Effect of harvest date on barley grain contamination with Fusarium spp. and deoxynivalenol in northeastern Ontario
Bibliographic record
Abstract
The effect of harvest date on the incidence of seed-borne Fusarium spp. and deoxynivalenol (DON) concentration in barley (Hordeum vulgare L.) was studied using three cultivars at three locations in Ontario in both 2004 and 2005. The profile of seed-borne Fusarium spp. was dominated by F. equiseti (Corda) Sacc., F. sporotrichioides Sherb., and F. poae (Peck) Wollenw., isolated from 4.4%, 3.3%, and 1.6% of the kernels, representing 39.3%, 29.4%, and 14.2% of the Fusarium pathogen population, respectively. Fusarium graminearum Schwabe and F. avenaceum (Fr.) Sacc. were each recovered from <1% of the kernels and represented 8.3% and 6.6% of the pathogen population, respectively. Other species, including F. acuminatum Ellis & Everh., F. culmorum (W.G. Sm.) Sacc., and F. semitectum Berk. & Rav., collectively occurred only on 0.2% of all kernels and represented <2% of the population. The incidence level of all Fusarium spp. increased from 6.9 to 13.9% when harvest was delayed. Of the commonly recovered species, only F. avenaceum and F. sporotrichioides levels increased with the delayed harvest, while other species did not follow a clear pattern. DON concentration in the harvested grain ranged from 0.20 to 0.28 mg kg‑1 with the five harvest dates, and was not statistically different. Significant differences in the incidence of all Fusarium spp. and in DON concentration were observed among cultivars, locations, and between the 2 yr of the study. The highest DON concentration observed in this study was 0.5 mg kg‑1, which is below the Canadian tolerance level of 1.0 mg kg‑1.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".