Production of Dietetic Bakery Product - Tapa-Nan with Functional Additives
Bibliographic record
Abstract
In this study 12 % mixture of mashed carrot and pumpkin and powder of pumpkin seeds and medicinal herbs: St.-John's-wort (Hypericum L); thousand-leaf (Achilea millefolium L.) and licorice root (xty.beat) were used to enrich dietetic bakery product - tapa-nan produced with first grade wheat flour. The effect of addition on dough on its rheological properties, on bread on its physical-chemical and sensory parameters of bread was studied. The results showed that the baking properties of flour and the rheological properties of the dough with additives at a dosage 12% to weight fraction of flour increased significantly (p<0.05). It was found that the introduction of mixture has intensifying effect on the fermentation process, reduces gluten content and strengthens its structural and mechanical properties. Also the reduction of the dough fermentation period and expenses of dried substances were found. Introduction of functional additives increased the water absorption capacity of flour (WAC), lowered dilution of dough consistency; as well its elasticity improved. Physical – chemical parameters of the proposed dietetic national bakery product (tapa-nan) such as moisture, porosity, titratable acidity showed no significantly (p<0.05) different. In appearances, taste, smell and flavor definitions showed that addition of 12 % mixture of mashed carrot and pumpkin and powder of pumpkin seeds and medicinal herbs: St.-John's-wort (Hypericum L); thousand-leaf (Achilea millefolium L.) and licorice root (xty.beat) had more to yellowness. In texture characteristics, the result showed the hardness of bread decreased and chew ability improved. Apart from that, biological value of enriched bread increased.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".