Relationships among bread-making quality, gluten strength, physical dough properties, and pasta cooking quality for some Canadian durum wheat genotypes
Bibliographic record
Abstract
Fifty-four durum wheat (Triticum durum) genotypes entered into the 1995, 1996 and 1997 Co-operative Tests were evaluated for gluten strength characteristics using the sodium dodecyl sulphate (SDS) sedimentation test, the gluten index (GI) test, and physical dough tests including farinograph (high and low adsorption), mixograph, alveograph and extensigraph. Baking quality was evaluated for bread prepared by the Canadian short process (CSP), a short mechanical dough mixing process, and pasta quality was evaluated for spaghetti dried at both low (40°C) and high (70°C) temperatures. The effect of genotype on physical dough measurements, baking quality and spaghetti cooking quality was then determined. SDS sedimentation, GI, pasta dough farinograph (low absorption), bread dough farinograph (high absorption), extensigraph and alveograph measurements were interrelated. When baked by the CSP, the strongest genotypes exhibited mixing times and mixing energies similar to or greater than good quality bread wheat (Triticum aestivum). Although loaf volume (LV) was positively correlated to gluten strength indicators, the strongest genotypes still exhibited only about 85% of the LV expected of good-quality bread wheat of comparable protein content. Baking quality however, was not related to pasta cooking quality, and, therefore, there is potential to breed for dual-purpose durum cultivars, which combine improved baking properties and good pasta cooking quality. Key words: Durum wheat, bread making quality, gluten strength, physical dough properties, pasta cooking quality
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".