Wheat Production in the High Winter Stress Climate of the Great Plains of North America—An Experiment in Crop Adaptation
Bibliographic record
Abstract
ABSTRACT The traditional winter wheat (Triticum aestivum L.) production area on the North American Great Plains extended as far north as southern Alberta, Canada. This paper reviews a research and development program initiated with the objective of expanding production north and east into higher winter stress areas of the Canadian prairies. Winter survival was considered the main limitation to production in this region. However, the widespread adoption of no‐till seeding into standing stubble for snow trapping has proven to be a successful method of overwintering wheat if cold hardy cultivars are grown using recommended management practices. Plant breeding improvements have increased production potential and winter wheat has become western Canada's third largest wheat class. Average commercial yields of 149, 125, and 118% of spring wheat in Manitoba, Saskatchewan, and Alberta, respectively, have demonstrated the high yield potential that can be realized while employing environmentally sustainable crop management practices. In light of current environmental concerns, changing weather patterns, diminishing world wheat reserves, and an ever increasing global population to feed, one would assume that winter wheat production in western Canada would be widely embraced. However, marketing obstacles and difficulties inserting winter wheat into rotations, both of which have a direct influence on farmers’ net returns, remain to be overcome for this potential to be fully realized.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".