Short-term persistence of ammonium-N following pig manure application is greater with perennial forage grasses than annual crops
Bibliographic record
Abstract
A 2-yr study was conducted on a loamy sand soil to compare short-term persistence of ammonium-N in an annual (ACS) and a perennial (PCS) cropping system following pig manures application as a possible explanation for the reduced nitrate leaching from perennial forage grasses. In spring 2014 and 2015, nitrogen-based application rates of liquid (LPM) and solid (SPM) pig manure were broadcast on PCS and ACS plots with incorporation of the manures for ACS plots alone. Following manure applications, soil samples were taken at 0–15 and 15–30 cm depths seven times (2014) and six times (2015) over 2–3 wk period for ammonium-N and nitrate-N concentrations. Ammonium-N (0–15 cm) with LPM peaked 4 d after manure application in ACS (18–29 kg ha−1) and PCS (50–74 kg ha−1) in both years. In both years, persistence of ammonium-N at 7 d was 46%–77% in LPM-amended PCS and 8%–14% in LPM-amended ACS. Ammonium-N measured in SPM-amended ACS and PCS was low after manure application in both years. There was lower accumulation of nitrate-N in PCS than ACS of LPM- and SPM-amended treatments in both years. The greater persistence of ammonium-N in the LPM-amended PCS than ACS coupled with lower percentage increase in nitrate-N in the PCS may account for lower nitrate leaching previously observed for perennial forage grasses at the study location.
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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".