The diverse mycoflora present on dried cannabis (<i>Cannabis sativa</i> L., marijuana) inflorescences in commercial production
Bibliographic record
Abstract
The objective of this study was to assess harvested dried inflorescences (buds) of cannabis (Cannabis sativa L., marijuana) for fungal presence and diversity. Samples from drying rooms of three licenced facilities in British Columbia were tested repeatedly during 2017–2019. A swab method was used, wherein sterile cotton swabs were gently swabbed over bud surfaces and directly streaked onto potato dextrose agar containing 140 mg L−1 streptomycin sulphate. Petri dishes were incubated at 21–24°C for 5–6 days and the fungal colonies that developed were recorded. The testing was repeated to provide >40 cumulative sampling times over a 2-year period. Representative colonies of each unique morphological type were identified to genus and species by PCR of the ITS1-5.8-ITS2 region of rDNA and sequence analysis. Among 34 different fungal species identified, the most prevalent were Penicillium (comprising 17 different species), followed by species of Cladosporium, Botrytis, Aspergillus, Fusarium, Talaromyces and Alternaria. All samples had several fungal species present and the number and composition varied at different sampling times and within different facilities. The swab method provided a qualitative assessment of viable mould contaminants on cannabis buds and reflected the diversity of mycoflora present, many of which are previously unreported. Fungi on cannabis buds may originate from spores released from diseased or decomposing plant materials, from growing substrates used in cannabis production, or as airborne contaminants in post-harvest trimming and drying rooms. Samples of dried buds exposed to electrobeam (e-beam) radiation treatment had no detectable fungal contamination when assessed using the swab method.
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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 | 0.001 |
| 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".