Entomopathogenic Fungi Effectively Control Phorodon cannabis Aphid Population in Cannabis sativa Plants
Bibliographic record
Abstract
The rapid expansion of the cannabis industry in Canada post-legalization has heightened the prevalence of pests, particularly the cannabis aphid Phorodon cannabis (P. cannabis), which poses significant threats to crop health. This study investigates the immediate effects of P. cannabis on Cannabis sativa (C. sativa) plants and explores biological control strategies utilizing entomopathogenic fungi. Fungal isolates of Beauveria bassiana and Metarhizium anisopliae were isolated from infected aphids, cultured, and characterized. Infection tests on aphids revealed that both fungi achieved 100% aphid mortality at high conidial concentrations (1 × 107 conidia/mL) by the 10th DAT, with Beauveria bassiana demonstrating better efficacy. In greenhouse trials on three cannabis varieties, B. bassiana effectively controlled aphid populations, keeping levels low and stable in infested plants treated with B. bassiana at the concentration of 1 × 107 conidia mL−1 (I-B) and infested plants treated with insecticide (I-I). Both I-B and I-I treatments maintained aphid populations near zero for nine weeks. In contrast, control plants showed significant aphid growth, with the Perseid variety being the most susceptible, followed by Congo Durban, while GCC exhibited the lowest susceptibility. Cannabinoid and terpene analyses revealed that treatment with insecticide substantially decreased the amount of produced cannabinoids and terpenes. In contrast, Beauveria bassiana-treated plants exhibited higher concentrations of key metabolites, including delta-9-tetrahydrocannabinolic acid and cannabidiolic acid, and total terpenes, compared to chemically treated plants, and in two out of three cultivars, these concentrations were higher than in control, untreated plants. The findings highlight Beauveria bassiana as an eco-friendly alternative for pest management that not only controls aphids effectively but also supports the biochemical quality of cannabis plants.
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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 | 0.001 | 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 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".