Breeding wheat for resistance to Fusarium head blight in the Global North: China, USA, and Canada
Bibliographic record
Abstract
The objective of this paper is to review progress made in wheat breeding for Fusarium head blight (FHB) resistance in China, the United States of America (USA), and Canada. In China, numerous Chinese landraces possessing high levels of FHB resistance were grown before the 1950s. Later, pyramiding multiple sources of FHB resistance from introduced germplasm such as Mentana and Funo and locally adapted cultivars played a key role in combining satisfactory FHB resistance and high yield potential in commercial cultivars. Sumai 3, a Chinese spring wheat cultivar, became a major source of FHB resistance in the USA and Canada, and contributed to the release of more than 20 modern cultivars used for wheat production, including the leading hard spring wheat cultivars Alsen, Glenn, Barlow and SY Ingmar from North Dakota, Faller and Prosper from Minnesota, and AAC Brandon from Canada. Brazilian wheat cultivar Frontana, T. dicoccoides and other local germplasm provided additional sources of resistance. The FHB resistant cultivars mostly relied on stepwise accumulation of favorable alleles of both genes for FHB resistance and high yield, with marker-assisted selection being a valuable complement to phenotypic selection. With the Chinese Spring reference genome decoded and resistance gene Fhb1 now cloned, new genomic tools such as genomic selection and gene editing will be available to breeders, thus opening new possibilities for development of FHB resistant cultivars.
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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 | 0.003 |
| 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".