Self‐regenerating black medic cover crop provides agronomic benefits at low nitrogen
Bibliographic record
Abstract
Abstract A black medic ( Medicago lupulina L.) cover crop is able to regenerate from seed annually and produce biomass at the end of each growing season, but its long‐term effectiveness on crop productivity, water use efficiency (WUE), and soil nutrient status within a no‐till cropping system is unclear. A field experiment was established in 2003 in Saskatchewan in a 3‐yr crop rotation [flax ( Linum usitatissimum L.)–oat ( Avena sativa L.)–wheat ( Triticum aestivum L.)]. Treatments included cover crop (black medic or no medic), and N fertilizer (20, 60, and 100% of recommended N) arranged in a split‐split plot design. Over 10 yr, medic aboveground fall biomass averaged 625 kg ha –1 (range 0–1,868 kg ha –1 ) and was greatest at the lowest N rate, 879 kg ha –1 . Medic increased grain yield at 20% N fertilizer; no effect was observed at higher N rates. Medic increased tiller density and kernel weight at 20% N, indicating that medic positively influenced the crop throughout the entire life cycle. Medic presence did not affect grain N or P status. Medic did not affect level of available soil N in fall but consistently increased level of soil available P. This extended to the 30–60 cm soil depth in the 100% vs. lower N rates, suggesting medic roots may have influenced P cycling. In oat stubble, medic increased spring soil water and WUE. In conclusion, black medic improved crop productivity at the low N rate but improved available soil P at all N rates, warranting further research.
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 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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".