Selecting Cover Crop Mulches for Organic Rotational No‐Till Systems in Manitoba, Canada
Bibliographic record
Abstract
In western Canada, limited research has been conducted on reduced‐tillage grain production systems managed organically. The objective was to select cover crop mulches for an organic rotational no‐till system in Manitoba. A 2‐yr field study (2010–2011, and repeated 2011–2012) was conducted in Carman, MB, Canada. In the cover crop year, 10 different combinations of cover crop species were seeded in the spring, in pure stand or in mixtures, and rolled using a roller‐crimper in mid‐summer, at the flowering stage. These rolled mulches were then left on the soil surface over the fall and winter. The following spring, spring wheat (Triticum aestivum L.) was seeded directly into these mulches (no‐till). Mulches with hairy vetch (Vicia villosa Roth) showed the most promising results. Cover crop treatments with vetch had the highest mulch biomass in September of the cover crop year (9.1–10.7 Mg ha−1), and in the following spring (6.0–7.6 Mg ha−1) and provided the best weed control. In late fall of the cover crop year, N content of mulches with vetch reached high levels (308 kg N ha−1 on average), and high amounts of N (93–164 kg N ha−1) were released from these mulches over winter. Organic spring wheat no‐till planted into mulches with vetch produced yields comparable to regional conventional average yields. Mulches with vetch used in an organic rotational no‐till system reduced the need for tillage for a period of 1.5 to 2 yr without affecting yields of organic spring wheat.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".