Nitrogen- and phosphorus-based applications of cattle manure and compost for irrigated cereal silage
Bibliographic record
Abstract
Land application of livestock manure has caused concern about excess nutrients in soil and the potential risk to water quality. Application of manure based on crop-nutrient requirements is considered a beneficial management practice. A field study was conducted to assess the feasibility and impact of crop-based N and P application rates of cattle (Bos taurus) manure and compost for crop productivity and accumulation of extractable soil N and P. The 6-yr (2002-2007), small-plot field study included 10 amendments: control (CONT), annual synthetic fertilizer N (F-N), annual synthetic fertilizer P (F-P), annual synthetic fertilizer N plus P (F-NP), annual N-based manure (M-N), annual P-based manure (M-P), three times the P-based manure once per 3 yr (M-3P), annual N-based compost (C-N), annual P-based compost (C-P), and three times the P-based compost once per 3 yr (C-3P). Amendments were arranged in randomized complete block design with five replicates and applied based on annual soil testing and nutrient recommendations. The test crops were triticale (× Triticosecale rimpaui Wittm.) and barley (Hordeum vulgare L.) silage managed under irrigation. Dry matter yields for CONT and F-P were significantly smaller than for the other treatments. There were generally no significant differences among the six organic and F-NP amendments. Apparent N recovery (ANR) was greatest for F-NP (45%) and F-N (41%), followed by the P-based organic amendments (26-34%), M-N (15%), and smallest for C-N (10%). Apparent P recovery (APR) was greatest for F-NP (30%) and smallest for M-N (6%) and C-N (4%). The APR for the P-based organic amendments ranged from 14 to 22%. Application of the amendments did not result in the accumulation of excess nitrate N in the soil profile. The M-N and C-N amendments applied for 6 yr increased extractable P in the 0- to 0.15-m soil layer from 12 mg kg -1 to 121 and 156 mg kg -1 , respectively. Crop productivity and soil nutrient responses indicated that assumptions made for P and N availability in manure and compost were reasonably accurate. Based on the results, P-based application of manure or compost can achieve optimum crop yield and prevent nutrient build-up in soil. Under the conditions of this study, the amount of land required to accommodate P-based application would be five to seven times more for manure and eight to ten times more for compost compared with N-based application.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".