Pathogenicity of seedborne <i>Alternaria</i> and <i>Stemphylium</i> species and stem-infecting <i>Neofusicoccum</i> and <i>Lasiodiplodia</i> species to cannabis ( <i>Cannabis sativa</i> L., marijuana) plants
Bibliographic record
Abstract
Cannabis (Cannabis sativa L., marijuana) plants grown at indoor and outdoor production sites in British Columbia (BC) and Ontario with stem canker symptoms were sampled and affected tissues were surface-sterilized and plated onto potato dextrose agar. Isolates were identified by colony and spore morphology as well as PCR amplification and sequencing of the ITS1-ITS2 rDNA, beta-tubulin, and actin gene regions. The most frequently isolated fungi were Alternaria alternata, Neofusicoccum parvum, and Lasiodiplodia theobromae. In addition, A. alternata was recovered from cannabis inflorescences in BC as well as surface-sterilized hemp seed. Stemphylium vesicarium was isolated from hemp seeds for the first time. The pathogenicity of all these fungi to cannabis plants was confirmed by inoculation of leaves, stems, buds, rooted cuttings and mature plants. Disease ratings varied depending on both tissue type and pathogen. Both L. theobromae and N. parvum produced extensive stem cankers on mature cannabis plants as well as extensive lesions on leaves. All pathogens showed optimal colony growth in culture at 25–30°C. A comparison of the susceptibility of five cannabis genotypes to foliar infection by N. parvum indicated there were significant differences (p < 0.05) in lesion size, with some genotypes showing high susceptibility and others showing resistance. This is the first report of L. theobromae, N. parvum, A. alternata, and S. vesicarium causing stem canker and leaf spot symptoms on cannabis in Canada. The recovery of these fungi adds to the growing list of pathogens that cause infection and loss of quality in cannabis production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".