Genetic Variance for Gluten Strength Contributed by High Molecular Weight Glutenin Proteins
Bibliographic record
Abstract
ABSTRACT A total of 162 doubled haploid (DH) lines were produced from a cross between Triticum aestivum L. ‘AC Karma’ and line 87E03‐S2B1 to study the genetic contribution of high molecular weight (HMW) glutenin subunits to gluten strength. HMW glutenin subunit composition of each DH line was determined by SDS‐PAGE. The population was grown in the field at one location in 1999 and at three locations in 2000. Gluten strength and dough mixing properties were measured by mixograph test and SDS‐sedimentation test. Variance components were estimated for each measurement to determine the variability contributed by HMW glutenin subunits. Results indicated significant environmental impact on tested mixograph parameters, SDS‐sedimentation volumes and grain and flour protein concentration. Significant main effects of Glu‐1D loci encoded subunits were obtained for mixograph development time, energy to peak, slope after peak, and first minute slope. Lines containing 5+10 combination of subunits had higher values for mixograph development time and energy to peak, while slope after peak and first minute slope were lower as compared with 2+12 containing lines. Low intergenomic interactions were observed for bandwidth energy (BWE), total energy (TEG), and SDS‐sedimentation test, involving B and D genomes only. A portion of the genetic variability for gluten strength was accounted for overexpression of Bx7 subunit originating from the cultivar Glenlea derived line 87E03‐S2B1. There was no significant effect of Glu‐A1 encoded subunits on any of the tested parameters. Estimated genetic variability for gluten strength contributed by Glu‐B1 and Glu‐D1 encoded HMW glutenins was 55% for mixing development time and 51% for energy to peak.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".