Sweet Clover Termination Effects on Weeds, Soil Water, Soil Nitrogen, and Succeeding Wheat Yield
Bibliographic record
Abstract
Farmers on the Canadian Prairies utilizing green manure sweet clover [Melilotus officinalis (L.) Lam.] are concerned about the increased risk of wind erosion when sweet clover is terminated by high soil disturbance methods. This study was conducted to determine if the merits of green manure sweet clover could be maintained in a reduced tillage system. Sweet clover was undersown in spring wheat (Triticum aestivum L.) in Year 1 and then killed at the 80% flowering stage in Year 2 by mowing at a 30‐cm height and removing topgrowth as hay, mowing at a 30‐cm height and leaving residues on the soil surface, partial soil‐incorporation with an offset disk, or complete soil‐incorporation with a moldboard plow. Mowed sweet clover where the topgrowth was removed as hay often had more weeds than the other treatments but mowed sweet clover with residues left on the soil surface had similar or fewer weeds than disked sweet clover. Soil water content was similar with all sweet clover termination methods. Sweet clover hay resulted in 7 to 19% less available soil N than all other sweet clover treatments but mowed and disked sweet clover had similar soil N levels. Soil N was 21 to 33% greater with plowed sweet clover than with all other termination methods. Wheat yields were similar with mowed, disked, and plowed sweet clover in one experiment but were 14% lower with mowed sweet clover in a second experiment. Farmers contemplating switching to conservation tillage can be encouraged by these results indicating that mowed sweet clover with residues left on the soil surface and disked sweet clover provided similar benefits to the crop production system.
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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".