Validation of Molecular Markers for Use With Adapted Sources of Fusarium Head Blight Resistance in Wheat
Bibliographic record
Abstract
Genetic control of resistance to Fusarium head blight (FHB) is quantitative, making phenotypic selection difficult. Genetic markers to resistance are helpful to select favorable genotypes. This study was conducted to determine if Fhb1 and Fhb5 present in the Sumai 3 source of FHB resistance occur in Sumai 3-derived North American spring wheat cultivars and to understand the appropriateness of using markers to select for the favorable alleles at these loci in breeding. Sumai 3-derived parents Alsen, ND3085, ND744, Carberry, and Glenn were used in crosses to generate 14 doubled haploid breeding populations. The parents and progeny were genotyped with five Fhb1 and three Fhb5 microsatellite markers. Progeny were selected based on performance relative to parents and other control cultivars in FHB nurseries near Portage la Prairie and Carman, MB. χ2 and t test analyses were performed on marker and FHB data. The χ2 test frequently determined the proportion of lines carrying molecular variants associated with FHB resistance increased following nursery selection for FHB. Similarly, the t test regularly demonstrated that selection for FHB resistance lowered the mean level of disease associated with resistant marker haplotypes. The study affirmed FHB resistance sources Alsen, Carberry, ND3085, and ND744 have Fhb1 and Fhb5 loci like Sumai 3, but no evidence was found that Glenn carries Fhb1 and Fhb5 resistance alleles. The results justified use of Fhb1 and Fhb5 markers for marker assisted selection in populations derived from Alsen, Carberry, ND3085, and ND744, but not Glenn. Combined or individual application of Xgwm493 and Xgwm533 in selection of genotypes carrying Fhb1, and Xgwm150, Xgwm304, and Xgwm595 for Fhb5 will enhance FHB resistance in wheat.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".