A baseline survey of pest and beneficial insects in industrial hemp (<i>Cannabis sativa</i>) in central Alberta
Bibliographic record
Abstract
Alberta is the leading producer of industrial hemp ( Cannabis sativa L.) in Canada, accounting for approximately half of the hemp production in the country. However, as the industry continues to expand, research on the agronomic practices surrounding this niche crop remain limited—particularly in the areas of insect pest management and insect community surveys. To investigate temporal and spatial changes to potential pest and beneficial insect populations, insects were collected along two transects in central Alberta industrial hemp fields in 2021 and 2022. Overall, year and collection site did not affect insect abundance; however, transect location had a significant effect with more insect families identified at the crop edge compared to the interior. The major potential insect pests identified included Lygus spp. ( L. lineolaris, L. borealis, L. elisus), Melanoplus spp. ( M. bivittatus, M. femurrubrum, M. packardii, M. sanguinipes) and different species of leafhoppers (Cicadellidae). Several important families of natural enemies of insect pests were identified and included parasitoid wasps in Chalcidoidea, Braconidae, and Ichneumonidae; predatory flies from the families Dolichopodidae and Hybotidae; and other predators from the families Anthocoridae (i.e., minute pirate bugs; Orius insidious and Orius tristicolor), Chrysopidae (i.e., lacewings; Chrysopa chi, Chrysopa oculate, Chrysoperla carnea), Nabidae (i.e., damselbugs; Nabis spp.), Geocoridae (i.e., big-eyed bugs; Geocoris atricolor, and Geocoris bullatus), and various spiders. This survey establishes a baseline of potential pest and beneficial insects associated with industrial hemp in central Alberta, supporting future research on their impact on hemp yield and development of an integrated pest management program.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".