A genetic examination of early flowering and maturity in Canadian spring wheat
Bibliographic record
Abstract
Under short-season western Canadian growing conditions, vernalization non-responsiveness is generally considered a preferable spring wheat (Triticum aestivum L.) phenotype, to avoid inconsistent maturity and yield patterns. The objectives of this study were to investigate the genetic factors affecting early flowering and maturity, and related agronomic traits, in a set of five Canadian spring wheat cultivars. The cultivars were first studied under 10- and 16-h photoperiods and 0- and 42-d vernalization treatments. Thereafter, the parents and F1 hybrids from a one-way diallel mating design were grown with and without a 42-d vernalization treatment. Shorter photoperiod delayed flowering time in all cultivars, and increased final leaf number in AC Barrie. Vernalization hastened flowering and decreased final leaf number in AC Foremost and AC Taber. AC Foremost and AC Taber carry at least one different allele, from the rest of the cultivars studied, at the major loci governing vernalization response. Leaf and spikelet number on the main culm, days to anthesis and maturity, tiller number and yield plant-1 were mainly controlled by additive gene action. Narrow-sense heritability was medium to high (0.53–0.93) for final leaf number, days to anthesis, spikelet number and grain yield, but low to medium (0.20–0.71) for days to maturity and tiller number. Selection for early flowering under non-vernalizing conditions may aid in the breeding of (vernalization non-responsive) early-maturing spring wheat cultivars in western Canada. Key words: Diallel cross, earliness, photoperiod, vernalization, Triticum aestivum L.
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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 | 0.001 | 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".