Identification and Characterization of Calonectria Species Associated with Plant Diseases in Southern China
Bibliographic record
Abstract
Calonectria species are important plant pathogens on a wide range of hosts, causing significant losses to plant production worldwide. During our survey on phytopathogenic fungi from 2019 to 2021, diseased samples were collected from various hosts in Guangdong Province, China. In total, 16 Calonectria isolates were obtained from leaf spots, stem blights and root rots of species of Arachis, Cassia, Callistemon, Eucalyptus, Heliconia, Melaleuca and Strelitzia plants. Isolates were identified morphologically, and a multigene phylogenetic analysis of combined partial sequences of calmodulin (cmdA), translation elongation factor 1-alpha (tef1-α) and beta-tubulin (β-tubulin) was performed. These sixteen isolates were further identified as nine Calonectria species, with five new species: Ca. cassiae, Ca. guangdongensis, Ca. melaleucae, Ca. shaoguanensis and Ca. strelitziae, as well as four new records: Ca. aconidialis from Arachis hypogaea, Ca. auriculiformis from Eucalyptus sp., Ca. eucalypti from Callistemon rigidus, and Ca. hongkongensis from Eucalyptus gunnii. Moreover, we provide updated phylogenetic trees for four Calonectria species complexes viz. Ca. colhounii, Ca. cylindrospora, Ca. kyotensis and Ca. reteaudii. Our study is the first comprehensive study on Calonectria species associated with various hosts from subtropical regions in China. Results from the present study will be an addition to the biodiversity of microfungi in South 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 | 0.002 | 0.002 |
| 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".