Managing Tile Drainage, Subirrigation, and Nitrogen Fertilization to Enhance Crop Yields and Reduce Nitrate Loss
Why this work is in the frame
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Bibliographic record
Abstract
Improving field-crop use of fertilizer nitrogen is essential for protecting water quality and increasing crop yields. The objective of this study was to determine the effectiveness of controlled tile drainage (CD) and controlled tile drainage with subsurface irrigation (CDS) for mitigating off-field nitrate losses and enhancing crop yields. The CD and CDS systems were compared on a clay loam soil to traditional unrestricted tile drainage (UTD) under a corn (Zea Mays L.)-soybean (Glycine Max. (L.) Merr.) rotation at two nitrogen (N) fertilization rates (N1: 150 kg N ha(-1) applied to corn, no N applied to soybean; N2: 200 kg N ha(-1) applied to corn, 50 kg N ha(-1) applied to soybean). The N concentrations in tile flow events with the UTD treatment exceeded the provisional long-term aquatic life limit (LT-ALL) for freshwater (4.7 mg N L(-1)) 72% of the time at the N1 rate and 78% at the N2 rate, whereas only 24% of tile flow events at N1 and 40% at N2 exceeded the LT-ALL for the CDS treatment. Exceedances in N concentration for surface runoff and tile drainage were greater during the growing season than the non-growing season. At the N1 rate, CD and CDS reduced average annual N losses via tile drainage by 44 and 66%, respectively, relative to UTD. At the N2 rate, the average annual decreases in N loss were 31 and 68%, respectively. Crop yields from CDS were increased by an average of 2.8% relative to UTD at the N2 rate but were reduced by an average of 6.5% at the N1 rate. Hence, CD and CDS were effective for reducing average nitrate losses in tile drainage, but CDS increased average crop yields only when additional N fertilizer was applied.
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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 | 0.001 | 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 it