Economic benefits of integrated weed management systems for field crops in the Dark Brown and Black soil zones of western Canada
Bibliographic record
Abstract
Integrated weed management (IWM) systems that combine seeding date, seeding rate, herbicide rate, and timing of nitrogen (N) fertilizer application were assessed for their economic performance in the Dark Brown and Black soil zones. A barley-field pea IWM system in the Black soil zone at Lacombe, Alberta, and a wheat-canola IWM system in the Dark Brown soil zone at Lethbridge, Alberta, and Scott, Saskatchewan, were used to assess contributions of seeding date (April or May), seeding rate (recommended or 150% of recommended), fertilizer timing (fall or spring), and in-crop herbicide rate (50% or 100% of recommended). The factorial set of treatments was applied in 4 consecutive years at each site. For barley-field pea production, the highest contribution margin (CM) (returns over variable production costs) was earned with 50% of the recommended herbicide rate, spring application of N fertilizer, seeding barley later at the high seeding rate, and seeding field pea early at the recommended seeding rate. This IWM system had a CM benefit of at least $51 ha -1 compared with current common practices. The wheat-canola system results were site specific. At Lethbridge, it was more profitable to use 50% of recommended herbicide rates and to seed both crops early, with an early seeding date being very important for canola. The CM of this IWM system was $48 ha -1 higher than current common practices. At Scott, the wheat-canola system was more profitable with spring fertilizer application, 50% of the recommended herbicide rate, and an early seeding date for canola. The best IWM system had a CM $15 to $75 ha -1 higher, depending on the year, than common practices. Our results confirmed the economic merits of using IWM practices for cereal-oilseed and cereal-pulse cropping systems in these regions of western Canada. Key words: Economic, integrated weed management, contribution margin, canola, wheat, field pea, barley
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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 | 0.000 |
| 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 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".