First report of <i>Fusarium proliferatum</i> causing crown and stem rot, and pith necrosis, in cannabis (<i>Cannabis sativa</i> L., marijuana) plants
Bibliographic record
Abstract
Cannabis (Cannabis sativa L., marijuana) plants grown under greenhouse or controlled environments with symptoms of leaf yellowing, leaf necrosis and defoliation were observed during 2018–2019. Additional symptoms included crown rot and internal browning or blackening of the pith tissues. Stock (mother) plants as well as plants in the vegetative and flowering stages of 15 cannabis strains (genotypes) were affected. In addition, damping-off symptoms were observed on rooted cuttings in propagation rooms. Isolations from diseased tissues yielded predominantly Fusarium proliferatum, with some F. oxysporum also recovered. Phylogenetic analysis of sequences from the translation elongation factor 1α (TEF-1 α) region of 29 isolates of F. proliferatum from eight licenced production facilities in three provinces in Canada (British Columbia, Ontario and New Brunswick), and one cannabis production site in northern California, grouped isolates from cannabis with a large clade of isolates from a wide range of other hosts in different geographic regions. Pathogenicity studies confirmed the ability of F. proliferatum to cause symptoms of wilting, leaf and pith necrosis, and plant death on cuttings, rooted plants and stock plants. Inoculated tomato and cucumber plants developed similar symptoms. Stem colonization was more extensive by F. proliferatum compared to F. oxysporum on cannabis cuttings. Both grew optimally at 25°C on agar media although F. oxysporum grew faster than F. proliferatum at all temperatures tested. The occurrence of F. proliferatum on cannabis plants has not been previously reported, adding to recent reports of F. oxysporum and F. solani that cause similar symptoms on cannabis plants.
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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 | 0.000 | 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) | 0.001 | 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".