A Sustainable Management Package for Triticale in the Western Canadian Prairies
Bibliographic record
Abstract
Triticale (× Triticosecale Wittmack) is a minor cereal crop in Alberta which has recently garnered interest as a biofuel feedstock. Basic agronomic information is lacking for triticale cultivars released since 1990. Field experiments were initiated in 2010 and conducted for 2 yr at four sites in central and southern Alberta to compare the impact of cultivar selection, seeding date, and seeding rate on grain yield, grain quality, and other agronomic traits. Six triticale cultivars released between 1996 and 2011, and one Soft White Spring wheat cultivar ( Triticum aestivum L.) were evaluated over two seeding dates; one before and one after 15% of the total seasonal growing degree days (GDD; base = 0°C) had elapsed. The cultivars were evaluated at seeding rates of 250, 375, and 500 seeds m −2 . Older triticale cultivars had higher grain yields but lower grain quality than cultivars released after 2000. The triticale cultivars produced more grain than Soft White Spring wheat in five of seven environments; however, Soft White Spring wheat exhibited better grain quality than the triticales. Yield generally increased linearly with seeding rate but the highest return on investment was observed at 375 seeds m −2 . Provided there was not an early frost, triticale seeded after 15% of the seasonal GDD had elapsed could produce grain yield similar to the earlier‐seeded triticale. A sustainable management system for triticale includes modern cultivars, a seeding date that can accumulate 1750 GDD’s before frost, and a sowing density of at least 375 seeds m −2 .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".