Effects of reduced pesticide use on winter wheat production in the Canadian Prairies
Bibliographic record
Abstract
Winter wheat ( Triticum aestivum L.) is a highly competitive crop with the potential to enhance on-farm revenue and reduce reliance on crop protection inputs. The adoption of winter wheat in the Canadian Prairies has varied significantly over recent decades; however, improved weed and disease management practices could facilitate stability of hectares cultivated. To assess current and alternative pesticide management practices, we conducted a study across 15 site-years at four locations over 4 years (2018–2022). Experimental treatments included pre-plant weed management (glyphosate vs. glyphosate mixed with pyroxasulfone + carfentrazone-ethyl), in-crop weed management (no in-crop herbicide vs. fall-applied 2,4-D vs. fall-applied 2,4-D + spring-applied site-year-specific herbicides), and in-crop fungicide management (no in-crop fungicide vs. one prothioconazole + tebuconazole application at Zadoks Growth Stage (ZGS) 60 vs. two prothioconazole + tebuconazole applications at ZGS32 and ZGS60). Pre-plant glyphosate alone and glyphosate tank-mixed with pyroxasulfone + carfentrazone-ethyl exhibited comparable effects on grain yield, quality parameters, and agronomic characteristics. In-crop weed management had no significant influence on these factors compared to the no in-crop herbicide control, suggesting that in-crop herbicide applications are unnecessary due to the high competitiveness of winter wheat against weeds. However, disease mitigation was prudent as single and double application of fungicide increased grain yield while maintaining grain protein concentration levels. A high-yielding, stable system for optimal grain yield typically required pre-plant weed management coupled with two fungicide applications. These observations confirm herbicide inputs can be reduced in a winter wheat cropping system, but disease pressure requires careful cultivar selection with respect to disease resistance as multiple applications of fungicides were needed to optimize grain yield.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".