Effects of Glomus intraradices and onion cultivar on Allium white rot development in organic soils in Ontario
Bibliographic record
Abstract
Commercial products containing formulations of the vesicular–arbuscular mycorrhiza (AM) Glomus intraradices were assessed for their effectiveness in suppressing Allium white rot (WR) on onions (Allium cepa) in organic soils and compared with the fungicide Folicur 3.6F (430 g a.i./L tebuconazole) under field conditions. The trials were conducted during 2000 and 2001 in commercial onion fields in the Holland–Bradford Marsh in Ontario. The AM product MIKRO-VAM, which is used in transplanted onions, reduced the incidence of WR by almost 50%compared with the untreated control and was comparable with that of the fungicide treatment, Folicur 3.6F, applied according to label recommendations. This is one of the few studies to demonstrate season-long disease suppression with AM under field conditions, and it is the first to show that the AM products can be as effective as a fungicide treatment under commercial production practices. A consistent difference in incidence of WR was found between the cultivars ‘Hoopla’ and ‘Fortress’ onions. ‘Hoopla’ was more susceptible to WR than ‘Fortress’ in 10 of 13 field trials and all trials where WR incidence on ‘Hoopla’ was 4%. There was a significant negative correlation between disease incidence and AM root colonization, suggesting that AM colonization was an important factor in the reduction of WR observed in this study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".