Genetics of pre-harvest sprouting resistance in a cross of Canadian adapted durum wheat genotypes
Bibliographic record
Abstract
Severe losses attributable to pre-harvest sprouting (PHS) have been reported in Canada in recent years. The genetics of PHS resistance have been more extensively studied in hexaploid wheat and generally not using combinations of elite agronomic parents. The objective of our research was to understand the genetic nature of PHS resistance in an elite durum cross. A doubled haploid (DH) population and checks were phenotyped in replicated trials for grain yield and PHS traits over 3 years in western Canada. The response of intact spikes to sprouting conditions, sampled over two development time points, was measured in a rain simulation chamber. The DH population was genotyped with simple sequence repeat and Diversity Arrays Technology markers. Genotypes were a significant source of variation for grain yield and PHS resistance traits in each tested environment. Transgressive segregant DH genotypes were identified for grain yield and PHS resistance measurements. Low or no correlation was detected between grain yield and PHS, while correlation between PHS resistance measurements was moderate. The heritability of PHS resistance was moderate and higher than grain yield. Significant quantitative trait loci with small effect were detected on chromosomes 1A, 1B, 5B, 7A and 7B. Both parents contributed to the PHS resistance. Promising DH genotypes with high and stable grain yield as well as PHS resistance were identified, suggesting that grain yield and PHS can be improved simultaneously in elite genetic materials, and that these DH genotypes will be useful parental material for durum breeding programs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".