Legume Cover Crops Provide Nitrogen to Corn During a Three‐Year Transition to Organic Cropping
Bibliographic record
Abstract
Crop yields are often lower during the “three‐year transition” period from conventional to organic production systems. This paper presents the results from an organic cropping trial which used summer‐seeded legume cover crops as the primary N source for corn in a corn (Zea mays L.)‐ soybean (Glycine max (L.) Merr)‐ winter wheat (Triticum aestivum L.) rotation in southwestern Ontario, Canada. The cover crop treatments included crimson clover (CC, Trifolium incarnatum L.), hairy vetch (HV, Vicia villosa Roth subsp. villosa) and red clover (RC, Trifolium pratense L.). Also included were a conventional control (CKC, with synthetic fertilizers) and an organic control (CKO, no synthetic fertilizer) without cover crops. The objectives were to determine the N and C accumulation in the legume above‐ground biomass; the impacts of cover crops on residual soil mineral N (RSN) in late fall and on crop grain yields during the 3‐yr transition period. Compared to CKC, cover crops left less RSN (51 kg N ha−1 less) in the soil profile (0–90 mm) by late November. In early May before plow‐down, significantly more above‐ground biomass was found for HV (3313 kg C ha−1, 240 kg N ha−1) and RC (2766 kg C ha−1, 199 kg N ha−1) than for CC (1787 kg C ha−1, 119 kg N ha−1). In the three‐year transition period, average corn grain yields were 13.1 and 13. 0 Mg ha−1 for HV and RC which were similar (P = 0.05) to CKC (13.8 Mg ha−1) but greater than CKO (6.4 Mg ha−1) (P = 0.05). This study highlighted the effectiveness of using HV or RC as a primary N source for organic corn production in southwestern Ontario. Core Ideas Summer seeded legume cover crops decreased residual soil N in late fall. Summer seeded hairy vetch & red clover grow well in the following spring. Summer seeded hairy vetch & red clover were good N sources for corn in SW Ontario.
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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".