Bibliographic record
Abstract
Seeding date is an important factor influencing productivity of barley (Hordeum vulgare L.). When conditions are conducive to early seeding or result in delayed seeding, producers need to know how cultivars will respond to these seeding situations. In this study, five cultivars (Abee, Harrington, Jackson, Noble and Virden) registered for western Canada were studied for 4 yr (1990 to 1993) when seeded early (late April or early May), in mid-May, in late-May, or late (mid-June) at Lacombe, AB. For all cultivars, early seeding resulted in grain yield advantages of 113 to 134% of the mean site yield, while with late seeding, grain yields were reduced to 54 to 76% of the mean site yield. The reduction in yield was least for Jackson, the earliest maturing cultivar tested. Late seeding reduced the period from sowing to emergence, vegetative period, grain-filling period, time from emergence to physiological maturity, test weight, grain yield, kernel weight, and tillers per plant; and increased plant height and percent thins. Late seeding had no significant effect on phyllochron, stand establishment, scald, lodging, protein content of the grain, kernel number per spike, and spikelet number per spike. Barley responded positively to early seeding in central Alberta, but when seeding was delayed (in this study to mid-June) the early and mid-maturing six-rowed cultivars with short phyllochrons performed better than the two-rowed and late six-rowed cultivars. Key words: Hordeum vulgare L., seeding rate, phenological development, grain quality, grain yield, components
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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 | 0.001 | 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".