Nitrogen and phosphorus distribution in plant, soil, and leachate as affected by liquid hog manure and chemical fertilizers
Bibliographic record
Abstract
A 2 yr field study was conducted on a coarse-textured soil in Manitoba, Canada, to investigate the effects of liquid hog manure (LHM) and chemical fertilizer application on barley (2005) and red spring wheat (2006) yields, crop nutrient uptake, and nitrogen (N) and phosphorus (P) movement to the environment. The treatments were LHM applied at two rates as 22 000 L·ha−1 (2500 gal·ac−1, abbreviated as M2500) and 43 000 L·ha−1 (5000 gal·ac−1, abbreviated as M5000) and two rates of chemical fertilizer to match total N and P in LHM treatments, F2500 and F5000, along with an unamended control. The M5000 and M2500 treatments showed similar grain yield and N and P uptake. However, M5000 and M2500 significantly increased grain yield by 67% and 78%, respectively, compared with the control in 2005. In 2006, wheat grain yields from M2500 and M5000 were 71% and 86% greater than the control. In 2005, leachate NO3-N concentrations and leaching loads were higher with chemical fertilizers than M2500. In 2005, the apparent recovery of applied N as leachate was 35% and 23% in F5000 and F2500 treatments, whereas it was 6% and 7% of applied N in M5000 and M2500 plots, respectively. However, the application of M5000 resulted in P accumulation near the surface and may increase the potential risk of P loss with runoff. Our results show that applying LHM at moderate rates (M2500) may ensure desirable crop yields comparable to higher rates of nutrient application with minimal potential losses relative to higher rates.
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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 | 0.001 | 0.001 |
| 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".