1 Validation of fusarium head blight markers in Triticum aestivum
Bibliographic record
Abstract
With quantitative disease resistance, it is difficult to know which loci of a resistant source are passed to progeny that are subsequently used as parents in further crossing. The objective of this study was to identify the Sumai 3 loci that contribute fusarium head blight (FHB) resistance in breeding populations which have Sumai 3 derived parents. Doubled haploid populations of Infinity/ND3085, Infinity/ND744, and Alsen/Helios crosses were evaluated in FHB nurseries at Carman MB, Ottawa ON and Charlottetown PE in 2007 using a two replicate randomized complete block design of 80 lines per population plus parental checks. Percent incidence and severity of head blight, Fusarium-damaged kernels and DON accumulation were evaluated. DNA markers reported as associated with Sumai 3 FHB resistance at different loci were assessed on the parents and lines of each population. Statistical analyses were applied to marker and disease results to determine which loci contributed resistance. Resistance was expressed inconsistently across environments and across parents for particular loci. The results demonstrate the need to validate FHB resistance loci from Sumai 3 to determine which were passed to progeny that are subsequently used as parents (eg. Alsen) to efficiently apply marker assisted selection.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".