Effects of the addition of waxy and normal hull‐less barley flours on the farinograph and pasting properties of composite flours and on the nutritional value, textural qualities, and <i>in vitro</i> digestibility of resultant breads
Bibliographic record
Abstract
Hull-less barley (HLB), especially waxy HLB, contains many physiologically active ingredients; however, its poor processing performance and end-product quality are unfavorable. In this study, 80% waxy or normal HLB wholegrain flour (WGF) and 20% wheat flour were used for baking bread. The farinograph and pasting properties of composite powders, and the nutritional value, textural properties, and in vitro hydrolysis of resultant breads were evaluated. The addition of a high proportion of HLB WGFs significantly increased the nutritional value of breads, especially the β-glucan contents of waxy HLB breads. The addition of HLB WGFs and a suitable amount of wheat gluten led to a lower degree of softening of HLB bread flours but improved its farinograph characteristics, such as higher water absorption rate, development time, stability time, and farinograph quality number. Although the sensory profiles of HLB breads were considerably lower than those of wheat bread, they still received a good overall acceptability from a panel of sensory evaluators. HLB breads, particularly the waxy types, exhibited higher hardness, gumminess, chewiness, and lower specific volume, glycemic index and equilibrium concentration in starch hydrolysis. After baking, the starch crystallinity of dough changed from A to V type, and the relative crystallinity decreased. Overall, waxy HLB breads had more nutritional value than normal HLB breads. Higher β-glucan and total dietary fiber content in HLB might have a positive effect on the nutritional value of the resultant breads. However, high β-glucan and total dietary fiber was also accompanied by a negative effect on the sensory quality and processing performance of the end product. PRACTICAL APPLICATION: The composite flour with 80 g hull-less barley wholegrain flour, 20 g wheat flour, and 30 g wheat gluten can be substituted in breadmaking. Compared to wheat bread, hull-less barley bread exhibited different but acceptable sensory properties and had more nutritional value, particularly the waxy one. Therefore, a high proportion of hull-less barley could be recommended for bread production.
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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".