Effect of irrigation management on yield and water use efficiency of timothy hay in southern Alberta
Bibliographic record
Abstract
Timothy hay production for export markets has recently expanded on the Canadian prairies. Irrigation management information for timothy production is limited; therefore, irrigation practices to achieve optimum dry matter (DM) yield and water use efficiency (WUE) of timothy hay were investigated from 2005 to 2007 near Bow Island and Picture Butte, Alberta. Treatments were defined by managing irrigation using 0.25-m, 0.50-m, 0.75-m, and 1.00-m root zone depths with an allowable moisture depletion of 50% of available soil moisture. The 0.25-m root zone treatment resulted in greater first-cut timothy DM yield than the 1.00-m root zone treatment at Bow Island. The 0.50-m root zone treatment resulted in greater first-cut timothy DM yield than the 0.25-m root zone treatment at Picture Butte. Treatment effect on the second-cut DM yield was not significant. Water use for the first-cut crop was significantly greater for the 0.25-m root zone treatment at Bow Island and for the 0.50-m root zone treatment at Picture Butte than the other treatments in 2006 and 2007. There was no consistent treatment effect with the second-cut crop water use. The treatment effect with the first-cut WUE was not significant and there was no consistent treatment effect with the second-cut WUE. Use of a shallow root zone depth (0.25-0.50 m) for irrigation management could optimize first-cut timothy production for export, but producers may need to avoid irrigating the second-cut crop to conserve water for other efficient uses in southern Alberta. Key words: Irrigation management, dry matter, timothy, Phleum pretense, root zone, water use efficiency, allowable depletion, available moisture
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".