Soil water use, biomass accumulation and grain yield of no-till winter wheat on the Canadian prairies
Bibliographic record
Abstract
Higher water use efficiency provides no-till-seeded winter wheat with an advantage over spring-sown crops in western Canada. However, like all crops, winter wheat (Triticum aestivum L) is subject to large yield losses due to drought. This study was undertaken to identify the effect of weather and crop soil water status on water use, aboveground biomass production and grain yield of no-till winter wheat grown on the Canadian prairies. Five winter wheat cultivars were grown over a 3-yr period at a total of 17 sites scattered across the different climatic zones of Saskatchewan. Both the establishment and expression of grain yield potential were limited by drought in these dryland environments. Early-season moisture was required to set up a high grain yield potential while low ET and high precipitation during grain filling were necessary to secure yield. Rapid growth under cool temperatures during April and early May consumed much of the available water in the top 50-cm of the soil profile and large ET deficits, as a consequence of a continuous decline in available water, characterized drought stress in most trials. While stored soil water at greenup was not sufficient to support a crop, there was growing season rainfall at all trial sites and improvements in water availability led to higher grain yields and an increased range in mean environmental grain yield. Rainfall had its greatest influence on grain yield during tillering, while atmospheric conditions and soil water content were more important from heading to anthesis. Because environmental differences in drought stress were related to the volume and distribution of growing season precipitation, some dryland environments were exposed to intermittent stress while stress was terminal in others. Therefore, to be successful, winter wheat cultivars and management systems for the Canadian prairies must be able to accommodate variable patterns of growing season water availability. Key words: Triticum aestivum L., evapotranspiration, precipitation, water use, biomass, grain yield
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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 | 0.001 | 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".