Marker-assisted breeding of hexaploid spring wheat in the Canadian prairies
Bibliographic record
Abstract
Bread wheat (Triticum aestivum L.) is an important crop and export commodity for Canada. Increased global population, demand for superior quality grains, and rapidly evolving pathogens have necessitated the breeding of high-yielding, disease-resistant wheat cultivars. Significant improvements in breeding efficiency can be made through advances in wheat genetics and genomics to develop tools that accelerate genetic gains in wheat. The identification of genes and quantitative trait loci for economically important traits and the development of associated molecular markers have the potential to improve selection efficiency. Marker-assisted selection enriches desirable allelic frequency, complements phenotypic data, and facilitates gene stacking. Molecular markers have been developed for various genes and quantitative trait loci conferring resistance to leaf rust, stripe rust, stem rust, Fusarium head blight, loose smut, common bunt, leaf spot, wheat blossom midge, and wheat stem sawfly. Markers are available for wheat grain and flour characteristics as well. Agronomic traits such as vernalization requirement, day-length sensitivity, and plant height can also be selected using molecular markers. Validated single nucleotide polymorphism based markers are a useful tool in breeding new wheat varieties for the Canadian prairies. In the current review, we present a compilation of validated molecular markers that are polymorphic and potentially useful for Canadian wheat breeding.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".