Functionally diverse flax-based rotations improve wild oat (<i>Avena fatua</i>) and cleavers (<i>Galium spurium</i>) management
Bibliographic record
Abstract
Abstract Wild oat (Avena fatua L.) and false cleavers (Galium spurium L.) are currently a challenge to manage in less competitive crops such as flax (Linum usitatissimum L.). Increasing the functional diversity in crop rotations can be an option to improve weed management. Nonetheless, this strategy had not been tested in flax in western Canada. A 5-yr (2015 to 2019) crop rotation study was carried at three locations in western Canada to determine the effect of diverse flax-based crop rotations with differences in crop species, crop life cycles, harvesting time, and reduced herbicides on managing A. fatua and G. spurium. The perennial rotation (flax–alfalfa [Medicago sativa L.]–alfalfa–alfalfa–flax) under reduced herbicide use was found to be the most consistent cropping system, providing A. fatua and G. spurium control similar to the conventional annual flax crop rotation (flax–barley [Hordeum vulgare L.]–flax–oat [Avena sativa L.]–flax) with standard herbicides. At Carman, this alfalfa rotation provided even better weed control (80% A. fatua, 75% G. spurium) than the conventional rotation. Furthermore, greater A. fatua control was identified compared with a conventional rotation in which two consecutive winter cereal crops were grown successfully in rotation (flax–barley–winter triticale [×Triticosecale Wittm. ex A. Camus (Secale × Triticum)]–winter wheat [Triticum aestivum L.]–flax). Incorporation of silage oat crops did not show consistent management benefits compared with the perennial alfalfa rotation but was generally similar to the conventional rotation with standard herbicides. The results showed that perennial alfalfa in the rotation minimized G. spurium and A. fatua in flax-cropping systems, followed by rotations with two consecutive winter cereal crops.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".