Swelling Index of Glutenin Test for Prediction of Durum Wheat Quality
Bibliographic record
Abstract
ABSTRACT The swelling index of glutenin (SIG) was assessed for suitability as a screening procedure for durum wheat gluten strength. Five sets of samples with a wide range of gluten strength values were collected according to gluten strength parameters and characterized for SIG. Statistical analysis revealed that the SIG and SDS sedimentation tests were both able to satisfactorily account for variations in gluten strength in all sets of samples. However, for most samples, the SIG test was more reliable than the SDS sedimentation test for predicting gluten strength. Furthermore, the SIG test can differentiate samples with glutenin swelling properties that could not be accounted for by intercultivar variation of SDS sedimentation volumes. The percentage of insoluble glutenin in protein is usually a better predictor for gluten strength than the percentage of insoluble glutenin in flour. Similarly, when the SIG values were divided by the protein content of the samples, the resulting proportions were better predictors of gluten strength than the absolute values. Analysis of protein fractions revealed that the insoluble glutenin was the protein fraction most responsible for the SIG value and gluten strength. Extensibility of dough was significantly related to the soluble glutenin content, while the alveograph G index was related to monomeric protein content. The results suggest that screening based on the SIG test would be valuable for comparing durum wheat lines and cultivars for gluten strength and pasta‐making 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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".