Stubble options for winter wheat in the Black soil zone of western Canada
Bibliographic record
Abstract
Irvine, B. R., Lafond, G. P., May, W., Kutcher, H. R., Clayton, G. W., Harker, K. N., Turkington, T. K. and Beres, B. L. 2013. Stubble options for winter wheat in the Black soil zone of western Canada. Can. J. Plant Sci. 93: 261-270. Winter wheat (Triticum aestivum L.) production has yet to reach its full potential in the Canadian prairies. Alternative stubble types are needed to help overcome the challenge of timely planting of winter wheat in late-maturing canola (Brassica napus L.) fields. A study was conducted in the prairie provinces of Canada to determine ideal stubble types for winter wheat and select spring cereals grown in the Black soil zone. Spring wheat (Triticum aestivum L.), canola, pea (Pisum sativum L.), barley grain or silage (Hordeum vulgare L.), and oat (Avena sativa L.) stubbles were established at four locations in western Canada. A new study area was established at each location for 3 yr. In the year following establishment, winter wheat, hard red spring wheat, barley, and oats were grown on each stubble type at each study area. Winter wheat and spring cereal crops often yielded best and had greater grain protein concentration on barley silage, pea, and canola stubbles relative to other stubble types. The yield and grain protein concentration of spring cereals was best when grown on pea stubble. Winter wheat production attributes varied most among site by crop combinations, and further investigation indicated the source of this variability may be from winter wheat plantings on canola and pea stubble. Among the optimal stubbles, less variable results were observed when winter wheat was grown on barley silage stubble, suggesting proper crop residue management would reduce the variability observed in canola and pea stubble. Our results suggest stubble alternatives to canola are available for winter wheat plantings in western Canada.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".