Impact of delayed postemergence herbicide application on corn yield based on weed height, days after emergence, accumulated crop heat units, and corn growth stage
Bibliographic record
Abstract
Abstract Nine field experiments were conducted from 2017 to 2019 in Ontario to determine the impact of early weed interference on corn yield based on corn growth stage, days after emergence (DAE), accumulated crop heat units (CHU), and weed size. The predicted weed size at herbicide application that resulted in a 1%, 2.5%, 5%, 10%, 25%, and 50% yield loss in corn was estimated to be 1, 4, 11, 53, non-estimable (N est.*), and N est.* cm under low weed density and 3, 5, 7, 11, 27, and N est.* cm under high weed density, respectively. The predicted DAE at herbicide application time that resulted in a 1%, 2.5%, 5%, 10%, 25%, and 50% yield loss in corn was predicted to be 14, 20, 27, 44, N est.*, and N est.* DAE under low weed density and 5, 7, 11, 17, 25, and 59 DAE under high weed density, respectively. The predicted CHU from planting at herbicide application time that led to a 1%, 2.5%, 5%, 10%, 25%, and 50% yield loss in corn was 468, 636, 821, 1,271, N est.*, and N est.* CHU from planting under low weed density and 207, 283, 385, 551, 972, and 1,748 CHU from planting under high weed density, respectively. The predicted crop stage at herbicide application that led to a 1%, 2.5%, 5%, 10%, 25%, and 50% yield loss in corn was V5, V6, V7, V11, N est.*, and N est.* under low weed density and V1, V2, V3, V4, V8, and V14 under high weed density, respectively. Results indicate that weeds must be controlled before they reach 7 cm in height, prior to 11 d after crop emergence, prior to 385 accumulated CHU from emergence, or prior to the V3 stage under high weed density to avoid greater than 5% yield loss.
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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 | 0.000 | 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 | 0.000 | 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 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".