Early detection of onion neck rot disease in Manitoba
Bibliographic record
Abstract
Neck rot caused by the fungus Botrytis allii Munn. is one of the most devastating diseases of onions (Allium cepa L.), resulting in significant yield losses. This disease is latent in nature developing symptomless onion plants in the field with bulbs typically showing symptoms 1–2 months after harvest in the storage. Molecular studies were conducted to detect latent infections of Botrytis neck rot in the onion fields of Manitoba, Canada. Plant samples of onion cultivars ‘Redwing’ and ‘Pocono’ were collected every 10 days throughout the growing season, starting from planting until bulb harvesting during 2018, 2019, and 2020 from a research farm in Brandon, Manitoba, and plant samples of ‘Redwing’ were collected during 2019 and 2020 from a commercial vegetable farm in Portage La Prairie, Manitoba. The amplified DNA fragment of onion leaves and the neck region of collected samples were subjected to polymerase chain reaction using the Botrytis-specific primer pair BA2f/BA1r. Botrytis allii was detected on onion samples collected from the commercial farm as early as the end of June 2019 and 2020 when plants were at the 5–7 leaf stage. The majority of onion samples collected from the research farm also started testing positive for the pathogen from June (2019, 2020) and July (2018) onwards. This knowledge about the timing of infection in the field will be useful in helping farmers to develop and evaluate management strategies in the field, and also predict the storability and availability of quality bulbs for sale.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".