The <i>Fusarium solani</i> species complex infecting cannabis (<i>Cannabis sativa</i> L., marijuana) plants and a first report of <i>Fusarium</i> (<i>Cylindrocarpon</i>) <i>lichenicola</i> causing root and crown rot
Bibliographic record
Abstract
Greenhouse-grown cannabis (Cannabis sativa L., marijuana) plants with yellowing, crown rot and root-browning symptoms were sampled from six production facilities during 2019–2020. Among 34 fungal isolates recovered, 28 were identified as Fusarium solani and six isolates were provisionally identified as Cylindrocarpon sp. based on morphology. These latter isolates produced slow-growing colonies with grey-white aerial mycelium and a chestnut-brown colour below. Cylindrical 1–3 septate conidia without a distinctive foot cell were produced. Microconidia were absent and chlamydospores were produced in culture. Phylogenetic analysis of three isolates based on the elongation factor (TEF-1 α) and ITS1-5.8S-ITS2 regions identified them as Fusarium lichenicola (formerly Cylindrocarpon lichenicola), a member of F. solani species complex (FSSC) subclade 16. Pathogenicity tests using a mycelial and spore suspension were performed on cannabis cuttings and rooted plants. Isolates of F. solani originating from diseased crowns caused symptoms in 10–14 days, while those of F. lichenicola caused yellowing and wilting after 3 weeks, suggesting that F. lichenicola is less virulent. Inoculum of F. lichenicola was detected in coco coir samples used for plant propagation. Previous reports of F. lichenicola are from tropical climates, where the fungus has been associated with dermal and ocular infections of human tissues, with a few reports of it causing diseases on pomelo fruits, taro corms and tea plants. This study demonstrates the first occurrence worldwide of F. lichenicola on cannabis plants, on which it is considered a weak introduced tropical pathogen, likely to have originated from coco coir imported into Canada.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".