Nitrogen loss on tile-drained Mollisols as affected by nitrogen application rate under continuous corn and corn-soybean rotation systems
Bibliographic record
Abstract
Helmers, M. J., Zhou, X., Baker, J. L., Melvin, S. W. and Lemke, D. W. 2012. Nitrogen loss on tile-drained Mollisols as affected by nitrogen application rate under continuous corn and corn-soybean rotation systems. Can. J. Soil Sci. 92: 493–499. Nitrate-nitrogen (NO3-N) loss from production agricultural systems through subsurface drainage networks is of local and regional concern throughout the Midwestern United States. The increased corn acreage and the practice of growing continuous corn instead of a corn-soybean rotation system due to the increasing demand for food and energy have raised questions about the environmental impacts of this shift in cropping systems. The objective of this 4-yr (1990–1993) study was to evaluate the effect of nitrogen (N) application rate (0–168 kg N ha−1 for corn following soybean and 0–224 kg N ha−1 for corn following corn) on NO3-N concentration, NO3-N losses, and crop yields in continuous corn and corn-soybean production systems on tile-drained Mollisols in north central Iowa. The results show that NO3-N concentrations from the continuous corn system were similar to NO3-N concentrations from the corn-soybean rotation at equivalent N application rates.When extra N fertilizer (approximately 56 kg N ha−1) was applied to continuous corn than the corn-soybean rotation, this resulted in 14–36% greater NO3-N concentrations in subsurface drainage from the continuous corn system. While corn yield increased as N application rate increased, corn yields at the recommended N application rates (112–168 kg N ha−1) in the corn-soybean rotation were up to 3145 kg ha−1 greater than corn yields at the recommended application rates (168–224 kg N ha−1) in the continuous corn system. The corn-soybean rotation with recommended N application rates (168–224 kg N ha−1) appeared to be beneficial environmentally and economically.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".