The Role of Jasmonates in Modulating Growth, Trichome Density, and Cannabinoid Accumulation in Cannabis sativa L.
Why this work is in the frame
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Bibliographic record
Abstract
Jasmonates have emerged as a prominent elicitor for enhancing trichome development and cannabinoid production in Cannabis sativa L. (cannabis). These glandular trichomes synthesize and store important cannabinoids, including tetrahydrocannabinol (THC) and cannabidiol (CBD), which determine the yield, potency, and quality of cannabis flowers. Methyl jasmonate (MeJA) acts through the COI1–JAZ–MYC signaling pathway to upregulate genes associated with trichome initiation and cannabinoid precursor formation. Evidence suggests that moderate MeJA concentrations (typically 50–100 µM) can effectively boost trichome density, elevate hexanoyl-CoA availability, and modestly enhance key biosynthetic enzyme activities, ultimately increasing THC and CBD content. However, higher methyl jasmonate doses can amplify these benefits, yet pose a risk of excessive vegetative stunting, highlighting the crucial trade-off between enhancing cannabinoid potency and maintaining overall biomass yield. Interaction with hormones like gibberellins, salicylic acid, and ethylene further shapes the plant’s stress responses and secondary metabolism. Application in controlled environments, such as greenhouses or vertical farms, shows promise for enhancing resin production while minimizing biomass loss. In outdoor conditions, the application may offer additional defense benefits against pests and pathogens. These responses can vary depending on the cultivar, underscoring the importance of cultivar-specific optimization. As demand for high-cannabinoid cannabis products continues to grow and agrochemical options remain limited, leveraging MeJA treatments offers a practical, non-genetically modified approach to optimize yield, quality, and resilience in cannabis cultivation.
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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) | 0.000 | 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) | 0.000 | 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 it