Selection of Ontario soybean varieties tailored for specific food processing functionality
Bibliographic record
Abstract
This thesis focused on soybean varietal differences of the Harovinton variety and its eleven derived null-lines which could lead to the breeding of varieties tailored to produce specific functional ingredients. Soy protein gels with different subunit compositions and glycinin/[beta]-conglycinin ratio had distinctive gelation temperatures and resulted in gels with different network structures. The absence of A3 and the combination of A1, A2 and A4 subunits of glycinin enhanced the formation of heat-induced gels. The ratio glycinin/[beta]-conglycinin was not correlated to stiffness of soy protein gels. Changes in the protein composition of the soybean lines brought also changes in the composition of the carbohydrate fraction. Mixed systems containing gluten protein and soy protein from different sources and protein composition affected the gluten properties differently. It was concluded that there is a great potential to enhance the physical properties of soy protein by modulating the composition of the glycinin and [beta]-conglycinin subunits.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".