Integrating residual herbicides with cultural and mechanical weed control in faba bean (Vicia faba L.)
Bibliographic record
Abstract
Herbicide resistance is becoming an increasing problem worldwide, one that is threatening global food production. Frequent use of herbicides with high efficacy has led to strong selection pressure for the development of herbicide resistant weed species. Faba bean (Vicia faba L.) is an emerging crop in western Canada. To date, there is very limited research that contains several integrated weed management strategies together to mitigate weed pressures. Field trials were conducted near Saskatoon, Floral and Melfort, Saskatchewan to address this gap. The first study in this research aimed to determine the optimal combination of pre-emergence (PRE), residual herbicides and crop seeding rate to reduce the number of weeds exposed to a post emergent herbicide application. Weed control was improved by the addition of pyroxasulfone+sulfentrazone into a tank mix with glyphosate, but the greatest weed control was with when a PRE herbicide was combined with POST emergence application of imazamox+bentazon. Although no interaction was observed between herbicide and seeding rate, higher seeding rates tended to improve weed control and crop yield. The optimal seeding rate needed to reach the highest yield varied for each herbicide treatment. The objective of the second study was to determine if high or medium intensities of integrated weed management strategies (IWM), combined with a PRE herbicide with residual characteristics, could eliminate the need for a post emergence herbicide application. The best weed control was achieved with medium to high levels of intensity of integrated weed management strategies. Weed control generally did not differ among herbicides, regardless of the duration of the residual period. The highest crop yield and seed size was also observed in the medium to high IWM treatments. Herbicide did not affect crop yield or seed size. Based on the results in these studies, growers should seed a faba bean crop in early May or late April, depending on environment, with an increased seeding rate (50-75 seeds m-2) and a narrower row spacing (<25 cm). Furthermore, using a pre-emergence herbicide such as pyroxasulfone+sulfentrazone, saflufenacil, or flumioxazin will help to further reduce early season weed pressure, while reducing the risk for developing herbicide resistant weeds. In addition, near perfect weed control was achieved with an effective PRE herbicide coupled with a high IWM intensity. This demonstrates that it is indeed possible to achieve both excellent weed control and good crop production without the use of an in-crop herbicide.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".