Development and sensory evaluation of a potential gluten free bread using chia sourdough
Bibliographic record
Abstract
Generation of novel functional foods are essential for agriculture industry. Sourdough technology is widely used in bread making (leavening properties) and is mainly represented by lactic acid bacteria (LAB) and yeast, whose fermentation confers to the resulting bread its characteristic features such as palatability and high sensory quality. Chia seeds are widely consumed for various health and nutritional benefits, their gluten free properties are essential for celiac patient and in gluten intolerant diet. However, the production of a gluten free bread is a challenge due its low quality and for exhibit poor mouth feel and flavor. Food industry try to replace absence of gluten mainly with starch, protein based ingredients and hydrocolloids in order to mimic the viscoelastic properties of gluten. Fermentation of Chia with starter culture, releases aminoacids and water-soluble polysaccharides that could improve nutritional sensory and technologically food products. Sensory evaluation of Weisella cibaria C-2 inoculated in chia sourdough breads compared with its unfermented and the reference, was conducted by 56 people recruited from the University of Alberta campus. Demographic showed a 44% of population studied consume bread 2-3 times a week, 47% like bread and a 26% consider bread as a favorite bakery product. A 9-point hedonic scale where used to classified different samples. Overall, participants moderately disliked the reference and its texture. Its taste was only slightly disliked. Consumers slightly disliked the 20% sourdough’s taste, texture and the bread overall. The 30 and 40% breads scored the highest, with all categories falling into neither like or dislike. A duo trio test was performed in which 70% of participants could tell that the samples were not the same (p≤ 0.005). Therefore, using fermented versus unfermented chia seed caused differences in sensory qualities. All these data are essential for targeted development of specific functional food products in future projects.
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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 | 0.000 |
| 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) | 0.000 | 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".