Dairy Cattle Manure Improves Soil Productivity in Low Residue Rotation Systems
Bibliographic record
Abstract
Mineral fertilizer alone may not sustain soil productivity in cropping systems that return little crop residues to the soil, unless additional organic residues and/or manure is applied regularly to the soil. The objective of the present study was to assess the long‐term effects of mineral fertilization (No fertilizer, PK, and NPK) and manure addition (0 and 20 Mg ha −1 yr −1 ) on soil physical and chemical properties and crop yields in a cereal rotation with removal of crop residues. After 28 yr, soil organic carbon (SOC) declined by −0.25 g C kg −1 yr −1 and total nitrogen (TN) by −0.025 g N kg −1 yr −1 with balanced mineral fertilization (NPK, no manure), comparable to the control (no manure, no fertilizer). In addition, mean weight diameter (MWD) of water‐stable aggregates was lower with balanced mineral fertilization than in the control. In contrast, long‐term application of manure significantly increased water‐stable macroaggregates, potentially mineralizable nitrogen (PMN), and soil preseeding NO 3 –N levels. Corn yield and N uptake were increased by mineral fertilization compared to the control, and manure application increased corn yield by 89 and 87% and corn N uptake by 110 and 79% in 2005 and 2006, respectively. Increased corn yield in manured plots was attributed to the residual manure‐derived nutrients and to improved soil properties. Mineral fertilizer alone could not sustain soil productivity in intensive low‐residues cropping systems.
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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 | 0.000 |
| 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 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".