The Effect of Vernalization Genes on Earliness and Related Agronomic Traits of Spring Wheat in Northern Growing Regions
Bibliographic record
Abstract
Vernalization response ( Vrn ) genes play a major role in determining the flowering times of spring‐sown wheat ( Triticum aestivum L.). The objective of this study was to investigate the effect of Vrn genes on flowering and maturity times and important agronomic traits in a set of reciprocal whole‐chromosome substitution lines and eight western Canadian spring wheat cultivars of known Vrn genes, grown over three seeding dates in Alberta, Canada over 2 yr. The genotype carrying spring habit alleles at Vrn‐A1 , Vrn‐B1 , and Vrn‐D5 flowered and matured the earliest, and had the highest grain protein content but the lowest grain yield. Genotypes with spring habit alleles Vrn‐A1 and Vrn‐B1 were early maturing and high yielding. Genotypes with the spring habit Vrn‐D5 allele either singly or in combination with Vrn‐A1 were late maturing. The spring habit allele of Vrn‐A1 was not completely epistatic to Vrn‐B1 and Vrn‐D5 for flowering or maturity time. The spring habit allele of Vrn‐B1 , however, was epistatic to that of Vrn‐D5 for these traits. In northern wheat growing regions, breeding preference should be given to Vrn genotypes with three spring habit alleles or those with spring habit alleles of Vrn‐A1 and Vrn‐B1 Genotypes carrying spring habit Vrn‐D5 allele singly or in combination with Vrn‐A1 should be planted as early in the growing season as possible to realize their full yield potential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".