Nitrogen dynamics in soil amended with composted cattle manure
Bibliographic record
Abstract
The amount and pattern of plant-available nitrogen (N) release from composts are variable and not well-defined. We used a 425-d canola (Brassica napus L.) bioassay to follow the release of N from eight composted cattle manures applied to soil at 20 g kg-1. Two stockpiled manures, one inorganic fertilizer and an unamended control were also included for comparison. Eight consecutive 30-d growth cycles were conducted in a controlled environment chamber (20°C) and plant N uptake was measured. Total N uptake was greatest from the N fertilizer and least from the wood-chip bedded manure. Addition of compost increased N uptake by 27–99% compared with that in the control. Nitrogen uptake from compost was directly proportional to its inorganic N content (r2 = 0.98; P < 0.0001) showing that the initial inorganic N content of compost, analyzed prior to its application can be used to predict plant available N. In seven of the eight composts studied, less than 5% of organic N was mineralized over 425 d, suggesting that little of the organic N in compost becomes available in the year of application. Compost is a valuable organic amendment, but co-application of N fertilizer is recommended to supply adequate N and optimize the benefits of compost for crop growth. Key words: Plant-available nitrogen, compost, nitrogen mineralization, beef manure
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".