Wheat and Cereal Rye Inter-Row Living Mulches Interfere with Early Season Weeds in Soybean
Bibliographic record
Abstract
Rapid growth of cool-season weeds in the spring exacerbates weed interference during early soybean (Glycine max (L.) Merr.) establishment in northern climates. This study tested the utility of spring-seeded inter-row living mulches in soybean for early season weed suppression using volunteer canola (Brassica napus L.) as a representative model weed species. The effects of the presence or absence of spring wheat (Triticum aestivum L.) or winter cereal rye (Secale cereale L.) living mulches (mulch type) that had been seeded simultaneously with soybean grown using 38 or 76 cm row spacing (spatial arrangement) and the presence or absence of herbicides used for mid-season mulch termination (herbicide regime) were evaluated in three environments in Manitoba, Canada, in 2013 and 2014. Soybean yield was similar in the presence and absence of the living mulches. In the environment that received the lowest precipitation (Carman 2013), the mulches terminated with post-emergence glyphosate resulted in a 55% greater soybean yield compared to the mulches that remained live throughout the growing season. Inter-row mulches that had been living or terminated mid-season reduced volunteer canola seed production by about one-third (up to 9000 seeds m−2). This study demonstrates the utility of wheat or cereal rye inter-row living mulches for enhanced interference with weeds during early soybean establishment.
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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) | 0.000 | 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 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".