Integration of Conservation Tillage and Herbicides for Sustainable Dry Bean Production
Bibliographic record
Abstract
Development of conservation tillage practices for dry bean has lagged behind that of many other crops. A field study was conducted to determine the effects of various crop residues and herbicide treatments on weed management and dry bean yield within a zero-tillage system. Main plot treatments included wheat stubble, canola stubble, fall-seeded winter rye, fall-seeded spring rye, and a no-cover control. Subplot treatments included various preplant and POST herbicides. Wheat stubble, canola stubble, and winter rye residue provided sufficient ground cover to prevent soil erosion, and they effectively reduced weed density compared with the no-cover control in all years. Fall-seeded spring rye provided only partial soil-erosion protection and reduced weed density in only 1 of 3 yr. Dry bean emergence was 3 to 5 d slower in the crop residue treatments compared with the no-cover control, but crop density was not adversely affected. However, winter rye residue delayed dry bean maturity by 2 to 6 d. Fall-applied granular ethalfluralin followed by POST bentazon/imazethapyr or imazamox provided the most effective weed control. A sole POST imazamox application also provided good weed control when weed densities were reduced by winter rye residue or wheat stubble. Overall, results indicate that with suitable herbicide programs, similar yields were attained when dry bean was seeded directly into crop stubble or cover crop residues compared with the no-cover control. Information gained in this study will be used to encourage greater farmer adoption of conservation tillage practices for dry bean production on the Canadian prairies.Nomenclature: Bentazon, ethalfluralin, imazamox, imazethapyr, canola, Brassica napus L., dry bean, Phaseolus vulgaris L., rye, Secale cereale L., wheat, Triticum aestivum L
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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".