Canadian Onion Production Depends on Fungicides International Pesticide Benefits Case Study No. 77, April 2013
Bibliographic record
Abstract
Onion is one of the most important vegetable crops produced in Canada with an annual production of 210,000 tons valued at $74 million. Canadian production of onions is centered on the muck soils in the eastern provinces of Ontario and Quebec. In 1952, a leaf spot and wilt disease (Botrytis leaf blight, BLB) caused by Botrytis squamosa was first recorded in Ontario where widespread injury to the foliage of yellow bulb onions occurred [1]. A three-year research program in the 1950s demonstrated that fungicides prevented an average loss of 15 % in onion yield [1]. Botrytis spores land on onion leaves and, in the presence of moisture, germinate and produce enzymes that kill leaf tissue. Botrytis leaf blight causes early death of the leaves and undersized mature bulbs. Severely affected onion fields may take on a blighted appearance with most leaves dead and dried out. Bulb size is reduced 50 % or more by botrytis leaf blight. In eastern Canada, the disease is generally present every year [2]. Since there is a premium price for large onions, loss of Botrytis leaf blight control can have large economic consequences [2]. B. squamosa overwinters as sclerotia on crop residues, or on the soil surface. In the
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".