Tillage and weed management effects on forage production in a barley-red clover rotation
Bibliographic record
Abstract
Tillage and weed management practices used during the establishment year can likely affect for age yield during the subsequent production year(s). This study was conducted as part of a long-term experiment to determine the suitability of conservation tillage practices for red clover (Trifolium pratense L.) production on a Kamouraska clay from 1988 to 1995. Red clover was underseeded with spring barley (Hordeum vulgare L.) in cropping systems including different tillage (MP: fall moldboard plow; CP: fall chisel plow; NT: no-till) and weed management (intensive, moderate, minimum) treatments applied during the establishment year. Red clover dry matter yields and weed biomass were measured twice in the subsequent forage production year. Tillage had no effect on red clover yields in 3 out of 7 yr. Yields were 16% greater with NT in 1 yr and 52% with MP tillage in 3 yr compared with other tillage treatments. Weed response to tillage was consistent over years. Dicot weed biomass increased as tillage intensity was reduced. Monocot biomass was much less with NT than with MP or CP treatments. Red clover yield was 11% greater with intensive weed management, but this yield increase was not associated with differences in dicot or monocot biomass during the forage production year. Red clover yield gain with intensive weed management would need to be weighed against economical and environmental costs to determine the relevance of increased herbicide use in a short-term cereal/forage rotation. Key words: Red clover (Trifolium pratense L.), conservation tillage, no-till, forage legume
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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 | 0.001 | 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 | 0.000 | 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".