Nitrogen content of pea‐based cover crop mixtures and subsequent organic corn yield
Bibliographic record
Abstract
Abstract Organic growers rely heavily on manure additions to meet corn ( Zea mays L.) nitrogen (N) needs. Considering the limited availability of farmyard manure and its increasing cost, the use of cover crop mixtures may help in addressing this challenge. The impact of fall‐seeded cover crops with or without pelletized poultry manure application on corn yield and N dynamics was investigated at three sites in Québec, Canada. Cover crop treatments consisted of field pea ( Pisum sativum L.) in a pure stand, 2‐, 6‐, and 12‐species pea‐based mixtures, and a weedy control without cover crops. Nitrogen content of shoot biomass was the greatest for the pure stand of field pea at Augustin17 (157 kg N ha –1 ), and for the pure stand of field pea and the 2‐species mixture at Augustin18 (average of 109 kg N ha –1 ) and Barthelemy17 (average of 171 kg N ha –1 ). Nitrogen content of root biomass averaged 13 kg N ha –1 . Cover crops increased organic corn grain yield by 28% compared to a weedy control. Corn grain yield was similar following the pure stand of field pea and the mixtures of 2 and 12 species, showing no clear advantage of using mixtures instead of a pure stand of field pea regarding N supply and corn yield. Corn yield increased by 10% with poultry manure application irrespective of the cover crop treatments. These results indicate that the use of cover crops, either a pure legume or legume in mixture, could contribute to organic grain corn yield.
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How this classification was reachedexpand
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) | 0.002 | 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 teacher head, 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".