Do Cultivar and Burning Affect Forage Yield and Incidence of Verticillium Wilt or Insect Pests in Alfalfa Stands?
Bibliographic record
Abstract
Alfalfa (Medicago sativa L.) is one of the most important forage crops in Canada and many parts of the world. Two experiments were conducted over a 13‐yr period (1989–2002) in Lethbridge, Alberta, Canada with five alfalfa cultivars. In the first experiment, ‘Barrier’ and ‘Pacer’ were given three burn treatments (no burn, burn every year, and burn in alternate years) while in the second experiment four cultivars ‘Barrier’, ‘Heinrichs’, ‘Trumpetor’, and ‘Legend’ were given burn or no burn treatments to determine the impact of burning of crop residues on forage yield, incidence of verticillium wilt, and insect pest abundance. Burning did not affect forage yield or incidence of verticillium wilt of alfalfa. Barrier had the highest yield and lowest disease incidence. Burning had a significant albeit variable impact on abundance of alfalfa plant bugs, lygus bugs, aphids, and leafhoppers but not on abundance of alfalfa weevil. The lack of effectiveness of the burning treatments on forage yield and adverse environmental consequences of burning such as air pollution, hazardous loss of visibility during burning operations, and loss of crop cover suggest that burning should not be used as a production strategy for this widely grown crop.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".