Nutrient Uptake and Leaching from Soil Amended with Cattle Manure and Nitrapyrin
Bibliographic record
Abstract
We investigated whether nitrification inhibitor nitrapyrin can reduce nutrient leaching and increase nutrient uptake by corn (Zea mays L.) in cattle manure amended soil. Amendments included non-amended check (CK), urea (Urea), REG (manure from cattle fed barley grain), and DDGS (manure from cattle fed 60% dried distillers grains with solubles), co-applied with or without nitrapyrin and leached or unleached with water. Nitrapyrin reduced (P < 0.01) leaching of nitrate by 56, 32, and 24% from DDGS, REG, and Urea treatments, respectively, and also reduced (P < 0.05) leaching of phosphate (58%), potassium (39%), calcium (39%), and magnesium (39%) from DDGS treatment. While nitrapyrin reduces the rate of ammonium conversion to nitrate, higher magnesium and phosphate levels in DDGS-amended soil favor struvite formation and reduce their leaching. Corn biomass and nutrient uptake were higher (P < 0.01) in DDGS and Urea than CK and REG treatments, but remained unaffected by nitrapyrin. The benefits of nitrapyrin should be further investigated under field conditions.Abbreviations: DCD, dicyandiamide; DDGS, dried distillers grains with solubles; NI, nitrification inhibitor; TP, total P; TN, total N.
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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) | 0.001 | 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".