Nitrogen Fertilizer Rate Effects on Weed Competitiveness is Species Dependent
Why this work is in the frame
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Bibliographic record
Abstract
Information on nitrogen fertilizer effects on crop–weed competitive interactions might aid in developing improved weed management programs. A controlled environment study was conducted to examine the effect of three N rates on the competitive ability of four weed species grown with wheat. The four weed species were chosen to represent species that varied in their growth responsiveness to nitrogen (N): Persian darnel (low), Russian thistle (low), redroot pigweed (high), and wild oat (high). Wheat and each weed species were grown in a replacement series design at N rates of 60, 120, and 240 mg N kg −1 soil. The competitive ability of the low N-responsive species, Persian darnel and Russian thistle, was not influenced by N rate, supporting our hypothesis that N rate would have little effect on the competitiveness of species responding minimally to N. Conversely, the competitiveness of the high N-responsive species redroot pigweed progressively improved as N rate increased. However, wild oat competitiveness was unaffected by N fertilizer rate. There is some evidence from this study to suggest that fertilizer management strategies that favor crops over weeds deserve greater attention when weed infestations consist of species known to be highly responsive to higher soil N levels. Information gained in this study will be used to advise farmers of the importance of strategic fertilizer management in terms of both weed management and crop yield.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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