Legume cover crop as a primary nitrogen source in an organic crop rotation in Ontario, Canada: impacts on corn, soybean and winter wheat yields
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This study presents results from the first 5 years of an organic cropping trial in Ontario, Canada, where legume cover crops were the primary nitrogen source in a soybean-winter wheat/cover crop-corn rotation. Treatments included cover crop termination using moldboard plow (MP) or chisel plow (CP), a no-cover crop control under conventional production (CK-C), and four cover crops including summer-seeded crimson clover (CC, Trifolium incarnatum L.), summer-seeded hairy vetch (HV, Vicia villosa L. Roth), summer-seeded red clover (RC ss , Trifolium pratense L.), and frost-seeded red clover (RC fs ). Summer-seeding occurred after wheat harvest (July–August), and frost-seeding occurred in early spring (March–April). At cover crop termination, average aboveground cover crop biomass ranged from 5.9 to 8.1 Mg ha −1 , while accumulated biomass nitrogen ranged from 155 to 193 kg ha −1 . Corn grain yields were 11.6 Mg ha −1 for MP and 10.2 Mg ha −1 for CP tillage-termination method; and 13.3 Mg ha −1 for CK-C, 10.9 Mg ha −1 for RC fs , 10.6 Mg ha −1 for HV, 10.2 Mg ha −1 for CC, and 9.5 Mg ha −1 for RC ss . Organic winter wheat yields were nitrogen-limited, averaging 27% lower than CK-C. Winter wheat yields were 10–15% lower in the RC fs than in other summer-seeded cover crop treatments. Soybean yields were largely unaffected by the treatments. It was concluded that summer-seeded legume cover crops are an effective primary nitrogen source for corn, but not as effective for the winter wheat phase of the soybean-winter wheat-corn rotation.
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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 | 0.000 | 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 it