Integration of Cropping Practices and Herbicides Improves Weed Management in Dry Bean (<i>Phaseolus vulgaris</i>)<sup>1</sup>
Bibliographic record
Abstract
A field study was conducted to determine the combined effects of row spacing, plant density, and herbicides on weed management and dry bean (Phaseolus vulgaris) yield. In weed-free dry bean, a reduction in row spacing from 69 to 23 cm increased yield by 19% and an increase in density from 20 to 50 plants/m2 increased yield by 17%. In the presence of weeds, narrow rows and high plant densities increased dry bean yield, but without herbicides, yields remained low. However, when combined with herbicides, narrow-row and high-density production practices resulted in better weed control and higher dry bean yield than that attained in a wide-row and low-density production system. Herbicide combinations, often at reduced rates, controlled weeds as well or better than the full rate of any individual herbicide. Ethalfluralin applied preplant incorporated followed by reduced rates of imazethapyr or bentazon postemergence (POST) consistently controlled weeds. Imazamox exhibited the potential to provide a total POST weed control option in dry bean production. Information gained in this study will be used to develop improved weed management programs appropriate for either wide- or narrow-row dry bean production systems.Nomenclature: Bentazon, 3-(1-methylethyl)-(1H)-2,1,3-benzothiadiazin-4(3H)-one 2,2- dioxide; ethalfluralin, N-ethyl-N-(2-methyl-2-propenyl)-2,6-dinitro-4-(trifluoromethyl)benzenamine; imazamox, 2-[4,5-dihydro-4-methyl-4-(1-methylethyl)-5-oxo-1H-imidazol-2-yl]-5-(methoxymethyl)-3-pyridinecarboxylic acid; imazethapyr, 2-[4,5-dihydro-4-methyl-4-(1-methylethyl)-5-oxo-1H-imidazol-2-yl]-5-ethyl-3-pyridinecarboxylic acid; small red dry bean, Phaseolus vulgaris L. ‘Ember.’Additional index words: Integrated weed management, plant density, row spacing, ECHCG, POLCO, POLSC, SETVI, SOLSA.Abbreviations: PAR, photosynthetically active radiation; POST, postemergence; PPI, preplant incorporated.
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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".