Grain yield and water use: Relative performance of winter vs. spring cereals in east-central Saskatchewan
Bibliographic record
Abstract
Changing economic conditions have provided strong incentives for grain producers to choose the most profitable cereal crops to grow. We determined grain yield and water use efficiency (WUE) for winter wheat (Triticum aestivum L.), fall rye (Secale cereale L.), hard red spring (HRS) wheat, Canada prairie spring (CPS) wheat, amber durum (Triticum turgidum L.), and barley (Hordeum vulgare L.) under no-till systems. Over 60% of yield variability existing among site/years was due to water use or evapotranspiration (ET) in semiarid east-central Saskatchewan. Mean grain yield increased by 16.3 kg ha −1 with each millimetre of increase in ET. Barley produced 3748 kg ha −1 of grain on average, or 21% higher than winter wheat, 27% higher than CPS wheat, 39% higher than rye or durum, and 50% higher than HRS wheat. Average yields differed less than 5% between winter wheat and CPS wheat, but in water-stressed environments, CPS wheat had 19 to 34% lower grain yield than winter wheat. In one of the five cases where winter wheat was seeded much later than the recommended seeding date, CPS wheat yields were 16% higher than winter wheat. With every millimetre of increased ET, CPS or barley increased grain yield by 22 kg ha −1 , while winter wheat increased yield by 17 kg ha −1 . Winter wheat and rye had no yield differences in general, but in more moist environments, winter wheat produced higher (up to 28%) grain yield than fall rye, and in the year when winter wheat was seeded late, winter wheat yielded 11% lower than rye. As fertiliser N increased from 50 to 100 kg ha −1 , barley grain yield increased by 347 kg ha −1 , and durum grain yield increased by only 5 kg ha −1 . Winter wheat, fall rye and barley had greater WUE than the other spring cereals, but soil profile (0–120 cm) water in the spring did not differ among crops. In maximising grain yield and water use in east-central Saskatchewan, barley, winter wheat, and CPS wheat would provide the best options. Key words: Water-use efficiency, protein, winter wheat, Triticum aestivum, Secale cereale, Triticum turgidum, Hordeum vulgare
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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) | 0.000 | 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) | 0.000 | 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".