Biocontrol in practice in Canadian floricultural greenhouses
Bibliographic record
Abstract
Abstract The environment inside Canadian prairie greenhouses differs from greenhouses built in other northern latitude locations in terms of lighting, temperature, humidity, and photoperiod. Since the performance of biocontrol agents depends upon several interactive environmental variables, their effectiveness to control pests in a particular crop growing under certain climatic conditions does not directly translate to another crop or location. So, we analyzed research trials assessing the efficacy and compatibility of various biocontrol agents (Amblyseius cucumeris, Amblyseius cucumeris, Phytoseiulus persimilis, Encarsia formosa, Aphidius colemani, Aphidius ervi, and Steinernema feltiae) on key pests (Western flower thrips, two-spotted spider mites, greenhouse whiteflies, and aphids) of spring bedding plants grown in a commercial floricultural greenhouse. Were analyzed several compatible combinations of biocontrol agents and observed a significant reduction in pest densities and plant damage symptoms as compared to untreated control plants. The results demonstrate that P. persimilis controlled two-spotted spider mites successfully in calibrachoa crop. The combination of Amblyseius cucumeris and S. feltiae resulted in significantly better control of Western flower thrips than the use of Amblyseius cucumeris alone in sweet potato vine plants. The application of E. formosa and Amblyseius cucumeris individually reduced greenhouse whiteflies on calibrachoa plants as compared to control, but their combination performed better resulting in a significantly lower number of whiteflies on plants. Another combination of Aphidius colemani and Aphidius ervi controlled green peach aphids and foxglove aphids effectively on the pansy crop. The biocontrol agents were effective for managing a variety of pests in a commercial greenhouse setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".