Field evaluation of regression equations to estimate crop yield losses due to weeds
Bibliographic record
Abstract
Various regression equations based on weed density alone, or relative time of weed and crop emergence or crop density in addition to weed density have been developed in western Canada to estimate the effects of wild oat (Avena fatua L.) and volunteer cereals on yield loss of field crops, and to advise farmers on the economics of weed control with herbicides. In 1997, 1998, and 1999, several of these equations were evaluated in 9 barley (Hordeum vulgare L.), 9 wheat (Triticum aestivum L.) and 11 canola (Brassica napus L.) fields in Alberta. Wild oat was the dominant weed in the barley and wheat fields, and wild oat or volunteer cereals in the canola fields. In barley and wheat, more complex equations based on both weed density and either crop density or relative time of weed and crop emergence were more reliable in estimating yield losses due to wild oat than those based on weed density alone. In canola, an equation based on volunteer barley and canola density provided the most reliable estimates. Under the assumed crop prices and herbicide costs, these equations also resulted in the best estimates of whether or not a herbicide application resulted in a net profit or loss. Herbicide application was rarely economical in barley, but usually economical in wheat and canola reflecting the different market value of the crops. The implementation of the weed economic threshold concept is likely to be more feasible in low-value crops such as feed barley than in higher-value crops such as canola. Key words: Barley (Hordeum vulgare L.), canola (Brassica napus L.), volunteer cereals, weed economic threshold, wheat (Triticum aestivum L.), wild oat (Avena fatua L.)
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".