Biological Control of Weeds- Potential Candidates Evaluation of Fungal and Bacterial Agents for Biological Control of Canada Thistle
Bibliographic record
Abstract
From a collection of 287 pathogenic fungi that were isolated from Canada thistle growing in the Canadian prairies, a total of 71 fungal isolates were evaluated for biologi-cal activity on Canada thistle roots using an agar mat bioassay. In addition, the bacterial agent, Pseudomonas syringae pv. tagetis (PST) was evaluated as a biocontrol agent on the weed. The fungal genera examined were: 8 Phoma, 12 Phomopsis, 14 Colletotrichum, and 37 Fusarium. Eighteen isolates were selected for biological control because they caused significant reductions in shoot emergence and root weight, chlorosis, and/or death of Canada thistle. Efficacy of 2 fungal isolates was confirmed in greenhouse studies using infested barley grains as a granular inoculant. An application rate between 250 to 500 g/m2 was required to kill Canada thistle in 4 to 6 weeks. Application of PST in the organosilicone surfactant Silwet L-77 caused chlorosis and stunting, but fresh or dry weights were not significantly affected after 5 weeks, when compared to PST alone, Silwet alone and water alone. However, flowering was inhibited when treated with PST and Silwet L-77. When sub-lethal rates of glyphosate were applied at 0.1 X recommend-ed rated, there were significant reductions in fresh and dry weights and greater apical chlorosis, when compared to the low rate of glyphosate alone, PST and Silwet and PST alone. Further evaluations with the fungal pathogens and PST include rate and time of application, various formulations, applications with low rates of herbicides, and multiple pathogen synergies.
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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 | 0.000 | 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) | 0.001 | 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".