Cannabis Seedlings Inherit Seed-Borne Bioactive and Anti-Fungal Endophytic Bacilli
Bibliographic record
Abstract
Throughout the hundreds of millions of years of co-evolution, plants and microorganisms have established intricate symbiotic and pathogenic relationships. Microbial communities associated with plants are in constant flux and can ultimately determine whether a plant will successfully reproduce or be destroyed by their environment. Inheritance of beneficial microorganisms is an adaptation plants can use to protect germinating seeds against biotic and abiotic stresses as seedlings develop. The interest in Cannabis as a modern crop requires research into effective biocontrol of common fungal pathogens, an area that has seen little research. This study examines the seed-borne endophytes present across 15 accessions of Cannabis grown to seed across Western Canada. Both hemp and marijuana seedlings inherited a closely related group of bioactive endophytic Bacilli. All Cannabis accessions possessed seed-inherited Paenibacillus mobilis with the capacity to solubilize mineral phosphate. Additionally, seeds were found to carry genera of fungal isolates known to be Cannabis pathogens and post-harvest molds: Alternaria, Penicillium, Cladosporium, Chaetomium, Aspergillus, Rhizopus, and Fusarium. Thirteen seed-borne endophytes showed antibiotic activity against Alternaria, Aspergillus, Penicillium, and Fusarium. This study suggests both fungal pathogens and bacterial endophytes that antagonize them are vectored across generations in Cannabis as they compete over this shared niche.
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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 | 0.000 |
| 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".