Fall-seeded cover crops after dry bean and potato in Southern Alberta
Bibliographic record
Abstract
Dry bean (Phaseolus vulgaris L.) and potato (Solanum tuberosum L.) usually provide insufficient plant residue cover after harvest to protect the soil from wind erosion. Experiments were conducted at the Lethbridge Research Centre to determine the potential beneficial effects of planting cereal cover crops after Russett Burbank potato, which is harvested in late September or October, and dry bean, which is harvested in mid- to late September at Lethbridge, Alberta. Annual cereals planted after potato provided insufficient ground cover to protect the soil from erosion in the fall or spring. Winter annual cereals after potato and dry bean and annual cereals after dry bean usually provided enough residue in the spring (> 30% ground cover). However, winter cereals killed with glyphosate just before seeding spring wheat (Triticum aestivum L.) consistently reduced wheat yield. Reductions in available N and soil moisture due to winter annual cereals were small, and likely did not reduce wheat yield. None of the cover crops provided enough ground cover to reduce weed density. Additional research is required to assess the benefits of seeding annual cereals after early-maturing potato varieties and after dry bean, which matures earlier at lower elevations in southern Alberta, with more heat units. Key words: Fall rye, ground cover, soil erosion, winter triticale
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".