Influence of no‐till furrow opener and seed treatment on ultra‐early wheat seeding systems
Bibliographic record
Abstract
Abstract Ultra‐early planting is an alternative practice that involves planting based on soil temperature, initiated once the trigger temperature of >0°C is observed, regardless of calendar date. Our previous research concluded that spring wheat ( Triticum aestivum L.) grain yields are maintained or improved with enhanced yield stability when adopting this practice. However, a knowledge gap remains around the influence of furrow opener configuration and seed treatments to mitigate abiotic stressors related to cold soil and ambient temperatures. Thus, a 5‐year experiment was conducted in Lethbridge, AB, to examine the effects of planting dates triggered by soil temperatures of 0°C, 2.5°C, 5°C, 7.5°C, and 10°C; seed treatment (tebuconazole, prothioconazole, metalaxyl, and imidacloprid vs. untreated); and furrow opener (knife vs. disc) on ultra‐early planted spring wheat. Optimal grain yield was achieved when wheat was planted at a soil temperature of 0°C, irrespective of seed treatment and furrow opener type. A significant yield reduction was observed when wheat was planted at a soil temperature of 10°C. Wheat planted at soil temperatures of ≤7.5°C with a disc opener often resulted in high and stable yields, regardless of seed treatment. Grain protein concentration responses to soil temperature trigger were less consistent, but wheat planted at 10°C accumulated low and unstable concentrations. Seed treatment delayed emergence, flowering, and maturity; reduced head density; and ultimately lowered grain yield. Overall, spring wheat grain yield and protein concentration were optimized when planted at soil temperatures of ≥0 and ≤7.5°C using a disc opener, regardless of seed treatment adoption.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".