Genomic analyses of five <i>Fusarium</i> species infecting cannabis ( <i>Cannabis sativa</i> L.) plants in Canada and their potential for mycotoxin production
Bibliographic record
Abstract
Fusarium species are important pathogens that affect many vegetable, cereal, and pulse crops in Canada. These pathogens also infect a diverse range of horticultural crops, including cannabis (Cannabis sativa L.). A range of disease symptoms have been reported on cannabis plants upon infection by several Fusarium species, which include root rot, wilting, stem rot, and bud rot. In this study, we report the genome sequences of five Fusarium species that were recovered from symptomatic greenhouse-grown cannabis plants in British Columbia: F. graminearum, F. sporotrichioides, F. culmorum, F. proliferatum, and F. oxysporum. Comparative genomic analysis revealed that the isolates from cannabis displayed a high percentage genome alignment to currently recognized pathogenic Fusarium species infecting other crops. This may suggest that horizontal transmission of the pathogens has occurred between these crops, potentially through air, soil, or seed-borne inoculum. In addition, analysis of secondary metabolites and toxin production in the Fusarium species affecting cannabis indicated they have the potential to produce several mycotoxins, including trichothecenes, fumonisin, zearalenone, beauvericin and culmorin. Further epidemiological and in planta studies are needed to establish the extent to which horizontal spread of Fusarium species from horticultural and field crops to cannabis plants is occurring and the impact this can have on post-harvest quality and mycotoxin production. Studies on genetic changes that may be occurring in the Fusarium species as they adapt to cannabis as a host would provide evolutionary insights into the pathogenicity of this complex, versatile and important group of plant pathogens.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".