Cover Crop Effects on Nitrogen Availability to Corn following Wheat
Bibliographic record
Abstract
Maximizing the environmental and economic benefits of cover crops partially depends on an accurate estimate of the N fertilizer requirement of subsequent crops. Four trials involving cover crop, tillage, and N rate variables were conducted from 1992 to 1995 in southcentral Ontario on well‐drained Typic Hapludalf soils. Rye (Secale cereale L.), oilseed radish [Raphanus sativus (L.) var. oleiferus Metzg (Stokes)], oat (Avena sativa L.), and red clover (Trifolium pratense L.) cover crops were established after winter wheat (Triticum aestivum L.) to evaluate their effects on soil NO3–N levels as well as subsequent corn (Zea mays L.) grain yield response at fertilizer rates of 0 and 150 kg N ha−1. Corn response to cover crops was compared in autumn plow and no‐till tillage systems. Within no‐till, autumn vs. spring chemical kill for red clover and rye was also evaluated. Although red clover biomass N yields were usually at least double those with other cover crops, all cover crops were equally effective at lowering residual soil NO3–N concentrations following wheat harvest. Presidedress NO3–N concentrations after autumn‐killed or plowed red clover were at least 24% higher than after any other cover crop. Grain corn yield responses indicated that red clover substantially enhanced N availability to corn in both autumn plow and no‐till systems, but that oilseed radish, oat, and rye cover crops did not enhance N availability to succeeding corn, compared with the no‐cover treatment, in either tillage system. Furthermore, the presidedress NO3–N test reliably estimated N fertilizer requirements of corn following all cover crop systems except spring‐killed red clover.
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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) | 0.000 | 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) | 0.001 | 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".