Exploring agronomic strategies to improve oat productivity and control weeds: leaf type, row spacing, and planting density
Bibliographic record
Abstract
The trade-off between crop production and weed control is a fundamental scientific issue, as it is frequently influenced by individual crop competitive ability, population density, and planting pattern. A 2 yr field study was conducted to examine the relationship between planting density and row spacing, using two contrasting oat varieties. On average, high planting density (480 plants m −2 ) reduced weed biomass at oat maturity by 59% in 2012 and by 56% in 2013, when compared with a low density (120 plants m −2 ). The droopy-leaf variety suppressed weed biomass by up to 69% and weed density up to 72%, compared with the erect-leaf variety. In a drier year, the greatest grain yield was achieved with the droopy-leaf variety under the intermediate density, while in 2013, the erect-leaf variety under the high density had similar yield to the droopy-leaf variety at the intermediate density. A general trend was that increasing plant density suppressed weed infestation, and promoted crop biomass and yield. The droopy-leaf variety exhibited a strong competitive ability under the intermediate planting density, while the erect-leaf variety had a strong competitive ability under the high density. Taken together, there was a complex variety-by-environment interaction to achieve the balance between crop production and weed suppression, which was mediated by growing-season conditions.
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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 | 0.001 |
| 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".