Weed Interference, Pulse Species, and Plant Density Effects on Rotational Benefits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pulse crop management can increase pulse yields and N fixation, but the effects of previous pulse crop management on subsequent crop performance is poorly understood. Field studies were conducted at three locations, in the Parkland region of Alberta, Canada, between 2004 and 2006. Tannin-free faba bean, narrowleaf lupin, and field pea were planted at 0.5, 1.0, 1.5, and 2.0 times the recommended pulse planting density (PPD), with or without barley as a model weed. Faba bean produced the highest seed yields in higher precipitation environments, whereas pea produced the highest seed yields in lower precipitation environments. Lupin seed yields were consistently low. In the absence of weed interference, faba bean, pea, and lupin N-fixation yields ranged from 70 to 223, 78 to 147, and 46 to 173 kg N ha−1, respectively. On average, faba bean produced the highest N-fixation yield. The absence of weed interference and a high PPD increased pulse seed and N-fixation yields. Quality wheat crops were grown on pulse stubble without additional N fertilizer in some site–years. Management practices that increased N fixation resulted in only marginal subsequent wheat yield increases. Subsequent wheat seed yield was primarily influenced by pulse species. Pea stubble produced 11% higher wheat yields than lupin stubble but only 2% higher wheat yields than faba bean stubble. Consistently high wheat yields on pea stubble may be attributed to synchronized N release from decomposing pea residues with subsequent crop N demand and superior non-N rotational benefits.
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.
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 | 0.001 | 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) | 0.000 | 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