Effects of planting date and earliness on deoxynivalenol contamination in barley under natural epidemic conditions
Bibliographic record
Abstract
Choo, T. M., Martin, R. A., Savard, M. E. and Blackwell, B. 2014. Effects of planting date and earliness on deoxynivalenol contamination in barley under natural epidemic conditions. Can. J. Plant Sci. 94: 1363–1371. Fusarium head blight, principally caused by Fusarium graminearum Schwabe, is a destructive disease of barley in many countries and it can result in mycotoxin contamination such as deoxynivalenol (DON) in the grain. An integrated management strategy is needed to mitigate the level of DON contamination in barley. Therefore, a study was initiated to determine if early planting and early-heading cultivars can be used to avoid severe DON contamination under natural epidemic conditions in the Maritimes. Twelve six-row barley cultivars were planted in a split-plot design with two planting dates (early vs. late) as main-plot units and cultivars as sub-plot units at the Harrington Research Farm in Prince Edward Island in 2007, 2008, 2010, 2011, and 2012. Grain samples from all experimental plots were contaminated with DON and one contained as high as 23.1 mg kg−1. Early planting frequently resulted in less DON contamination and higher yield than late planting. Days to heading was positively correlated with DON concentration only at late planting in 2007. The results of this study suggest that six-row barley should be planted early in the Maritimes to avoid a high level of DON contamination and a reduction in grain yield, and that use of early-heading cultivars may not be effective at reducing DON contamination while retaining high yield.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".