Is Deoxynivalenol Contamination a Serious Problem for Oat in Eastern Canada?
Bibliographic record
Abstract
To assess the severity of deoxynivalenol (DON) contamination in oat (Avena sativa L.) grain from infection of Fusarium head blight in eastern Canada, DON were determined for 3243 oat grain samples, involving 160 oat genotypes tested in 87 year–location combinations in Quebec and Atlantic Canada (Maritimes) oat registration and recommendation trials from 2008 to 2015. Analysis of the data led to the following findings. First, there are repeatable genetic differences in DON contamination. Relatively resistant cultivars (e.g., ‘CDC Dancer’) and susceptible cultivars (e.g., ‘AC Rigodon’) were identified. Genotypes better than CDC Dancer or worse than AC Rigodon were also identified. Second, cultivars with less DON contamination tended to have thinner hulls, i.e., greater groat percentage. Third, oat grain produced in Quebec and Maritimes was generally safe for use as feed or food, according to the Canadian permissible DON limits. In about 16% of the trials, however, the grain may not be suitable for making infant food according to the EU limit. Using a resistant cultivar such as CDC Dancer can reduce this risk to 10%, while using a susceptible cultivar such as AC Rigodon can increase the risk to 21%. Breeding for Fusarium head blight resistance, as measured by less DON contamination, should be a component in oat breeding for the region.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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".