Quality Characteristics of Fresh and Dried White Salted Noodles Enriched with Flour from Hull‐less Barley Genotypes of Diverse Amylose Content
Bibliographic record
Abstract
ABSTRACT Fresh and dried white salted noodles (WSN) were prepared by incorporating up to 40% flour from hull‐less barley (HB) genotypes with normal amylose, waxy, zero amylose waxy (ZAW), and high amylose (HA) starch into a 60% extraction Canada Prairie Spring White (cv. AC Vista) wheat flour. The HB flours, depending on genotype, contained four to six times the concentration of β‐glucan of the wheat flour, offering potential health benefits. The HB‐enriched noodles were made with conventional equipment without difficulty. Noodles containing 40% HB flour required less work input during sheeting, probably due to higher optimum water absorption and weakening of the dough due to dilution of wheat gluten. The addition of HB flour had a negative impact on WSN color and appearance, as evident from decreased brightness, increased redness, and more visible specking. The impact of HB flour on cooked WSN texture varied by starch type. Enrichment with HA or normal starch HB flour produced WSN with bite and chewiness values equivalent to or superior to the wheat flour control. Addition of waxy and ZAW HB flour resulted in WSN with lower values for bite and chewiness. The diversity of HB starch types allows tailoring of WSN texture to satisfy specific markets. HB flour also has potential as an ingredient in novel noodle products targeting health‐conscious consumers who associate darker colored cereal‐based foods with superior nutritional composition.
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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".