Fallow management input strategies for weed management in <scp>Florida</scp> cabbage production
Bibliographic record
Abstract
BACKGROUND: Fallow period weed management is an important Florida production consideration due to its duration and impact on the cash crop. Cover cropping is a valuable summer fallow period option for weed suppression. Sorghum-sudangrass is a commonly used, competitive, and allelopathic Florida summer cover crop. The effect of increased seeding rate, a herbicide application, and added fertilizer inputs during the fallow period on the cover crop, weed populations, and cabbage yield was explored and compared to nontreated and chemical fallow controls. RESULTS: Increased sorghum-sudangrass seeding rates had no effect on the resultant stand density or biomass compared to the standard seeding rate. Cover cropping did not consistently suppress purple nutsedge, Florida pusley, or wild radish and added fertilizer inputs produced variable results. S-metolachlor enhanced purple nutsedge suppression at low densities but did not improve grass, wild radish, and Florida pusley suppression. CONCLUSIONS: Increased fallow management inputs did not consistently enhance weed suppression or provide benefit to the cash crop. Sorghum-sudangrass suppressed Poaceae densities during the fallow period but did not adequately suppress nutsedge, wild radish, or Florida pusley densities over time. We conclude that weed management inputs should be focused on the cash crop and that enhanced management during the fallow period has limited benefit. © 2021 Society of Chemical Industry.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".