Management of Manure Nitrogen Using Cover Crops
Bibliographic record
Abstract
The experiment was conducted to determine whether cover crops reduce N losses of fall‐applied liquid hog manure and whether sequestered N by cover crops is “transferred” to subsequent corn (Zea mays L.). Two locations (Elora and St. Mary's) in southern Ontario from 2003–2004 were used consisting of six cover crop treatments (red clover [RC] [Trifolium pratense L.] fall‐killed, RC spring‐killed, oat [Avena sativus L.] fall‐killed, oilseed radish [Raphanus sativus L.] fall‐killed, perennial ryegrass [Lolium perenne L.] spring‐killed, and no‐cover crop), and three target manure rates (0, 100, and 200 kg N ha−1). Non‐legume cover crops positively responded to fall manure application, where biomass increased by 50 to 130%. Red clover biomass increased 0 to 25% at higher manure rate application. A similar trend was found with plant N uptake. Generally applied manure N recovery was low (0–25%) in all the cover crops. Ammonia losses from manure applications to RC was higher than other cover crops due to inability to incorporate manure. During the period corresponding with corn N uptake, non‐legume cover crop impact on soil mineral N did not differ from the no cover control. When non‐legumes were used as cover crops following manure application, corn biomass, grain yield, and N uptake were equivalent to no cover crop treatment. However, when RC was used as a cover crop, above corn parameters were equivalent for all manure application rates and greater than the no‐cover crop treatment, so “transfer” of manure N could not be confirmed.
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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 | 0.000 | 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) | 0.001 | 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".