Endophytes in Cannabis sativa: Identifying and Characterizing Microbes with Beneficial and Detrimental Effects on Plant Health
Bibliographic record
Abstract
The roles of endophytes in Cannabis sativa (cannabis, hemp) remain poorly explored. While in vitro studies suggest that there can be several benefits, such as plant growth promotion and protection against pathogens, more in planta studies are needed. This review summarizes the bacterial and fungal endophytes previously reported in tissues of C. sativa and discusses the factors influencing their presence, as well as their potential beneficial and detrimental effects. Using genome sequencing and culture-based approaches, we describe the microbial diversity in hydroponically cultivated cannabis plants at several developmental stages. These include mother plants, cuttings, vegetative and flowering plants, and tissue-cultured plantlets. Microbes that were present include fungal, yeast, and bacterial endophytes found in roots, stems, leaves, inflorescences, and seeds. These may have originated from the growing substrate or be transmitted through vegetative propagation. Notable endophytes included Rhizophagus irregularis (a mycorrhizal fungus), Penicillium chrysogenum (an antibiotic producer), and various endophytic yeast species not previously described in C. sativa. Endophytes representing potential plant pathogens, such as Fusarium oxysporum, are also present within cannabis tissues, which can negatively impact plant health. Using scanning electron microscopy, we observed that fungal propagules are present within pith parenchyma cells and xylem vessel elements in stem tissues, illustrating for the first time the in situ localization and distribution of endophytes in cannabis vascular tissues. The mechanism of spread through xylem vessels likely contributes to the spread of endophytes within cannabis and hemp plants. Further research is required to validate the roles of endophytes in cannabis and hemp plants grown under commercial production conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".