The Integration of Spring and Winter Wheat Genetics With Agronomy for Ultra-Early Planting Into Cold Soils
Bibliographic record
Abstract
Early seeding has been suggested as a method of increasing the grain yield and grain yield stability of wheat (Triticum aestivum L.) in the Northern Great Plains. The point at which early seeding results in a decrease in grain yield has not been clearly identified. Changes in climatic conditions have increased frost-free periods and increased temperatures during grain filling, which can either be taken advantage of or avoided by seeding earlier. Field trials were conducted in western Canada from 2015 to 2018 to evaluate an ultra-early wheat planting system based on soil temperature triggers as opposed to calendar dates. Planting began when soil temperatures at 5cm depth reached 0oC and continued at 2oC intervals until 10oC, regardless of calendar date. Conventional commercial spring wheat genetics and newly identified cold tolerant spring wheat lines were evaluated to determine if ultra-early wheat seeding systems required further development of specialized varieties to maintain system stability. Ultra-early seeding resulted in no detrimental effect on grain yield. Grain yield increased at sites south of 51o latitude N, and was unaffected by ultra-early seeding at sites north of 51o latitude N. Grain protein content, kernel weight, and bulk density were not affected by ultra-early seeding. Optimal seeding time was identified between 2oC and 6oC soil temperatures. A greater reduction in grain yield was observed from delaying planting until soils reached 10oC than from seeding into 0oC soils; this was despite extreme environmental conditions after initial seeding, including air temperatures as low as -10.2oC, and as many as 37 nights with air temperatures below 0oC. Wheat emergence ranged from 55% to 70%, and heads m-2 decreased with delayed seeding while heads plant-1 did not change. Cold tolerant wheat lines did not increase stability of the ultra-early wheat seeding system relative to the conventional spring wheat check, and are therefore not required for growers to adopt ultra-early seeding. The results of this study indicate that growers in western Canada can successfully begin seeding wheat earlier, with few changes to their current management practices, and endure less risk than delaying seeding until soil temperatures reach 10oC or greater.
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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 | 0.001 |
| 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 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".