaping, forest ecosystems, and environmental protection. However, P. bungeana has been listed as a rare and endangered species in recent years due to population fragmentation. The occurrence of lethal diseases on the trees has made the situation even worse. This study aimed to identify the pathogen causing the trunk canker on P. bungeana trees in Qingdao, China. The morphological identification of the pathogen relied primarily on the morphology of conidia. Molecular identification was performed using the combined sequences of ITS, Tef and Tub2 genes. The eight isolates were all identified as Diplodia sapinea. The pathogenicity of the eight isolates was examined both in vitro and in vivo. The results showed that all the fungal isolates caused severe canker symptoms on the inoculated P. bungeana branches. Moreover, D. sapinea was re-isolated from the inoculated branches. This study is novel in reporting D. sapinea causing trunk canker on P. bungeana trees in China.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".