Effect of solid-stated fermented grasshopper (S. purpurascens) on gluten-free bread: a nutritional, textural and rheological approach
Bibliographic record
Abstract
The demand for gluten-free bread has surged driven by dietary needs of celiac and gluten-sensitive individuals, as well as growing consumer interest in health-focused diets. Research on gluten-free products is driving the exploration for high-quality protein sources to enhance their nutritional profile. The edible insect powder replacement on bread formulation is the strategy proposed in this work to enhance protein content in gluten-free bread. This study investigates the impact of incorporating solid-state fermented Sphenarium purpurascens powder on the quality of gluten-free breads and doughs made from rice and maize. Breads and dough with 20 g/100 g and 40 g/100 g substitution of base flour with fermented and non-fermented grasshopper powder, were evaluated. Physicochemical analysis revealed substantial protein and fiber improvements in protein and fiber with a substitution of 40 g/100 g, complying with FDA criteria as a "good source of protein." Rheological assessments indicated that the addition of fermented grasshopper powder reduced dough viscosity and starch retrogradation. Textural analysis showed increases in hardness and chewiness when fermented grasshopper was used, which can be potentially disadvantageous for sensory quality of the product. This research highlights the use of fermented grasshopper as a promising protein source for gluten-free bread.
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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".