Comparison of vegetable powders as ingredients of flatbreads: technological and nutritional properties
Bibliographic record
Abstract
Abstract Health-driven innovation is transforming bakery products, particularly with non-conventional ingredients. This study aimed to produce healthy and technologically acceptable flatbreads, exploring the inclusion (2%) of vegetable powders (black and green olives, orange peel, lemon, tomato, beetroot, carrot, onion, artichoke, spinach, chard, kale and pak choi). Spinach and chard increased the mineral content (1.42 and 1.30 g/ 100 g) respect to control (1.01 g/100 g). Fibre content ranged from 9.33 to 11.18 g/100 g when added onion, chard, pak choi, tomato or artichoke. Beetroot was the most effective changing the colour (ΔE* 43.09), while tomato reduced the hardness (4.06 vs 5.29 N in the control). Lemon and tomato were effective reducing the extent of starch enzymatic hydrolysis by 65% and 34%, respectively. Vegetable powders can be innovative, natural, sustainable and healthy ingredients in the breadmaking of flatbreads. The incorporation of these non-conventional ingredients opens new opportunities for the bakery industry.
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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 | 0.001 | 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) | 0.002 | 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".