Biomass yield from an old grass field as affected by sources of nitrogen fertilization and management zones in northern areas
Bibliographic record
Abstract
The efficiency of municipal biosolids (MB) and liquid swine manure (LSM) as fertilizers for old grass fields used for biomass production remains to be determined in northern areas. We determined the response of a 7 yr old grass field to organic and mineral N fertilization in two management zones. Soil and crop spatial variability was characterized, and two management zones were defined using soil electrical conductivity (EC). Nitrogen was applied at 160 kg total N ha−1 for 3 yr as MB, LSM, or mineral fertilizer (M) along with an unfertilized control. Seasonal dry matter (DM) yields were 61% with no N applied, 87% with MB, and 95% with LSM of that with M. The apparent N recovery with LSM (38%) and MB (27%) was less than with M (51%). Management zones did not differ in responses of DM yield and apparent N recovery to fertilization treatments. Fertilization treatments affected the number of species and the contribution of the main species to DM yield. We concluded that MB and LSM are valuable sources of N for biomass production from old grass fields in northern areas and EC-defined management zones are unlikely to improve N management in similar situations.
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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 | 0.000 | 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".