Mineralization of organic nitrogen from farm manure applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study aimed to quantify the amount of nitrogen (N) mineralized from the organic fraction of farm manures under field conditions. Nine different farm manures were stripped of their ammonium‐N content prior to soil incorporation and establishment of ryegrass at two sites in England. Grass N uptake and nitrate‐N leaching were measured for five consecutive seasons and compared with an untreated control, with the sum of N uptake + leaching (net of the control) used as an estimate of the amount of organic N mineralized from the applied manures. The amount mineralized was related to thermal time (cumulative day degrees above 5 °C – CDD ), with two distinct phases – an initial phase up to 2300 CDD ( c .18 months under UK climatic conditions) where mineralization proceeded at rates ranging between 0.005 and 0.027%mineralized/ CDD and a slower phase at >2300 CDD , where rates were negligible at <0.001%mineralized/ CDD . There was no difference between soil types, both being light‐textured (<20% clay), but there were differences between manure types depending on the manure C: organic N ratios. For pig slurry and layer manure (C:organic N = 9–12:1), up to 70% of the organic N was mineralized, compared to 10–30% mineralization from the cattle slurry and straw‐based farmyard manures‐ FYM s (C:organic N = 10–21:1).The relationships derived provide a useful tool for predicting both the amount and timing of manure N release, with important implications for both crop N uptake and leaching risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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 it