Sprouted wheat wholemeal as a techno-functional ingredient in hard pretzels
Bibliographic record
Abstract
There has been a growing interest in incorporating sprouted wheat wholemeal (SWW) into whole grain baking, driven by its heightened nutritional content and improved nutrient bioavailability. This study aimed to assess how substituting soft wheat flour (SWF) with various levels of wheat wholemeal (unsprouted and sprouted) impacts the quality and sensory characteristics of hard pretzel sticks, which are globally enjoyed as popular snacks. The dough samples containing wholemeal did not demonstrate the same extensibility as the SWF dough sample. Additionally, substituting SWF with wholemeal increased the resistance to extension. Analysis of the Raman spectra of SWF and two other selected dough samples containing 75 % unsprouted wheat wholemeal (UWW) or SWW indicated α-helix as the dominant protein secondary structure. As the ratio of wholemeal to SWF increased in both unsprouted and sprouted wheat pretzel samples, protein and fiber content increased and starch content decreased, resulting in a decreased peak viscosity in an RVA (Rapid Visco Analyzer) test. The findings also showed no significant difference in hardness between the SWF pretzel sample and all other samples (p > 0.05), except when SWF was replaced with the highest level (75 %) of SWW, resulting in a significantly softer texture. Color analysis revealed that the introduction of wholemeal led to a decrease in the L* value, indicating a darker surface appearance in the samples, likely due to the presence of bran. Finally, sensory evaluation determined that replacing SWF with 25 % SWW resulted in the creation of a sample most similar to SWF in terms of sensory attributes. This research paves the way for future studies and advancements in the formulation and analysis of pretzel dough, creating opportunities to improve both the quality of the product and consumer satisfaction.
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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 | 0.001 |
| 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".