Agronomic benefits of alfalfa mulch applied to organically managed spring wheat
Why this work is in the frame
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Bibliographic record
Abstract
Field experiments were established at two locations in Manitoba in 2002 and 2003 to determine N contribution, moisture conservation, and weed suppression by alfalfa mulch applied to spring wheat (Triticum aestivum L). Mulch treatments included mulch rate (amount harvested from an area 0.5×, 1× and 2× the wheat plot area), and mulch application timing (at wheat emergence or at three-leaf stage). Positive relationships were observed between mulch rate and wheat N uptake, grain yield, and grain protein concentration. At Winnipeg, the 2× mulch rates (3.9 to 5.2 t ha -1 ) produced grain yields equivalent to where 20 and 60 kg ha -1 of ammonium nitrate-N was applied in 2002 and 2003, respectively. Where mulch and ammonium nitrate produced equivalent grain yield, grain protein in mulch treatments was often higher than where chemical fertilizer was used. N uptake was also observed in the following oat (Avena sativa L.) crop. The highest mulch rate (2×) produced higher N uptake and grain yield of second-year oat compared with ammonium nitrate treatments. N use efficiency of mulch-supplied N by two crops over 2 yr [calculated as (treatment N uptake – control N uptake)/total N added] was between 11 and 68%. Mulch usually suppressed annual weeds, with greater suppression with late- than early-applied mulch. Increased soil moisture conservation was observed with high mulch rates (≥ 4.3 t ha -1 ) at three sites. Alfalfa mulch holds promise for low-input cropping systems when used on wheat at the 2× rates. Key words: Legume N, low-input farming, integrated weed management, wheat protein
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it