Fertilizer nitrogen rate and the response of weeds to herbicides
Why this work is in the frame
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Bibliographic record
Abstract
Differences in plant community composition have been attributed to abiotic field characteristics, crop type, localized predation, farm implement traffic, and natural dispersal mechanisms. Nitrogen (N) fertilizer rates and herbicides also are known to influence weed community structure, although their interaction has not been reported in the literature. A growth room experiment was conducted using three weed species (green foxtail, redroot pigweed, and velvetleaf) and five herbicides (nicosulfuron, atrazine, glufosinate, glyphosate, and mesotrione) differing in their mode of action and efficacy to the selected species. The experiment was conducted in growth chambers with two levels of N fertilization (low: 0.7 mM N and high: 7.7 mM N). Weeds were grown to the two- to five-leaf stage (depending on species), treated with the appropriate herbicide, and harvested approximately 2 wk after treatment. The herbicide dose at which a 50% reduction in biomass occurred (GR 50 ) was determined using log-logistic analysis. Herbicide susceptibility of the different weed species was influenced by N level. Green foxtail grown under low N required approximately six times the dose of nicosulfuron compared with plants grown under high N. Similarly, higher doses of nicosulfuron, glufosinate, mesotrione, and glyphosate were required to achieve a 50% reduction in redroot pigweed biomass grown under low N. In contrast, N did not influence the efficacy of mesotrione, glufosinate, or atrazine when applied to velvetleaf. This indicated specificity among herbicide–species combinations. Differences in herbicide efficacy resulting from soil N levels may alter weed community structure and may potentially explain possible weed control failures on farm fields.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it